Unmanned ground vehicles (UGVs), which are of great strategic significance for developing high maneuvering unmanned ground combat systems, have become a research hotspot of defense technology. The development and current progress of UGVs for military application are reviewed. The fundamental components and development characteristics of military UGVs are stated and analyzed. The key technologies of military UGVs are also summarized in the areas of sensing and perception, motion planning and path tracking. In addition, the future research direction and focus of military UGVs are suggested.

Intelligent vehicle, which has great advantages in enhancing the driving safety and diminishing road accidents, has become an emerging research focus worldwide. The development and research current status of lateral control for intelligent vehicles at home and abroad are reviewed. The research process and modeling of vehicle lateral dynamics and tire dynamics, the theory and methods of lateral control, and the automatic steering actuator design are discussed and summarized. Several research issues and development trends of lateral control of intelligent vehicles are presented, in which the modeling of vehicle lateral dynamics and the lateral controller design concerning the nonlinearity, uncertainties and time-varying characteristics, particularly in high speed lateral control, and the integrated design combining sensing, perception and decision-making systems with vehicle system dynamics will be research focuses in the future. Key

A new method for partial image recognition and tracking in the infrared imaging terminal guidance is proposed for the problem of that the field-of-view of infrared seeker filled with target affects target recognition and tracking. The principle of infrared imaging guidance is analyzed. Five characteristic quantities, such as highlight region proportion, standard deviation of gray value, length-width ratio, compactness and complexity, are used as the criteria of feature extraction and target recognition. A fast target recognition algorithm suitable for missile is proposed. The change of target image projection area on seeker’s focal plane in the infrared imaging terminal guidance is calculated. The effects of missile-target distance and relative velocity on aircraft imaging are analyzed. The switching from centroid tracking to partial image tracking is studied. Considering reliability and real-time, the nose cone of aircraft is selected as the tracking point for partial image tracking. The simulation scene of infrared imaging guidance is built. The simulation results are analyzed. Experimental results show that the proposed method can effectively recognize the targets in the infrared images, decrease the blind area, and realize the steadily tracking in the infrared imaging terminal guidance.

Unmanned aerial vehicle (UAV) cloud can greatly enhance the intelligence of unmanned system by dynamically uploading the compute-intensive applications to the cloud. The different UAV missions may have different quality of service (QoS) requirements due to the uncertainty of UAV missions and the fast-changing battlefield environment. A BP neuron network-based feedback differentiated control approach for QoS-aware (BPFD)-MAC in UAV cloud is proposed, which can support both absolute and relative QoS guarantees with the consideration of energy saving. The hardware experiments demonstrate the feasibility of BPFD-MAC. Under heavy loads, BPFD has better throughput and power use efficiency; and underlight load, BPFD has lower total energy consumption.Key

A flight path tracking problem is studied for underactuated UAV in 3D space. The question of flight path tracking is transformed into way-point tracking by choosing a serious point on flight path. A mathematic model is established.The speed frame is alined to the desired frame so that position tracking is converted into attitude tracking. The guidance law is also deduced, and the theories of sliding variable structure and back-stepping are used to design the attitude controller and velocity controller. The direction of velocity vector is aligned to the position of a way-point by using the attitude controller. The speed of UAV is controlled by the velocity controller to make the UAV closing to a way-point. The guidance and control systems are simulated. The result shows that the designed controller is perfect in tracking and have a strong robustness.

A method to estimate the attitude of micro UAV based on the sparse line optical flow field is proposed according to the requirements for UAV vision-based navigation system.The concept of sparse line optical flow field of images is described, and an algorithm of sparse line optical flow field is presented. A new method to estimate the attitudes of micro UAV, including pitch rate, roll rate and yaw rate, is proposed based on the sparse line-optical flow field and the established horizon projection model. The proposed method and the classic Horn algorithm are used to numerically simulate a group of test images for calculating the optical flow field. The results show that the proposed method has the same calculation accuracy as the classic Horn algorithm, while the calculating time-cost of the former is only 6% of Horn algorithm. Taking an aerial image sequence as test samples, an off-line simulation is conducted to verify the method of UAV attitude estimation based on sparse line-optical flow field. The information calculated with the measured values of angular velocity gyro on UAV is compared. The comparative result shows that the proposed method is efficient for estimation of pitch, roll, and yaw rates of UAV. The calculated error of pitch rate is less than ±10(°), while the errors of roll and yaw rates are less than ±5(°)/s .

