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multiple models Direct Adaptive Controller for a Stochastic Non-minimum Phase System

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Journal of Shanghai Jiaotong university(Science) 2010年第5期15卷 578-586页

作者：郑益慧王昕李少远姜建国 Center of Electrical and Electronic Technology Shanghai Jiaotong University Department of Automation Shanghai Jiaotong University Department of Electrical Engineering Shanghai Jiaotong University

For a stochastic non-minimum phase multivariable system,a multiple models direct adaptive controller is *** is composed of multiple fixed models with two adaptive *** fixed models are used to cover the region where the system parameters jump and improve the transient response,while another two adaptive models are used to guarantee the *** generalized minimum variance design method,it adopts the stochastic system estimation algorithm with optimal controller design method to identify the controller parameter ***,the global convergence is *** simulation proves the effectives of the controller proposed.

关键词： multiple models stochastic system non-minimum phase direct adaptive control multivariable system

Adaptive control of a class of nonlinear time-varying systems with multiple models

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Control Theory and Technology 2016年第4期14卷 323-334页

作者： Koshy GEORGE Karpagavalli SUBRAMANIAN PES Centre for Intelligent Systems Department of Telecommunication Engineering PES Institute of Technology Bangalore India PES Centre for Intelligent Systems Department of Electronics and Communication Engineering PES University Bangalore India

The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper. Since satisfactory transient performance is an important factor, multiple models are required as these parameters change abruptly in the parameter space. In this paper we consider both the multiple models with switching and tuning methodology as well as multiple models with second level adaptation for this class of systems. We demonstrate that the latter approach is better than the former.

关键词： Nonlinear time-varying systems adaptive control multiple models

Introducing robustness in model predictive control with multiple models and switching

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维普期刊数据库

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Control Theory and Technology 2014年第3期12卷 284-303页

作者： Sachin PRABHU Koshy GEORG Department of Telecommunication Engineering PES Institute of Technology Bangalore 560085 India PES Centre for Intelligent Systems Bangalore 560085 IndiaE

Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.

关键词： Receding horizon control Time-varying horizon multiple models Switching Tracking Robustness

Multivariable direct adaptive decoupling controller using multiple models and a case study

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Science in China(Series F) 2009年第7期52卷 1165-1176页

作者： WANG Xin YANG Hui ZHENG YiHui Center of Electrical & Electronic Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Electrical & Electronic Engineering East China Jiao Tong University Jiangxi 330013 China

In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive con- troller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured distur- bance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system.

关键词： multivariable multiple models decoupling non-minimum phase direct adaptive

Adaptive switching control of a class of nonlinear systems based on mixed multiple models

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Journal of Beijing Institute of Technology 2012年第4期21卷 504-509页

作者：曹奇敏张艳霞 School of Automation Beijing Institute of Technology School of Mathematics Beijing Institute of Technology

The transient behaviors of traditional adaptive control may be very poor in general. A practically feasible approach to improve the transient performances is the adoption of adaptive switc- hing control. For a typical class of nonlinear systems disturbed by random noises, mixed multiple models consisting of adaptive model and fixed models were considered to design the switching con- trol law. Under certain assumptions, the nonlinear system with the switching control law was proved rigorously to be stable and optimal A simulation example was provided to compare the performance of the switching control and the traditional adaptive control.

关键词： adaptive control nonlinear systems switching control multiple models mixed models

Control design approaches for nonlinear systems using multiple models

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控制理论与应用（英文版） 2007年第3期5卷 266-270页

作者： Junyong ZHAI Shumin FEI Feipeng DA Research Institute of Automation Southeast University Nanjing Jiangsu 210096 China

It is difficult to realize control for some complex nonlinear systems operated in different operating regions. Based on developing local models for different operating regions of the process, a novel algorithm using multiple models is proposed. It utilizes dynamic model bank to establish multiple local models, and their membership functions are defined according to respective regions. Then the nonlinear system is approximated to a weighted combination of the local models. The stability of the nonlinear system is proven. Finally, simulations are given to demonstrate the validity of the proposed method.

关键词： multiple models Operating region Lyapunov function

Intelligent control using multiple models based on on-line learning

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控制理论与应用（英文版） 2006年第4期4卷 397-401页

作者： Junyong ZHAI Shumin FEI Feipeng DA Research Institute of Automation Southeast University Nanjing Jiangsu 210096 China

In this paper we deal with the problem of plants with large parameter variations under different operating modes. A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical response performance. At the same time adaptive model bank is applied to establish models without prior system information. multiple models and corresponding controllers are automatically established on-line by a conventionally adaptive model and a re-initialized one. A best controller is chosen by the performance function at every instant. The closed-loop system＇s stability and asymptotical convergence of tracking error can be guaranteed. Simulation results have confirmed the validity of the proposed method.

关键词： multiple models Adaptive model bank Switch

A class of nonlinear discrete-time system adaptive control based on second level multiple models

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A class of nonlinear discrete-time system adaptive control b...

Nonlinear Adaptive Control Using multiple Identification models

第36届中国控制会议

作者： Yong Chen Xin Wang Zhenlei Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Center of Electrical and Electronic Technology Shanghai Jiao Tong University

ISBN: (纸本)9781538629185

Using multiple models to deal with transients for adaptive systems which is large parametric uncertainties was introduced in the 1990 *** common method is using switching ***,these methods has some potential *** this paper,a new multiple models scheme is proposed for a class strict-feedback nonlinear discrete-time ***,we use feedback linearization and backstepping method to develop adaptive indirect schemes with an observer-based identifier to ***,we design a controller based on the convex hull of parameter *** the number of necessary models is less than switching scheme,and can use the information of all identification ***,simulation have demonstrated that this method is effectively to a class of strict-feedback nonlinear discrete-time system.

关键词： convex hull multiple models backstepping nonlinear system strict-feedback

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Nonlinear Adaptive Control Using Multiple Identification Mod...