Title :
PI controller design for network control system based on minimum entropy control
Author :
Xinlan Guo ; Tao Li ; Hongxia Zhao
Author_Institution :
Mech. & Electr. Eng. Dept., Nanjing Commun. Inst. of Technol., Nanjing, China
Abstract :
This paper designs PI controller which is easy to operate in an actual random framework for NCS, for nonlinear ARMAX model is difficult to achieve in the practical application. Based on the nature of the network control system is a random system and PI controller design is easy to operate in an actual random framework for NCS, the iterative learning ideas to batch control system output probability density function, so that the output probability density function of the system with increasing batch tracking a given probability density function. In order to achieve the NCS system of tracking error probability density function control, this paper introduces the minimum entropy control algorithm.
Keywords :
PI control; adaptive control; autoregressive moving average processes; control system synthesis; iterative methods; learning systems; minimum entropy methods; networked control systems; nonlinear control systems; probability; random processes; NCS; PI controller design; batch tracking; control system output probability density function; iterative learning control; minimum entropy control algorithm; network control system; nonlinear ARMAX model; random system; tracking error probability density function control; Entropy; Robustness; NCS; PI controller; minimum entropy control;
Conference_Titel :
Service Operations and Logistics, and Informatics (SOLI), 2014 IEEE International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/SOLI.2014.6960752