This paper is concerned with the problem of hypersonic vehicle (HSV) attitude control system in uncertain flight conditions. The problem can be expressed as the adaptive robust control for a class of uncertain nonlinear systems. Based on the description of the aerodynamic structure and the model of flight control system of a certain kind of HSV, the ideal nonlinear generalized predictive control (NGPC) law based on uncertain nonlinear model is raised first to optimize the receding-horizon criterion of tracking errors. Then the online support vector regression (SVR) is employed to identify the uncertain item in the ideal control law. It is the compensating part of the controller. In addition, the stability of the close-loop system is analyzed using the Lyapunov method. The developed control strategy is well-implemented in this HSV attitude control system, and the simulation results compared with both nominal NGPC and RBF neural network disturbance observer show the good robustness and disturbance attenuation ability of this strategy and demonstrate the efficiency of online SVR algorithm.
This paper proposes a states feedback control method for Z-axis MEMS gyroscopes using fractional calculus and adaptive dynamic sliding mode control method. A new sliding mode control method is proposed to achieve trajectory tracking by adding a fractional order term in the conventional sliding manifold. The new proposed sliding surface contains integer order terms as well as fractional order terms and thus can provide an extra degree of freedom. Besides, in the presence of unknown system parameters, some adaptive laws containing the new designed sliding manifold are proposed to online tune controller parameters. All adaptive laws are derived in the stability framework and the stability of the control system is also guaranteed according to the Lyapunov stability theory and. Simulations results on a Z-axis vibrating gyroscope are provided to illustrate the effectiveness of the control method.INDEX TERMS Adaptive control, dynamic sliding mode control, gyroscope, fractional order calculus.
An adaptive prescribed performance sliding mode control (APPSMC) of Micro-Electro-Mechanical System gyroscopes is proposed for the trajectory tracking in the presence of parameter variations and external disturbances. Steady-state error, transient error and convergence rate are important performance indexes in gyroscope systems. However, these indexes have not been investigated and corresponding control methods are not investigated as well. The proposed APPSMC scheme can guarantee that the tracking error is strictly within a predefined performance bound and the convergence rate is no less than a predefined value. All the gyroscope parameters including the angular velocity can be correctly estimated by adaptive laws and the disturbance bound is estimated by a neural network estimator to alleviate the chattering problem. Simulation results demonstrate the effectiveness of the proposed adaptive prescribed performance sliding mode controller.
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