Robust Performance for Complex Dynamical Systems Based on Cell Mapping and Data Driven
This paper presents cell mapping construction and the robustness performance analysis for a class of complex dynamical systems which consist of a nonlinear plant and a state-feedback controller connected in a closed loop.Firstly,according to the process characteristics,a improved controlled auto-regressive moving average(CARMA)model is proposed by K-means clustering algorithm of data driven technology.Based on this model,a quantum-behaved particle swarm optimization(QPSO)algorithm is derived to identify parameters and compared with the least square(LS)algorithm to illustrate it.Then,in order to analysis system performance,the class cell mappings are formed by dividing the state space into class cell space.Next,One step transfer vector is employed to analysis robust performance of controller based on cell mapping,which avoid exploring global robustness by each initial point.Finally,a simulation example is given to demonstrate the effectiveness of the proposed approach.
Particle swarm cell mapping pattern recognition robust performance
Xu Zhengguang Guo Lingli Wang Mushu
School of Automation and Electrical Engineering,University of Science &Technology Beijing,Beijing 100083
国内会议
厦门
英文
335-339
2017-11-17（万方平台首次上网日期，不代表论文的发表时间）