The issue of formation attack trajectory planning for cooperative air-to-ground attack of unmanned combat aerial vehicles (UCAVs) is investigated. A formation trajectory planning model is built based on single UCAV three degrees of freedom equations, relative movement model and UCAV initial and terminal states constraints. The cost function is constructed, which consists of single UCAV threat and task time, number of equivalent collisions and time error of executing command. The solution framework of optimal control method is formed based on the formation model and cost function. The whole trajectory is optimized by dividing it into three segments, and every segment is resolved by hp adaptive pseudospectral method. The simulation results show that the optimized formation attack trajectory satisfies the constraints, and the formation attack trajectory planning model is provn to be effective.

In view of the fact that the conventional joint fire attack mission planning method rarely involves an issue offriend-foe confrontation leading to the change in evaluationenvironment, a smart confrontation evolution algorithm based on the evolution of friend-foe confrontation is proposed. The proposed algorithm is based on genetic algorithm, in which the simulation of biological competition mechanism is introduced into the two populations of friend and foe for implementing the confrontational evolution. An observe-orient-decide-act (OODA) super-network is constructed based on the battlefield situation map, and then the OODA cycle efficiency is calculated to determine theorder of friend and foe attacks.The task-planning optimal individuals can adapt to the dynamic changes of the battlefield through the confrontation evolution of multiple generations. The simulated results show that the multi-generation evolutionary optimal individual has stronger dynamic adaptability, and the joint firepower strike rate is higher. The response mechanism to respond to the emergencies is more perfect, which can effectively solve the evaluation optimization issues of joint firepower mission planning. Key

Trajectory tracking control of unmanned tracked vehicle is challenged by complex system uncertainties and external disturbances. A kinematic model based on the instantaneous steering center is developed by studying the interaction between track and ground. Considering the fact that the reference path is a series of discrete waypoints, an adaptive reference path fitting method, which utilizes the third-order Bezier curve, is presented for path smoothing while providing road curvature information. Taking the unavoidable system uncertainty and external disturbance into account, a model predictive control based trajectory tracking controller with feedback correction is designed to systematically handle the modeling errors, environmental constraints, and actuator saturations. Real vehicle tests demonstrate that the proposed control scheme can be used effectively to restrain the effects of system uncertainties and external disturbances, while achieves the satisfying trajectory tracking performance of unmanned tracked vehicle. Key

For an unmanned aerial vehicle (UAV) with high-mounted wings, a simplified analytical model is established to analyze the cushioning characteristics of a soft landing airbag system and determine the initial design parameters of the soft landing airbags. A finite element model is established and a series of simulations are conducted to analyze the influence of design parameters and landing attitude angle on cushioning characteristics. Numerical results show that the results obtained by FEM and the analytical model are the same, but the errors of impact response values calculated by two models are still 5%~12.5% because of the introduction of some assumptions in the analytical model; and the existence of initial landing attitude angles makes the pitch and roll motions of UAV much worse in the later stage of landing process, so that the rigid impact occurs easily. However, a vented airbag system is incapable of avoiding the local damage caused by the rigid impact. The study also shows that the proposed hybrid airbag scheme can provide a reliable soft support in the later stage of soft landing process and reduce the risk of suffering the rigid impact.

The modulation classification of the non-cooperation underwater acoustic communication signals is extremely challenging due to channel transmission characteristics and low signal-to-noise ratio. The principal component analysis (PCA) is used to analyze the power spectra and square spectrum features of signals, which is capable of extracting the principal components associated with different modulated signals as input vector, thus reducing the feature dimension and suppressing the influence of noise. An artificial neural network (ANN) classifier is proposed for modulation recognition. The experimental modulation classification results obtained from field signals in 4 different underwater acoustic channels show that the proposed modulation recognition method has good classification performance.

