A Model-Free Stability-Based Adaptive Control Method for Unknown Nonlinear Systems

The design of an accurate model often appears as the most challenging tasks for control engineers especially focusing to the control of nonlinear systems with unknown parameters or effects to be identified in parallel. For this reason, development of model-free control methods is of increasing importance. The class of model-free control approaches is defined by the non-use of any knowledge about the underlying structure and/or related parameters of the dynamical system. Therefore the major criteria to evaluate model-free control performance are aspects regarding robustness against unknown inputs and disturbances to achieve a suitable tracking performance including ensuring stability. Consequently it is assumed that the system plant model to be controlled is unknown, only the inputs and outputs are used as measurements. In this contribution a modified model-free adaptive approach is given as the extended version of existing model-free adaptive control to improve the performance according to the tracking error at each sample time. Using modified model-free adaptive controller, the control goal can be achieved efficiently without an individual control design process for different kinds unknown nonlinear systems. The main contribution of this paper is to extend the modified model-free adaptive control method to unknown nonlinear multi-input multi-output (MIMO) systems. A numerical example is shown to demonstrate the successful application and performance of this method.

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A Model-Free Stability-Based Adaptive Control Method for Unknown Nonlinear Systems

Volume 1: Adaptive Control; Advanced Vehicle Propulsion Systems; Aerospace Systems; Autonomous Systems; Battery Modeling; Biochemical Systems; Control Over Networks; Control Systems Design; Cooperativ ◽

10.1115/dscc2012-movic2012-8679 ◽

2012 ◽

Cited By ~ 1

Author(s):

Xi Shen ◽

Dirk Söffker

Keyword(s):

Adaptive Control ◽

Nonlinear Systems ◽

Control Method ◽

Model Free

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Anti-noise model-free adaptive control and its application in the circulating fluidized bed boiler

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651820979376 ◽

2020 ◽

pp. 095965182097937

Author(s):

Na Dong ◽

Wenjin Lv ◽

Shuo Zhu ◽

Donghui Li

Keyword(s):

Adaptive Control ◽

Complete Convergence ◽

Circulating Fluidized Bed ◽

Control Method ◽

Noise Model ◽

Good Resistance ◽

Industrial Systems ◽

Noise Interference ◽

Model Free ◽

Tracking Differentiator

Model-free adaptive control has been developed greatly since it was proposed. Up to now, model-free adaptive control theory has become mature and tends to be an effective solution for complex unmodeled industrial systems. In practical industrial processes, most control systems are inevitably accompanied by noise that will result in indelible error and may further cause inaccurate feedback to the output. In order to solve this kind of problem with model-free technique, this article incorporates an improved tracking differentiator into model-free adaptive control. After that, the anti-noise model-free adaptive control method with complete convergence analysis is proposed. Meanwhile, numerical simulation proves that the improved control method can quickly track a given signal with good resistance to noise interference. Finally, the effectiveness and practicability of the proposed algorithm are verified by experiments through the control of drum water level of circulating fluidized.

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