Robust control for uncertain impulsive systems with input constraints and external disturbance

Author(s):  
Xuyang Lou ◽  
Xin Zhang ◽  
Qian Ye
Author(s):  
Dalong Tian ◽  
Jianguo Guo

This study aims to develop an advanced integral terminal sliding-mode robust control method using a disturbance observer (DO) to suppress the forced vibration of a large space intelligent truss structure (LSITS). First, the dynamics of the electromechanical coupling of the piezoelectric stack actuator and the LSITS, based on finite element and Lagrangian methods, are established. Subsequently, to constrict the vibration of the structure, a novel integral terminal sliding-mode control (ITSMC) law for the DO is used to estimate the parameter perturbation of the LSITS based on a continuous external disturbance. Simulation results show that, under a forced vibration and compared with the ITSMC system without a DO, the displacement amplitude of the ITSMC system with the DO is effectively reduced. In the case where the model parameters of the LSITS deviate by ±50%, and an unknown continuous external disturbance exists, the control system with the DO can adequately attenuate the structural vibration and realize robust control. Concurrently, the voltage of the employed piezoelectric stack actuator is reduced, and voltage jitter is alleviated.


2020 ◽  
Vol 10 (13) ◽  
pp. 4494 ◽  
Author(s):  
Lijun Feng ◽  
Hao Yan

This paper focuses on high performance adaptive robust position control of electro-hydraulic servo system. The main feature of the paper is the combination of adaptive robust algorithm with discrete disturbance estimation to cope with the parametric uncertainties, uncertain nonlinearities, and external disturbance in the hydraulic servo system. First of all, a mathematical model of the single-rod position control system is developed and a nonlinear adaptive robust controller is proposed using the backstepping design technique. Adaptive robust control is used to encompass the parametric uncertainties and uncertain nonlinearities. Subsequently, a discrete disturbance estimator is employed to compensate for the effect of strong external disturbance. Furthermore, a special Lyapunov function is formulated to handle unknown nonlinear parameters in the system state equations. Simulations are carried out, and the results validate the superior performance and robustness of the proposed method.


2016 ◽  
Vol 4 (5) ◽  
pp. 460-475 ◽  
Author(s):  
Longsheng Chen ◽  
Qi Wang

AbstractFor a class of non-affine nonlinear systems with state constraints, input constraint, uncertain parameters and unknown external disturbance, a back-stepping control scheme is proposed based on mean value theorem, nonlinear mapping and prescribed performance bounds (PPB). The non-affine system is first transformed into a time-varying system with a linear structure by using the mean value theorem, and the intervals of the time-varying uncertain parameters are calculated. The bounded time-varying parameters and external disturbance are estimated by adaptive algorithms with projection; the estimation error is compensated by employing nonlinear damping technology. To handle the state and input constraints, the nonlinear mapping technique (NMT), hyperbolic tangent function and Nussbaum function are employed. The prescribed performance control method improves the performance of the system. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control scheme.


2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881151
Author(s):  
Zhang Wenhui ◽  
Li Hongsheng ◽  
Ye Xiaoping ◽  
Huang Jiacai ◽  
Huo Mingying

It is difficult to obtain a precise mathematical model of free-floating space robot for the uncertain factors, such as current measurement technology and external disturbance. Hence, a suitable solution would be an adaptive robust control method based on neural network is proposed for free-floating space robot. The dynamic model of free-floating space robot is established; a computed torque controller based on exact model is designed, and the controller can guarantee the stability of the system. However, in practice, the mathematical model of the system cannot be accurately obtained. Therefore, a neural network controller is proposed to approximate the unknown model in the system, so that the controller avoids dependence on mathematical models. The adaptive learning laws of weights are designed to realize online real-time adjustment. The adaptive robust controller is designed to suppress the external disturbance and compensate the approximation error and improve the robustness and control precision of the system. The stability of closed-loop system is proved based on Lyapunov theory. Simulations tests verify the effectiveness of the proposed control method and are of great significance to free-floating space robot.


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