The path tracking problem for intelligent vehicle with delayed control inputs is studied. The cramping angle is expressed as a series structure model with pure lag and first-order inertial delay, and a steering control delay model is established using Matlab/Simulink. The collected steering control data of an actual vehicle is analyzed for parameter identification of the proposed delay model.The equivalent delay performance in simulation environment based on V-REP and ROS is implemented. The model predictive control (MPC)-based path tracking controllers without or with considering delay controlare designed based on Frenet coordinates, and the kinematic and dynamics models, which can also be used for marching vehicle formation. A curvature-variant reference paths collected at 5, 10 and 20 m/s are set in V-REP simulation environment. Three curvature-variant reference paths are presented. For the MPC path tracking controller without delay modeling, the average tracking error is less than 0.22 m for a vehicle platform without control delay. The MPC controllers with and without delay modeling are tested to compare their tracking performances for the vehicle system with long control delay. Simulated results indicate that the average and maximum tracking errors of MPC controller with delay modeling are 83.7% and 74.4% less than those of MPC controller without delay modeling when they are used on a vehicle with delayed control inputs. The kinematics-based MPC controller performs better at low speed, whereas the dynamics-based MPC controller performs better at high speed. Only dynamics-based MPC controller with delay modeling completed the whole test safely at 20 m/s on the vehicle with delayed control. Key

A novel multi-sensor information fusion identification method is proposed for the low accurate rate of the transmitter individual identification caused by the various jamming signals and sensor error, which can enhance the stability and accurate recognition rate of the transmitter individual identification in the complicated environment. The proposed method integrates the Dempster-Shafer evidence theory and feature extraction to get the utmost out of feature information and decrease the influence of uncertain factors in the signal processing. The features are extracted from the detected signals. The self-adaptive fusion rule based on the decision vector is utilized to fuse the evidences transformed by features. The recognition results can be obtained by judgment rules. The simulation analyses of self-adaptive fusion rule and fusion identification method are performed, respectively. The results show that the self-adaptive fusion rule can achieve a great balance between computational efficiency and accurate identification rate. Compared with other identification methods, the proposed fusion identification method can provide more accurate and stable recognition results.

Formation recognition is an important research task in the area of target recognition for anti-ship missile weapon systems. Perfect formation recognition capability can improve the target selection of anti-ship missiles for compact warship formation, thus enhancing the hit probability and operational effectiveness of anti-ship missiles. The formation recognition algorithm is researched base on Hough transform, which has higher recognition rate without the influence of detection noise. If the target information is polluted badly, the improved K-means clustering algorithm is used to cluster the local peaks in an accumulation matrix. The shape parameters of formation to be recognized can be extracted from the clustering results so that the adverse influence due to detection noise is restrained effectively. Even though the target information is polluted badly, the algorithm has better recognition accuracy and robustness. The complexity of the algorithm and the effect of target designation error on the accuracy of the algorithm are analyzed. The simulation results show that the proposed algorithm has the perfect capability of formation recognition.

Digital pattern is a new camouflage technique, which has better camouflage effect. For the problem of low efficiency of artificial painting，four detection techniques, such as the 3D square grid modeling of military equipment, the 3D digital pattern model generation, the spraying automatic path planning and the real time detection of lance position, are solved. A digital pattern automatic painting system is constructed. Test results show that the application of automatic system can effectively improve the painting efficiency of digital pattern, and promote the further development of digital pattern technology.

The action reliability is an important factor which must be considered in the design of mechanisms, and is a key index to evaluate the quality of a system. The main parameters influencing ejection action reliability are determined, and a rigid ejection reliability analysis and design process of automatic rifles is set up. A simplified virtual prototype model of rigid ejection action reliability is established. The simulated results show that the position of ejector, the backplate position of ejection port and the ejection velocity are the dominant factors which have effect on ejection action reliability; as the ejection velocity is high enough, gravity has less effect on ejection action reliability.A method to determine the position of ejector is presented, and the calculational equations are established for location dimension of ejection port. An adjustable backplate of ejection port mechanism is designed to test in the shooting experiment. The experimental results are consistent with the simulated results. It shows that the validity and suitability of the proposed method are verified.Key

The traditional DOA (direction of arrival) estimation methods of underwater acoustic target often have poor estimation performance or provide inaccurate estimation result under the constraint of spatial sparse observation based on the small platform (such as unmanned underwarter vehicle). A new highaccuracy DOA estimation algorithm based on spatial compressive sampling for underwater acoustic target is proposed by analyzing the space sparsity of underwater target location. The algorithm is used to establish a spatial sparse description model of underwater target, and compress the underwater target in spatial domain, and then the joint sparse reconstruction algorithm is used to achieve the DOA estimation of underwater acoustic target. The simulation results show that the method can increase the DOA estimation accuracy in the case of less array elements and less snapshots, and the high success rate can be increased by more than 50%, and the root mean square error in the low SNR environment can be maintained at 02°or less.

