Model free control based on GIMC structure

Many control researches for complicated and uncertain system are model-dependent and therefore require some prior knowledge for the complex systems. To avoid this problem, a number of model-free controllers are proposed. However, it is difficult to determine the control performance as the controller is not designed according certain system model especially when there are uncertainties and/or nonlinear dynamics in the system. To get over this problem, the model free controller (MFC) based on generalized internal model control (GIMC) structure is proposed in this paper. The MFC is used to attenuate the disturbance or uncertainty, and the system performance is determined by the nominal model and the nominal model controller. The parameters of nominal-model controller can be easily changed for meeting the change of the desired requirements. Moreover, the robust controller in the original GIMC is disassembled and rearranged to make the proposed methods easier to use, and the proposed method makes the controller be more flexible and greatly improves the system performance. Finally, the experiment results show that the MFC can be used to control the nonlinear systems and get the expected performance. The statistical analysis of performance for servo and regulatory behaviors also shows that the proposed method can achieve a better control performance than just using model free controller.

[1]  Zhongwen Wang,et al.  Model Identification and Control Method Study on Electro-Hydraulic Pressure Servo System , 2009, 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC).

[2]  R. Hedjar Application of nonlinear rescaling method to model predictive control , 2010 .

[3]  Zhang Ren,et al.  A new controller architecture for high performance, robust, and fault-tolerant control , 2001, IEEE Trans. Autom. Control..

[4]  Zhuzhi Yuan,et al.  Model-free control of affine chaotic systems , 2005 .

[5]  Rini Akmeliawati,et al.  Intelligent robust control design of a precise positioning system , 2010 .

[6]  Andrew Taylor,et al.  Modeling and Control of a Plastic Film Manufacturing Web Process , 2011, IEEE Transactions on Industrial Informatics.

[7]  Antonella Ferrara,et al.  Robust Model Predictive Control With Integral Sliding Mode in Continuous-Time Sampled-Data Nonlinear Systems , 2011, IEEE Transactions on Automatic Control.

[8]  Manuel Adam Medina,et al.  Adaptive nonlinear control of induction motor , 2011 .

[9]  Kemin Zhou A New Approach to Robust and Fault Tolerant Control , 2005 .

[10]  A. VasickaninovÃ,et al.  Fuzzy Model-based Neural Network Predictive Control of a Heat Exchanger , 2010 .

[11]  George K. I. Mann,et al.  Model-free intelligent control of a 6-DOF Stewart-Gough based parallel manipulator , 2002, Proceedings of the International Conference on Control Applications.

[12]  Riccardo Marino,et al.  Robust adaptive observers for nonlinear systems with bounded disturbances , 2001, IEEE Trans. Autom. Control..

[13]  Hecker,et al.  Predictive control of a heat exchanger , 1996 .

[14]  C. Lucas,et al.  A fast model free intelligent controller based on fused emotions: A practical case implementation , 2008, 2008 16th Mediterranean Conference on Control and Automation.

[15]  V. Aksakalli,et al.  Control of Nonlinear Stochastic Systems: Model-Free Controllers versus Linear Quadratic Regulators , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[16]  Heikki N. Koivo Practical PID Control (by Visioli, A.; 2006) [Book review] , 2008, IEEE Transactions on Automatic Control.

[17]  Daniel U. Campos-Delgado,et al.  Reconfigurable fault-tolerant control using GIMC structure , 2003, IEEE Trans. Autom. Control..

[18]  Frank L. Lewis,et al.  A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems , 1997, Autom..

[19]  Stuart Bennett,et al.  A History of Control Engineering 1930-1955 , 1993 .

[20]  Zhuzhi Yuan,et al.  Adaptive high order differential feedback control for affine nonlinear system , 2008 .

[21]  Hou Zhongsheng,et al.  Convergence of MFAC based feedback-feedforward ILC systems , 2008, 2008 27th Chinese Control Conference.

[22]  Zengqiang Chen,et al.  Robustly Stable Control of Continuous-time Generalized Predictive Control Combined with QFT Based on GIMC Structure , 2007 .