scholarly journals Composite Learning Prescribed Performance Control of Nonlinear Systems

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Fang Zhu ◽  
Wei Xiang ◽  
Chunzhi Yang
Keyword(s):  
Tracking Error ◽  
Original System ◽  
Feedback System ◽  
Closed Loop System ◽  
Performance Control ◽  
Prescribed Performance ◽  
Persistent Excitation ◽  
Prescribed Performance Control ◽  
Control Scheme ◽  
The Stability

This paper investigates a composite learning prescribed performance control (PPC) scheme for uncertain strict-feedback system. Firstly, a prescribed performance boundary (PPB) condition is developed for the tracking error, and the original system is transformed into an equivalent one by using a transformation function. In order to ensure that the tracking error satisfies the PPB, a sufficient condition is given. Then, a control scheme of PPC combined with neural network (NN) and backstepping technique is proposed. However, the unknown functions cannot be guaranteed to estimate accurately by this method. To solve this problem, predictive errors are defined by applying online recorded date and instantaneous date. Furthermore, novel composite learning laws are proposed to update NN weights based on a partial persistent excitation (PE) condition. Subsequently, the stability of the closed-loop system is guaranteed and all signals are kept bounded by using composite learning PPC method. Finally, simulation results verify the effectiveness of the proposed methods.

scholarly journals Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Zhonghua Wu ◽  
Jingchao Lu ◽  
Jingping Shi ◽  
Yang Liu ◽  
Qing Zhou
Keyword(s):  
Neural Control ◽  
Switching Function ◽  
Parameter Uncertainties ◽  
Adaptive Neural Control ◽  
Remarkable Feature ◽  
Performance Control ◽  
Prescribed Performance ◽  
Prescribed Performance Control ◽  
Control Scheme ◽  
Smooth Switching

This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller.

scholarly journals Prescribed Performance Control for Two-axis Optronic Stabilized Platform

2018 ◽  
Vol 160 ◽  
pp. 01003
Author(s):  
Wang Yexing ◽  
Luo Changxin ◽  
Zhang Tao ◽  
Liu Yaning ◽  
Xiao Chuhan
Keyword(s):  
Closed Loop ◽  
Initial Error ◽  
Closed Loop System ◽  
Performance Function ◽  
Performance Control ◽  
Prescribed Performance ◽  
Initial Errors ◽  
Prescribed Performance Control ◽  
Unknown Disturbance ◽  
Stabilized Platform

Aiming at improving the tracking and stabilizing performance of two-axis optronic stabilized platform with Stribeck friction and uncertain velocity disturbance, a prescribed performance control strategy with unknown initial errors is designed. By designing a new performance function, the limit of traditional prescribed control that the initial error has to be known accurately is broken through. The strategy possesses strong robustness against unknown disturbance, and the state error is restrained to a predefined arbitrary small residual. It is guaranteed that the closed-loop system is uniformly ultimately bounded. The simulation results demonstrate the effectiveness of proposed strategy.

scholarly journals Fuzzy-approximation-based prescribed performance control of air-breathing hypersonic vehicles with input constraints

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987735
Author(s):  
Xingge Li ◽  
Gang Li ◽  
Yan Zhao ◽  
Xuchao Kang
Keyword(s):  
Control Method ◽  
Hypersonic Vehicle ◽  
Hypersonic Vehicles ◽  
Input Constraints ◽  
Air Breathing ◽  
Performance Control ◽  
Prescribed Performance ◽  
Fuzzy Approximation ◽  
Prescribed Performance Control ◽  
Control Scheme

In this article, aiming at the longitudinal dynamics model of air-breathing hypersonic vehicles, a fuzzy-approximation-based prescribed performance control scheme with input constraints is proposed. First, this article presents a novel prescribed performance function, which does not depend on the sign of initial tracking error. And combining prescribed performance control method with backstepping control, the control scheme can ensure that system can converge at a prescribed rate of convergence, overshoot, and steady-state error. In order to solve the problem that backstepping control method needs to be differentiated multiple times, fuzzy approximators are used to estimate the unknown functions, and norm estimation approach is used to simplify the computation of fuzzy approximator. Aiming at the problem of input saturation of actuator in subsystem of air-breathing hypersonic vehicle, the new auxiliary system is designed to ensure the stability and robustness of air-breathing hypersonic vehicle system under input constraints. Finally, the effectiveness of the proposed control strategy is verified by simulation analysis.

scholarly journals Design of decentralized adaptive control approach for large-scale nonlinear systems subjected to input delays under prescribed performance

2021 ◽  
Author(s):  
Yu-Qun Han
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Large Scale ◽  
Control Method ◽  
Performance Control ◽  
Prescribed Performance ◽  
Control Approach ◽  
Prescribed Performance Control ◽  
Control Scheme ◽  
Input Delays

Abstract For the first time, the issue of input delays and prescribed performance control is investigated in the same framework for large-scale nonlinear systems in this study, and a original adaptive decentralized control method is proposed take advantage of multi-dimensional Taylor network (MTN) method. Firstly, the problem of input delays is solved by introducing new variables, and a new form of coordinate transformation is introduced before controller design, which simplified the control system. Secondly, the problem of prescribed performance control is coped with by integrating the idea of prescribed performance into the Lyapunov functions of first step of backstepping of each subsystem. Thirdly, MTNs are employed to evaluate the combination of unknown functions, and then a decentralized MTN-based adaptive control scheme is developed by way of backstepping technology. The theoretical analysis indicates that the proposed control scheme can implement the expected tracking goals under the condition of meeting the prescribed performance control. Finally, one numerical example is given to show the validity and rationality of the proposed control method.

Stability Analysis of a Bilateral Teleoperating System

1993 ◽  
Vol 115 (3) ◽  
pp. 419-426 ◽  
Author(s):  
Y. Strassberg ◽  
A. A. Goldenberg ◽  
J. K. Mills
Keyword(s):  
Feedback Linearization ◽  
Closed Loop ◽  
Tracking Error ◽  
Degree Of Freedom ◽  
Closed Loop System ◽  
Control Scheme ◽  
Feedback Linearization Control ◽  
Small Gain ◽  
The Stability ◽  
Three Degree Of Freedom

In this paper the stability of a control scheme for bilateral master-slave teleoperation is investigated. Given the nominal models of the master and slave dynamics, and using an approximate feedback linearization control, based on the earlier work of Spong and Vidyasagar, 1987, a robust closed-loop system (position and force) can be obtained with a multiloop version of the small gain theorem. It is shown that stable bilateral teleoperating systems can be achieved under the assumption that the deviation of the models from the actual systems satisfies certain norm inequalities. We also show that, using the proposed scheme, the tracking error (position/velocity and force/torque) is bounded and it can be made arbitrarily small. The control scheme is illustrated using the simulation of a three-degree-of-freedom master-slave teleoperator (three-degree-of-freedom master and three-degree-of-freedom slave).

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