Characteristic Model-based Adaptive Control Research Articles

Research on Characteristic Model-based Adaptive Control of High-speed Permanent Magnet Synchronous Motor With Time Delay

Research on Characteristic Model-based Adaptive Control of High-speed Permanent Magnet Synchronous Motor With Time Delay

Characteristic model-based adaptive control for cryogenic wind tunnels

With the increasing requirement of Reynolds number simulation in wind tunnel tests, the cryogenic wind tunnel is considered as a feasible method to realize high Reynolds number. Characteristic model-based adaptive controller design method is introduced to flow field control problem of the cryogenic wind tunnel. A class of nonlinear multi-input multi-output (MIMO) system is given for theoretical research that is related to flow field control of the cryogenic wind tunnel. The characteristic model in the form of second-order time-varying difference equations is provided to represent the system. A characteristic model-based adaptive controller is also designed correspondingly. The stability analysis of the closed loop system composed of the characteristic model or the exact discrete-time model and the proposed controller is investigated respectively. Numerical simulation is presented to illustrate the effectiveness of this control method. The modeling and control problem based on characteristic model method for a class of MIMO system are studied and first applied to the cryogenic wind tunnel control field.

Characteristic Model-Based Adaptive Control for a Class of MIMO Uncertain Nonaffine Nonlinear Systems Governed by Differential Equations

This paper addresses the difficulty of designing a controller for a class of multi-input multi-output uncertain nonaffine nonlinear systems governed by differential equations. We first derive the first-order characteristic model composed of a linear time-varying uncertain system for such nonaffine systems and then design an adaptive controller based on this first-order characteristic model for position tracking control. The designed controller exhibits a simple structure that can effectively avoid the controller singularity problem. The stability of the closed-loop system is analyzed using the Lyapunov method. The effectiveness of our proposed method is validated with a numerical example.

Characteristic Model-based Adaptive Control with Genetic Algorithm Estimators for Four-PMSM Synchronization System

For four-PMSM synchronization systems, the complex structure, nonlinearities and uncertainties make accurate modeling and precise control difficult to realize. This article proposes an easily realized adaptive control scheme for four-PMSM synchronization system. This control scheme combines novel characteristic modeling, genetic algorithm and terminal sliding mode control together. Firstly, the four-PMSM synchronization system is described by characteristic model, which significantly simplifies system’s dynamic model without losing its high-order characteristics. Secondly, a genetic algorithm estimator is newly designed to estimate the real-time value of parameters in characteristic model, which is the key issue in obtaining an accurate system model. Thirdly, an adaptive discrete-time terminal sliding mode controller is proposed based on the characteristic model to enhance system robustness. Also, this controller can eliminate chattering effect when system is reversing. Then, the stability of the closed-loop system is proved by Lyapunov stability theorem. Finally, simulation and experiment results verify the adaptiveness and robustness of the proposed control scheme.

Adaptive control of hypersonic vehicles based on characteristic models with fuzzy neural network estimators

Strong uncertainties and time-variations of hypersonic vehicles during the reentry phase pose huge challenges to their control system design. This paper addresses a novel adaptive output feedback control scheme based on characteristic models with fuzzy neural network estimators to guarantee the stable and accurate attitude tracking for the hypersonic vehicle, which is subject to unknown time-varying aerodynamics. By characteristic modeling, the time-varying uncertainties are integrated into several characteristic parameters to be estimated online, which inherit the time-variation property from the aerodynamics. And then the characteristic model-based adaptive control law is constructed, while the fuzzy neural network estimators are designed to estimate the time-varying characteristic parameters. The control performances including the property of estimators and the attitude tracking error are also analyzed. At last, the effectiveness of the proposed adaptive control scheme is illustrated by several representative simulations.

A simple characteristic model-based adaptive control for unstable processes with time delay

This paper proposed a novel control method for unstable process with time delay. Firstly, a simple proportion feedback inner loop is designed to maintain the stability of inner closed loop while the proportion value is selected with Routh criterion. Furthermore, by aiming at obtaining an accurate model, characteristic modelling theory is applied to establish characteristic model for unstable process with time delay. On the basis of characteristic model, keep tracking control law is presented and tracking theorem is also proved. Lastly, several illustrative examples taken from previous works are included to demonstrate the simplicity and superiority of the proposed method over those already published approaches.

A framework for stability analysis of high-order nonlinear systems based on the CMAC method

A framework for analyzing the stability of a class of high-order minimum-phase nonlinear systems of relative degree two based on the characteristic model-based adaptive control (CMAC) method is presented. In particular, concerning the tracking problem for such high-order nonlinear systems, by introducing a consistency condition for quantitatively describing modeling errors corresponding to a group of characteristic models together with a certain kind of CMAC laws, we prove closed-loop stability and show that such controllers can make output tracking error arbitrarily small. Furthermore, following this framework, with a specific characteristic model and a golden-section adaptive controller, detailed sufficient conditions to stabilize such groups of high-order nonlinear systems are presented and, at the same time, tracking performance is analyzed. Our results provide a new perspective for exploring the stability of some high-order nonlinear plants under CMAC, and lay certain theoretical foundations for practical applications of the CMAC method.