A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is propcsed. The design is based on the universal approx...A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is propcsed. The design is based on the universal approximation capability of the Takagi - Seguno （T-S） fuzzy systems. Motivated by the principle of certainty equivalenteontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computafion of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.展开更多
The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconneetions is studied in this paper. Based on the principle of slid...The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconneetions is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized di- rect adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local informa- tion. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.展开更多
A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and ...A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.展开更多
为提高电力系统稳定器的动态性能及鲁棒性,提出一种基于协同控制理论的分散非线性电力系统稳定器(powersystem stabilizer based on synergetic control theory,SPSS)设计方法。首先针对同步发电机及励磁系统模型,根据协同理论,构造出...为提高电力系统稳定器的动态性能及鲁棒性,提出一种基于协同控制理论的分散非线性电力系统稳定器(powersystem stabilizer based on synergetic control theory,SPSS)设计方法。首先针对同步发电机及励磁系统模型,根据协同理论,构造出合适的流形,然后推导出SPSS的控制规律,进一步实用化后,得到一种基于协同控制理论的实用的SPSS,由于SPSS的所有输入信号均为本地易测量信号且与网络参数无关,从而能实现分散控制。最后,将所设计的SPSS用于3机6节点电力系统进行小扰动和大扰动仿真验证。仿真结果表明,与常规的相位补偿型的PSS相比,所提出的SPSS能够在较大的运行范围内向系统提供充分的阻尼,并对模型误差不敏感,具有很好的鲁棒性。展开更多
文摘A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is propcsed. The design is based on the universal approximation capability of the Takagi - Seguno （T-S） fuzzy systems. Motivated by the principle of certainty equivalenteontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computafion of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.
基金This project was supported by the National Natural Science Foundation (60074013 &10371106)the Natural ScienceFoundation of Education Bureau of Jiangsu (KK0310067) the Foundation of Information Science Subject Group of YangzhouUniversity (ISG030606)
文摘The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconneetions is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized di- rect adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local informa- tion. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.
基金Supported by National Natural Science Foundation of China （60674039, 60704004） and Innovation Fund for Outstanding Scholar of Henan Province （084200510009 ）
基金supported by the National Natural Science Fundation of China (6080402160974139+3 种基金61075117)the Fundamental Research Funds for the Central Universities (JY10000970001K5051070000272103676)
文摘A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.
文摘为提高电力系统稳定器的动态性能及鲁棒性,提出一种基于协同控制理论的分散非线性电力系统稳定器(powersystem stabilizer based on synergetic control theory,SPSS)设计方法。首先针对同步发电机及励磁系统模型,根据协同理论,构造出合适的流形,然后推导出SPSS的控制规律,进一步实用化后,得到一种基于协同控制理论的实用的SPSS,由于SPSS的所有输入信号均为本地易测量信号且与网络参数无关,从而能实现分散控制。最后,将所设计的SPSS用于3机6节点电力系统进行小扰动和大扰动仿真验证。仿真结果表明,与常规的相位补偿型的PSS相比,所提出的SPSS能够在较大的运行范围内向系统提供充分的阻尼,并对模型误差不敏感,具有很好的鲁棒性。