The control parameters can not be provided for the model-based control algorithm, which leads to the undesirable control performances of the system since the depth motion model parameters regarding the unmanned semi-submersible vehicles (USVs ) BQ-01 are unknown. For this purpose, a multi-identification model-based dynamic sliding mode control algorithmis presented for the investigation of system's control problem on the desired depth. In the proposed algorithm, the average-fitting-error method is used to reduce the excessive redundant model parameters, and thusthe optimum model parameters is provided for the control algorithm by switching methods. And the state feedback method is used to bring about the chattering exponential decay of sliding mode controller so as to reduce the settling time. The experimental results of lake trials demonstrates that the proposed algorithm could offer the best model parameters for sliding mode control, and the dynamic sliding mode control with multi-identification models is capable of ensuring BQ-01 system to achieve the ideal control performance. Key

The limited forms of atoms in analytical dictionary lead to sub-optimal matching of atoms and complex emitter signal, resulting in low recognition rate of signal modulation. A dictionary learning method based on Fisher discrimination criterion is proposed to improve the recognition efficiency. The time-frequency transformation of emitter signal is made. The feature vectors are extracted from time-frequency graph using image processing method, which are added class labels. In the dictionary training, the Fisher criterion with small within-class scatter and big between-class scatter is introduced, by which the dictionary not only represents signal more suitably, but also owns better classification performance. The simulated result proves that, compared to analytical dictionary and non-supervision dictionary, the proposed method can obtain a better recognition rate, especially under low SNR. For the atom number N_s=20, Fisher discrimination dictionary can achieve a pretty good balance in recognition rate and calculation amount. Key

Thread connection is one of the main forms of connection between penetrating projectile and fuze body. To address the problem that thread connection can not be represented accurately by way of the existing dynamic numerical analysis, a method of simulating the thread connection using thin-layer elements is proposed, and a method for identifying the material parameters of thin-layer element based on test results is established. Modal test of pipe threads was carried out.The influences of the amplitude of excitation force and the loose and tight connection of threads on the modal frequency and frequency response curve are discussed, and the thin-layer element method is used for the simulation calculation of pipe threads. Results show that the state of loose thread connection is much more affected by non-linear factors compeared with tight connection; the magnitude of excitation force exerts greater influence on the measured result of loosely connected threads; the maximum error of modal frequency is reduced from 26.66% to 1.35% by comparing the simulated results of thin-layer element with the fixed nodes. Key

A consistency theory-based distributed formation control strategy is proposed for the multi-UAVswith nonlinear dynamic characteristics, in which the communication delay is changed in bounded interval and the network topology is jointly-connected. The Lyapunov-Krasovskii function is used to analyze the formation stability and deduce its sufficient conditions. The derivative characteristic of time-delay is not considered, and the high dimensional matrix solution of communication topology is transformed into low dimensional matrix solution with several connected parts. The proposed strategy has the advantages of wide applicability, low computational cost and excellent real-time performance. The effectivity of the proposed method in the cases of nonlinear fast-varying and random hopping delays was verified through simulation experiment. Experimental results show that the proposed strategy can be used to direct the multi-UAVs to assemble and converge to any symmetric or asymmetric target formation with scheduled speed. Key

In order to perform the feasibility study on the application of automatic mechanism for gas and floating barrel operated automatic action in high muzzle velocity grenade launcher(HMVGL) and reduce the recoil of weapon system, the structure parameters of gas operated device is adjusted, and the recoil energies of the barrel and bolt carrier assembly are matched. The basic equations of interior ballistic and flow problems which consider the effects of heat loss and floating barrel are derived based on aerodynamics and thermodynamics. The performance characteristics of automatic mechanism and the recoil-time curve are obtained by the calculation and simulation of launch dynamics of HMVGL. The reliability of the model is validated by comparing the simulation and experimental results. The pressure fluctuation of gas chamber is discussed with regard to gasport diameter, gas-port position and initial gas volume. The speed curves of automatic mechanism and the recoil curve are also analyzed. By means of automatic mechanism based on the gas and floating barrel operated automatic action, the maximum recoil of HMVGL can be limited within 1 100 N to achieve a low recoil launching.

