Characteristic model-based adaptive discrete-time sliding mode design for hypersonic vehicle attitude control

Inertia variations and torque disturbances, most often considered as two of the major uncertainties in servo systems, highly affect the control performance. This article presents a characteristic model–based adaptive controller in the presence of large-range load inertia variations. A discrete-time characteristic model of the servo system, which has more advantages in describing time-varying dynamics, is established. The parameters of characteristic model are identified by a recursive least squares algorithm. To restrain the identification error and load torque disturbances, a discrete extended state observer is newly designed for the discrete-time system. Both the convergence of discrete extended state observer and the stability of closed-loop system are verified by the Lyapunov theory. Finally, simulation and experimental results demonstrate that the proposed controller provides better performance than the fuzzy proportional integral controller in terms of adaptability and robustness.

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Chebyshev Neural Network-Based Adaptive Nonsingular Terminal Sliding Mode Control for Hypersonic Vehicles

Mathematical Problems in Engineering ◽

10.1155/2020/6830141 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Ruimin Zhang ◽

Qiaoyu Chen ◽

Haigang Guo

Keyword(s):

Sliding Mode Control ◽

Attitude Control ◽

Sliding Mode ◽

Hypersonic Vehicle ◽

Parameter Uncertainties ◽

External Disturbances ◽

Terminal Sliding Mode ◽

Mode Control ◽

Adaptive Law ◽

Nonsingular Terminal Sliding Mode

This paper presents an adaptive nonsingular terminal sliding mode control approach for the attitude control of a hypersonic vehicle with parameter uncertainties and external disturbances based on Chebyshev neural networks (CNNs). First, a new nonsingular terminal sliding surface is proposed for a general uncertain nonlinear system. Then, a nonsingular sliding mode control is designed to achieve finite-time tracking control. Furthermore, to relax the requirement for the upper bound of the lumped uncertainty including parameter uncertainties and external disturbances, a CNN is used to estimate the lumped uncertainty. The network weights are updated by the adaptive law derived from the Lyapunov theorem. Meanwhile, a low-pass filter-based modification is added into the adaptive law to achieve fast and low-frequency adaptation when using high-gain learning rates. Finally, the proposed approach is applied to the attitude control of the hypersonic vehicle and simulation results illustrate its effectiveness.

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Characteristic Model-Based Discrete Adaptive Sliding Mode Control for System with Time Delay

International Journal of Automation Technology ◽

10.20965/ijat.2016.p0282 ◽

2016 ◽

Vol 10 (2) ◽

pp. 282-287 ◽

Cited By ~ 1

Author(s):

Hua Zhong ◽

◽

Junhong Yu ◽

Hanzheng Ran ◽

Keyword(s):

Time Delay ◽

Sliding Mode Control ◽

Sliding Mode ◽

Delay System ◽

Adaptive Sliding Mode Control ◽

Time Delay System ◽

Characteristic Model ◽

Model Based ◽

Mode Control ◽

Discrete Sliding Mode Control

A novel characteristic model-based discrete sliding mode control (CMDSMC) for time delay system is presented in this paper. Firstly, to solve the challenge of establishing a accurate and simple model for time delay system, characteristic theory is applied to establish characteristic mode with time delay. Secondly, due to the uncertainties of time delay system, discrete sliding mode control based on characteristic model is proposed and stability analysis is done. At last, two illustrative examples taken from literatures are included to indicate the simplicity and superiority of the proposed method.

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