Nonlinear Model-Predictive Control Based on Quasi-ARX Radial-Basis Function-Neural-Network

A nonlinear model-predictive control (NMPC) is demonstrated for nonlinear systems using an improved fuzzy switching law. The proposed moving average filter fuzzy switching law (MAFFSL) is composed of a quasi-ARX radial basis function neural network (RBFNN) prediction model and a fuzzy switching law. An adaptive controller is designed based on a NMPC. a MAFFSL is constructed based on the system switching criterion function which is better than the (ON/OFF) switching law and a RBFNN is used to replace the neural network (NN) in the quasi-ARX black box model which is understood in terms of parameters and is not an absolute black box model, in comparison with NN. The proposed controller performance is verified through numerical simulations to demonstrate the effectiveness of the proposed method.

[1]  Ching-Chih Tsai,et al.  Predictive Control Based on Recurrent Neural Network and Application to Plastic Injection Molding Processes , 2007, IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society.

[2]  Imam Sutrisno,et al.  Modified fuzzy adaptive controller applied to nonlinear systems modeled under quasi-ARX neural network , 2013, Artificial Life and Robotics.

[3]  Faa-Jeng Lin,et al.  Modified Elman neural network controller with improved particle swarm optimisation for linear synchronous motor drive , 2008 .

[4]  Kwang Y. Lee,et al.  Diagonal recurrent neural networks for dynamic systems control , 1995, IEEE Trans. Neural Networks.

[5]  S. S. Douglas,et al.  Adaptive neural network model based predictive control for air-fuel ratio of SI engines , 2006, Eng. Appl. Artif. Intell..

[6]  Kumpati S. Narendra,et al.  Nonlinear adaptive control using neural networks and multiple models , 2001, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[7]  Yu Cheng,et al.  Stabilizing switching control for nonlinear system based on quasi-ARX RBFN model , 2012 .

[8]  Lan Wang,et al.  Study on adaptive control of nonlinear dynamical systems based on quansi-ARX models , 2011 .

[9]  Yu Cheng,et al.  A Quasi-ARX Neural Network with Switching Mechanism to Adaptive Control of Nonlinear Systems , 2010 .

[10]  Guohe Huang,et al.  A neural network predictive control system for paper mill wastewater treatment , 2003 .

[11]  Kotaro Hirasawa,et al.  A Method for Applying Neural Networks to Control of Nonlinear Systems , 2004 .