For slow convergence speed, large steady mean square error (MSE), and blind phase of the constant modulus blind equalization algorithm (CMA), a multi-modulus blind equalization algorithm based on shuffled frog leaping algorithm (SFLA-MMA) is proposed, which combines the basic idea of intelligent optimization algorithm and introduces the individual own evolution and social behavior among individuals into the blind equalization technology. In the proposed algorithm, the reciprocal of the cost function of multi-modulus blind equalization algorithm (MMA) is defined as the fitness function of the shuffled frog leaping algorithm (SFLA), the position vector of the frog individual in the frog group is regarded as the initial weight vector of MMA. The optimum location vector of the frog groups is searched using the global information sharing mechanism and local depth search ability of SFLA, and used as the initial optimum weight vector of the MMA. The optimal weight vector of MMA is obtained by updating the weight vector of MMA . The proposed SFLA-MMA is simulated with the higher-order multi-modulus QAM and APSK signals. The simulation results show that, compared with CMA, MMA, and the multi-modulus blind equalization algorithm based on particle swarm optimization algorithm (PSO-MMA), the proposed SFLA-MMA has the fastest convergence speed, the smallest MSE, and the clearest constellations of output signals.

An UCAV (unmanned combat air vehicle) robust maneuver decision method based on statistics principle is proposed for UCAV robust autonomous combat decision. A mathematic model of UCAV is built to reduce the sensibility of the combat maneuver decision. The typical maneuver library is improved, and the robust membership functions of the air combat situation parameters are designed. The statistics method is introduced in the robust maneuver decision, and the simulations are carried out with two typical air combat cases of UCAV confront maneuver and non-maneuver objects. The simulated results indicate that the robust maneuver decision method has the robustness and optimizing capability in guiding UCAV to the advantage situation. Key

In allusion to the problem that contribution rate evaluation of weapon equipment system has highly complexity and great difficulty due to multitudinous relation factors, a research framework is proposed based on the systematic analysis of contribution rate conception. For the contribution rate evaluation of a new intelligent armoured combat system, an evaluation index system is established from the viewpoints of functional completeness, architecture optimization, operational capability enhancement and technological progress. The contribution rate evaluation of a new intelligent armoured combat system is systematically studied by using an evidential reasoning approach based on the belief rule base. The result shows that the contribution rate of weapon equipment system is a comprehensive characteristic parameter describing the position and function of weapon equipment system, its evaluation must be systematically studied from multiviewpoints and multilevels, and the evidential reasoning approach based on the belief rule base is an effective, scientific and practical method for solving the contribution rate evaluation of weapon equipment system. Key

Characteristic information is hidden in the received signal of active torpedo electromagnetic fuse. The conventional burst controlling strategies based on energy-comparison are affected by ambient and electromechanical noises. The improved algorithms based on digital signal processing techniques are proposed. The received signals are first processed by all-phase compensation method to eliminate the direct coupling component, and then the residual signal is demodulated using STFT. An improved polynomial least mean square approximation method, which reduces the computation time, is presented for eliminating the side-effects brought by noise. A parametric estimation model base on bell-shape impulse is used to estimate the maximum of echo envelope. Simulation and trial data show that the proposed algorithm is effective and practical.

Rational intelligent and information design of armored vehicles is of great significance to reduce the mental workload and improve the effectiveness of armored vehicle occupants. In order to investigate the influences of intelligent design and complexity of information processing modality on occupant mental workload, and based on a new armored vehicle simulation platform, 20 subjects were selected to carry out a comprehensive experiment on the influencing factors of occupant mental workload according to the typical operational task of armored vehicle commander. The test results show that the NASA-TLX rating scale score, alpha band absolute power and task false operation rate under the condition of high-intelligent task are lower than those under the condition of low-intelligent task, and the saccade average peak speed under the condition of high-intelligent task is higher than that under the condition of low-intelligent task; in the audio-visual dual modalities task, higher NASA-TLX rating scale score, theta band absolute power and average pupil diameter are observed compared with the single visual modality task. The occupant mental workload under the condition of high-intelligent design is significantly lower than that under the condition of low-intelligent design, and the automation operation and intelligent human-computer interaction mode can effectively reduce the occupant workload of occupant under the high demand for information. The occupant mental workload under the condition of audio-visual dual modalities task is significantly increased compared with the single visual modality task, while the use of dual audio-visual modalities information processing mode is conducive to ensure a better performance under multi-task demands. In addition, the different physiological measurement indices have distinguished sensitivity and diagnostic ability to the influencing factors of mental workload.

