Feedback control of unknown chaotic dynamical systems based on time-series data
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions（1999）
摘要
A feedback control method is developed for controlling an unknown chaotic system, where the design is accomplished using only a finite set of one-dimensional (1-D) time-series data generated by the unknown system. The approach consists of three steps: (1) using the available time-series data to estimate a delayed time constant and an embedding dimension that both can be used to reconstruct a state space model preserving the chaotic attractor of the unknown system; (2) based on the reconstructed model, a lower order polynomial system of the same dimension is identified as a platform for controller design; and (3) a design method using the lower order approximate model is devised for determining a simple nonlinear feedback controller that works for the originally unknown underlying chaotic system. Computer simulation results on the Duffing oscillator are shown to demonstrate the effectiveness of this new feedback-control methodology
更多查看译文
关键词
uncertain systems,state-space methods,chaos,duffing oscillator,delayed time constant estimation,control system synthesis,embedding dimension estimation,unknown system,design method,chaotic dynamical systems,time-series data,feedback control methodology,feedback,nonlinear control systems,chaotic attractor,controller design,nonlinear feedback controller,lower order polynomial system,lower order approximate model,stability,state space model,delay estimation,time series,indexing terms,polynomials,oscillations,feedback control,control systems,computer simulation,design methodology,time series data
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要