Title :
Parallel Model Predictive Control of Nonlinear Time-delay Systems Based on Recurrent Neural Network
Author :
Wang, Dongqing ; Xu, Shuhua
Author_Institution :
Qingdao Univ., Qingdao
Abstract :
With regards to the nonlinear time-delay systems, d-step-ahead predictive model of neural network predictive control is adopted. This paper realizes the RTRL (real time recurrent learning) algorithm of parallel model of neural network predictive control for nonlinear time-delay systems for the first time. It describes advantages of RTRL algorithm of parallel model, compared with BP algorithm of series-parallel model. Simulation verified that RTRL algorithm of parallel model is better than BP algorithm of series-parallel model in performance and in disturbance rejection.
Keywords :
backpropagation; delay systems; neurocontrollers; nonlinear control systems; predictive control; recurrent neural nets; BP algorithm; disturbance rejection; nonlinear time-delay system; parallel model predictive control; real time recurrent learning; recurrent neural network; series-parallel model; Control system synthesis; Control systems; Educational institutions; Neural networks; Nonlinear control systems; Predictive control; Predictive models; Real time systems; Recurrent neural networks; Switches; RTRL (real time recurrent learning) algorithm; parallel model; predictive control; series-parallel model;
Conference_Titel :
Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-1685-1
Electronic_ISBN :
978-1-4244-1686-8
DOI :
10.1109/ICNSC.2008.4525302