A strategy of hill-start control is presented for military heavy-duty wheeled vehicles with automated mechanical transmission(AMT). A concept of that the opening degree of accelerator pedal, the engine speed and the decline rate of engine speed are used to estimate the clutch transmitting torque is put forward based on the dynamics analysis of hill-start process of vehicle and the engine speed characteristic curve. And also the parking brake release conditions are identified. The clutch control strategy is designed based on the existing experimental vehicle platform, and the satisfactory results are achieved when vehicle tests are carried out at the different angles of slopes. The experimental results show that the proposed theory is feasible.

A novel adaptive path following controller was presented for a miniature autonomous helicopter with uncertain inertial parameters and external disturbance. It was implemented by using dual-loop structure, including an outer-loop for path following and an inner-loop for attitude control. The outer-loop controlled the attitude angles and lift forces to track the expected path and velocity, and the inner-loop was designed as a attitude controller based on L₁ adaptive controller. The uncertain inertial parameters were and external disturbance were also compensated online by using parameter adaptive update laws in the inner-loop. The stability analysis for the inner- and outer-loop was provided separately and the closed-loop stability analysis was given on the basis of time-scale separation assumption. Finally, a simulation and a flight test were carried out. The results demonstrate that the feasibility and performance of the proposed controller.

A novel method for coalition formation of multiple heterogeneous unmanned aerial vehicles in cooperative search and attack in unknown environment is presented to improve the cooperative search and attack effectivenesses of multiple heterogeneous unmanned aerial vehicles. A coalition formation model is established based on the minimum target attack time and the minimum coalition scale with the constraints of required resources and simultaneous strike. A multistage sub-optimal coalition formation algorithm (MSOCFA) that has low computational complexity is proposed to solve the optimization problem of coalition formation. The performances of MSOCFA and partical swarm optimization algorithms are compared in terms of mission performance, complexity of algorithm and time taken to form the coalitions. In order to enable the multiple cooperative unmanned aerial vehicles to accomplish the search and attack missions autonomously, a distributed autonomous control strategy is proposed, which is based on the finite-state machine (FSM). The simulation results show the rationality, validity and high real-time performance of the proposed method for the coalition formation of multiple heterogeneous unmanned aerial vehicles in cooperative search and attack in the unknown environment. Monte Carlo method is employed to validate the impact of the number of unmanned aerial vehicles and targets on coalition formation. The reduced average mission completion time relates to the decreased number of targets and the increased the number of unmanned aerial vehicles.

A dynamic model of tricycle-undercarriage-UAV ground maneuvers is established using elastic tire theory. With full consideration of loads applied to UAV, the model can describe the process of the UAV ground maneuvers exactly. The simulation is based on a series of parameters of a real UAV. The constraints are put forward by analyzing some data from simulation, which affect the ground maneuvers of UAV. At last, the available range of UAV ground maneuvers is given.

A kind of auto disturbance rejection controller(ADRC) based on genetic algorithm for keeping UUV depth was designed according to the characteristics of UUV maneuvering. Because of more parameters of ADRC, its parameter design was transformed to parameter optimization. The controller parameter of ADRC in a UUV depth control system was optimized by using the genetic algorithm. The depth control of UUV was simulated without disturbing and near the surface. The simulation results show that the ADRC controller has better depth keeping and antijamming performances. Compared with the conventional PID controller, the amplitude and the frequency of steering controlled by ADRC controller are reduced much more obviously. The control quality of ADRC is significantly improved.

The cooperative navigation and localization technology of multi-USVs is an important way to solve the navigation problem in complex environment. For the cooperative navigation and localization of multi-USVs with leader-follower structure, a state space model of cooperative localization is built, and then a linear model is obtained by expanding the nonlinear model around filter value. An extended Kalman filter is designed to fuse the sensor information to locate the slave USV in real time. At last, the relationship among USV distances, angle and accuracy is researched, and the observability analysis of cooperative navigation filter algorithm is done with Lie algebra. The results show that the navigation accuracy is improved effectively by controlling the variations of distances and angles of leader and slave USVs between two adjacent moments, which is verified by simulation and experiment.

