Disturbance rejection of dead-time processes using disturbance observer and model predictive control

This article mainly focuses on disturbance rejection of dead-time processes by integrating a modified disturbance observer (MDOB) with a model predictive controller (MPC). The effect caused by model mismatches is regarded as a part of the lumped disturbances. This means that the disturbances considered here include not only external disturbances, but also internal disturbances caused by model mismatches. Control structure of the proposed method includes two parts which can be designed separately. The MPC which acts as a prefilter, is employed to generate appropriate control actions such that a desired setpoint tracking response is achieved. The MDOB is employed to estimate the disturbances of the closed-loop system, and the estimation is used for feedforward compensation design to reject disturbances. Rigorous analysis of setpoint tracking and disturbance rejection properties of the closed-loop system are given in the presence of both model mismatches and external disturbances. The proposed scheme is applied to control the temperature of a simplified jacketed stirred tank heater (JSTH). Simulation results demonstrate that the proposed method possesses a better disturbance rejection performance than those of the MDOB-PI, MPC and PI methods in controlling such dead-time processes.

[1]  M. Chidambaram,et al.  Smith delay compensator for multivariable non-square systems with multiple time delays , 2006, Comput. Chem. Eng..

[2]  William C. Messner,et al.  A novel disturbance observer design for magnetic hard drive servo system with a rotary actuator , 1998 .

[3]  Peter J. Gawthrop,et al.  A nonlinear disturbance observer for robotic manipulators , 2000, IEEE Trans. Ind. Electron..

[4]  Carl J. Kempf,et al.  Disturbance observer and feedforward design for a high-speed direct-drive positioning table , 1999, IEEE Trans. Control. Syst. Technol..

[5]  I. M. Alatiqi,et al.  Constrained model predictive control for a pilot hydrotreating plant , 2004 .

[6]  Michael Mulholland,et al.  Adaptive Linear Dynamic Matrix Control applied to an integrating process , 2004, Comput. Chem. Eng..

[7]  B. Bequette,et al.  Process Control: Modeling, Design and Simulation , 2003 .

[8]  Kouhei Ohnishi,et al.  An Analysis of Parameter Variations of Disturbance Observer for Motion Control , 2007, IEEE Transactions on Industrial Electronics.

[9]  Masayoshi Tomizuka,et al.  High-speed and high-precision motion control with an optimal hybrid feedforward controller , 1997 .

[10]  Kouhei Ohnishi,et al.  Microprocessor-Controlled DC Motor for Load-Insensitive Position Servo System , 1985, IEEE Transactions on Industrial Electronics.

[11]  Zhang Guanghui,et al.  Control of the process with inverse response and dead-time based on disturbance observer , 2005, Proceedings of the 2005, American Control Conference, 2005..

[12]  Pedro Albertos,et al.  A new dead-time compensator to control stable and integrating processes with long dead-time , 2008, Autom..

[13]  M. Chidambaram,et al.  Set point weighted modified Smith predictor with PID filter controllers for non-minimum-phase (NMP) integrating processes , 2010 .

[14]  Wen-Hua Chen,et al.  Nonlinear Disturbance Observer-Enhanced Dynamic Inversion Control of Missiles , 2003 .

[15]  O Smith,et al.  CLOSER CONTROL OF LOOPS WITH DEAD TIME , 1957 .

[16]  Takamasa Hori,et al.  Control of redundant manipulators considering order of disturbance observer , 2000, IEEE Trans. Ind. Electron..

[17]  Yu Zhang,et al.  Decoupling Smith Predictor Design for Multivariable Systems with Multiple Time Delays , 2000 .

[18]  M. Tomizuka,et al.  A novel add-on compensator for cancellation of pivot nonlinearities in hard disk drives , 1998 .

[19]  Shihua Li,et al.  Disturbance observer based multi-variable control of ball mill grinding circuits , 2009 .

[20]  Wen-Hua Chen,et al.  Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach , 2005 .

[21]  C. R. Cutler,et al.  Dynamic matrix control¿A computer control algorithm , 1979 .

[22]  Ridvan Berber,et al.  Dynamic simulation and quadratic dynamic matrix control of an industrial low density polyethylene reactor , 1996 .

[23]  Qi Li,et al.  Constrained model predictive control in ball mill grinding process , 2008 .

[24]  Yuichi Matsumoto,et al.  Modeling of Force Sensing and Validation of Disturbance Observer for Force Control , 2007, IEEE Transactions on Industrial Electronics.

[25]  Marappagounder Ramasamy,et al.  Control of ball mill grinding circuit using model predictive control scheme , 2005 .

[26]  M. Bertoluzzo,et al.  Performance analysis of a high-bandwidth torque disturbance compensator , 2004, IEEE/ASME Transactions on Mechatronics.

[27]  Doug Cooper,et al.  A Practical Multiple Model Adaptive Strategy for Multivariable Model Predictive Control , 2003 .

[28]  Yoichi Hori,et al.  Robust servosystem design with two degrees of freedom and its application to novel motion control of robot manipulators , 1993, IEEE Trans. Ind. Electron..

[29]  Ibrahim Kaya,et al.  IMC based automatic tuning method for PID controllers in a Smith predictor configuration , 2004, Comput. Chem. Eng..