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Six degrees of freedom(DOF) air bearing spacecraft simulators are the major component of the all physical simulation test system engaged in rendezvous and docking in the third stage of lunar exploration project. Ground simulation of spacecraft motion simulating all six degrees of freedom(DOF) is a challenging problem mainly due to that weightlessness in space is difficult to reproduce on ground, to simulate the space environment with the air bearing spacecraft simulator, the effects of gravity should be minimized. This paper designs a 6 DOF air bearing spacecraft simulator, and an automatic mass balancing system by actuating three proof masses on linear motion stages to compensate the offset between the center of mass (CM) and the center of rotation(CR) for the spherical air bearing system with 3 rotational degrees of freedom on the simulator. This paper propose using nonlinear adaptive control and unscented Kalman filter(UKF) for mass balancing. The stability of the feedback system and the convergence of the estimated unknown parameter are analyzed through Lyapunov stability theory. The proposed methods are simulated based on the data of a 3 DOF air bearing simulator that our team developed, the results show that the performance of the method proposed is better than that of the method has been used.

A dual loop iterative learning control method is presented for macro-micro dual actuator driving systems. As the model and coupling effects of the macro-micro motion system are analyzed, the dual loop macro-micro control structure is employed to attenuate the coupling effects. In addition, dual loop iterative learning control is employed based on the above structure. Then tracking errors of the micro motion system and macro-micro relative displacements are learned to improve tracking performance of the micro motion stage and decrease the macro-micro relative displacement. Finally convergence of the iterative learning control system is analyzed. The proposed method is applied to the macro-micro test bench, which is used to validate effectiveness of the method.

This paper presents an engineering design method of iterative learning control and its application to synchronization control system of the scanner. Firstly, the synchronization control scheme in the scanner is analyzed, and iterative learning control is introduced to reduce the synchronization errors based on the feedback control system. The method employs the time lead factor to compensate phase lag of the closed loop control system of the reticle stage around bandwidth in order to improve convergent domain of the system. Furthermore, a non-causal filter is introduced to enhance robustness of the system and improve convergent performance of the system. In addition, the convergent condition of the synchronization control system is given. Finally, simulated results are illustrated for validating the effectiveness of the proposed method.

Induction machines (IM) are widely employed as actuators in electromechanical driven system, and IMpsilas control problems, the demands of which are to realize energy saving and speed regulation, have become more significant than before. Efficiency and power factor are two crucial indices in energy saving control issues, and to realize economical running with remarkable efficiency and high power factor, optimization of efficiency and power factor are necessary. From the theoretical points of view, the two indices conflicts with each other in a certain conditions and the conventional solutions to these problems can be attributed to steady state optimization by means of rigid calculations, the results of which often lead to neglect of parameterspsila perturbations and lack of adaptation and robustness. Comparing with traditional control decisions, this paper analyses steady state model and dynamical model of IM, indicates that the courses of optimize efficiency and power factor can be regarded as to solve a kind of speed regulation issues with multiple parameters and conditionspsila restrictions, and proposes a new control method on the basis of soft computing. Simulation results show two indices follow their optimal points on the conditions of parameterspsila perturbations, and state variablespsila curves approach nearer to the optimal point than PID strategies. It has provided a theoretical support to practical applications.

At the condition of periodic boundary, motor vehicles traffic flow with different-maximum-speed vehicles mixed on one-way and single lane is the target of research. Based on NS models of traffic flow, the relative velocity among vehicles is taken into account. And the renewal rules of NS model are revised. It is mainly to raise the driving speed by correlating stochastic probability of speed-down with velocity. Mixed traffic flows with two-different-maximum-speed and three-different-maximum-speed are acted examples to be simulated. On the basic of the result of simulation, the velocity of mixed traffic flows is up to the velocity of slow vehicles. So for improving the velocity of high-speed roads, the limitation of the lowermost velocity is needed to be raised. The traffic capacity of high-speed roads also can be increased.

Soft-start and effectively running of thyristor controlled induction motor (IM) system with light-loads has been proved to save energy and improved the efficiency. The complex characteristics of IM often bring difficulties to electrical driven system. Due to its nonlinearity, strong coupling, high orders and uncertainties, only are studied the input and output characteristics in conventional applications. From the system point of view, during the course of soft-start, shaftpsilas pulsations make the dynamic performance worse. Traditional system analysis and modeling still completely depend on steady circuit calculation, the result of which leads to weakness of dynamic performances. This paper has listed open loop and close loop modes to control IM, has proposed a method of combining artificial neural network (ANN) identification with RBF network and dynamic information acquisition, and has present a modified algorithm to suppress stator current pulsation. Comparison of simulation results, experiment data and actual waveform, the validity of the design has been verified. It has provided theoretic support to industrial applications.

The complex principles of induction motor often bring difficulties to electrical driven system. Due to its nonlinearity, strong coupling and uncertainties, the input and output characteristics are only considered in conventional applications. Thyristors still occupy part of the driven fields where precise speed regulation is not needed, and some solid state controllers have been put into practice. However, from the view point of the system, the performance analysis and modeling of thyristor driven induction motor system still completely depend on circuit calculation. This paper has proposed a method of combining circuit calculation with RBF neural network approximating, and has designed a controller with NN. Comparison of simulation results, actual waveform and experiment data, the validity of the design has been verified. It has provided theoretic support to conventional applications.

In order to accelerate the convergence rate of the ant colony algorithm and avoid the stagnation behavior, a novel ant colony system developed from max-min ant system is present. The methods including multi-ant colony, improving state transition rules, introducing parameter mutation method according the convergent requirement are used in the algorithm. It is applied to the vehicle routing problem with time window. Experimental results show that algorithm has much higher capacity of global optimization and improve the speed of convergence efficiently.

In this paper, the author has aimed at the variable-voltage controlled induction motor, analyzed the steady-state performance of variable-voltage thyristor controlled induction motor system, and presented the mathematic model and circuit model of such system. Power factor, as a significant variable to measure the efficiency of motor operation, is particularly studied in the paper, and the control strategy based on the studies of power factor and slip is given. The simulation curves and real waves are shown in the result. Finally, the transient performance of induction motor is mentioned. The analysis and results reveal that such system based on the special arithmetic is available.