The electronic control brake technology for unmanned driving is researched based on a 4×4 manned light tactical wheeled vehicle. An electropneumatic brake system is designed according to the structure and characteristics of the original vehicle air brake, which realizes an electronic control brake function in unmanned driving mode, and reserves the manual brake function in manual driving mode. The two modes can be switched freely. The control characteristics of solenoid valve, vehicle rolling resistance coefficient on different roads, and the relationship among vehicle deceleration, speed and control input of electronic control brake are identified through vehicle test. The test results show that the electropneumatic brake system can rapidly and accurately respond to the braking request, and the user can flexibly switch between manual braking and electronic-controlled braking. The electropneumatic brake system can be used for the commercial vehicles.

In order to intercept the maneuvering targets and overcome the adverse effect of the missile autopilot’s dynamics on the guidance performance, this paper aims to propose a H_∞ robust guidance law with the dynamics of the autopilot considered. The third-order linear time-varying state equation for the integrated guidance and second-order dynamics of autopilot is expressed as a polytopic LPV system. A novel H_∞ robust guidance law, in the form of linear state-feedback with parameter-dependent gain, is designed using LMI method. The coefficients in the parameter-dependent gain are obtained by solving a convex optimization problem with LMI constraints. Simulation results indicate that, even if the target’s acceleration is not known, the H_∞ guidance law can still achieve strong robustness and obtain high guidance precision.

The prototype of a high firing rate automatic mechanism of a gun has a periodic fire stop failure during firing. The classical thermal expansion theory and the finite element method are used for the thermal-structure coupling analysis of high firing rate automatic mechanism. The analysis results show that the size of its structure can be appropriately adjusted to meet the requirement of the current firing rate and further improve the rate of fire. The improved structural design of demonstration prototype has non periodic fire stop phenomenon after several rounds of live ammunition tests. Thermal-structure coupling method can be used to solve similar failures in engineering practice.

The containment protocol proposed in the previous researches does not take the collision among followers into consideration under certain conditions. The containment of second-order nonlinear multi-agent system with collision avoidance mechanism around formation is studied based on the graph theory, matrix analysis and nonlinear analysis. The static and adaptive protocols are proposed, respectively. Lyapunov method is used to obtain the sufficient condition for stability of protocols. The simulations are used to verify the effectiveness of the containment control protocols. The protocols can make followers’ trajectories finally converge to a finite radius from the convex hull spanned by leaders’ trajectories, and keep the distances among followers being more than the safe distances all the time.

In allusion to the degenerative state recognition of rolling bearing, a performance degenerative recognition method based on mathematical morphological fractal dimension (MMFD) and fuzzy center means (FCM) is proposed by combining mathematical morphology and fuzzy assemble theory. MMFD is calculated for the performance degenerative feature of rolling bearing to describe its complexity and irregularity in the view of fractal. In consideration of the fuzziness among different performance degradation boundaries, FCM is introduced into fuzzy clustering for characteristic index, and the performance degradation could be recognized effectively in line with maximum subordinate principle. The fatigue life enhancement test of rolling bearing was carried out to gather the whole life data at Hangzhou Bearing Test & Research Center. The method is applied to the whole life data of rolling bearing, the overall state successful recognition rate reachs 96%. The results show that the method has a small calculating cost and a high efficiency, and can efficiently identify the performance degenerative state of rolling bearings.

An effective optimal control strategy is proposed in order to solve the stable control problem produced by the disturbance on unmanned underwater vehicle (UUV) in low-speed state. The system state equations with double input of the level rudder and buoyancy compensation are obtained by establis- hing a UUV longitudinal plane movement mathematical model and linearizing the model, and then a line- ar quadratic optimal control scheme based on buoyancy compensation is designed. The optimal control scheme is compared with the classical control scheme through simulation. The result shows that the opti- mal control scheme can shortens setting time by half, and more quickly and effectively make the disturbed system stable.

At present，the layer-count algorithm of penetration fuse usually uses one or more fixed thresholds to judge the target layer. The setting of threshold usually depends on the prior data. And there is no such a threshold which can fit all test conditions. For this problem， an adaptive threshold layer-count algorithm is proposed based on the fusion signal algorithm. The proposed algorithm uses the sensor signals collected by fuse to calculate the decision threshold of the next target in real time and online. Then the current number of layers is identified according to the calculated threshold. The simulated results show that the proposed algorithm can give the layer identification signal correctly under different test conditions compared with the fixed threshold algorithm.And the layer identification signal given by the proposed algorithm is in good agreement with the time recorded by high-speed camera in the actual test.