Nonliear Model Predictive Control of Ball-Plate System based on Gaussian Particle Swarm Optimization

被引：0

作者：

Fan, Jianchao ^{[1
]}

Han, Min ^{[1
]}

机构：

[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian, Peoples R China

来源：

2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2012年

关键词：

nonliear model predictive control; Gaussian particle swarm optimization; Ball-plate system; RECURRENT NEURAL-NETWORK; NONLINEAR-SYSTEMS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a new nonlinear model predictive control (NMPC) strategy based on the Gaussian particle swarm optimization (GPSO). Through the Taylor expansion, NMPC transform to a quadratic programming problem with unknown parameters. Hence, for the global convergence character and higher optimization accuracy, GPSO is employed to dynamically perform nonlinear constraint optimization. Finally, the proposed control strategy is applied to Ball-Plate system to verify the effectiveness.

引用

页数：6

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