Control Parameters Tuning Method of Nonlinear Model Predictive Controller Based on Quantitatively Analyzing

Tomohiro Henmi

doi:10.20965/jrm.2016.p0695

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JRM Vol.28 No.5 pp. 695-701

doi: 10.20965/jrm.2016.p0695

(2016)

Paper:

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Control Parameters Tuning Method of Nonlinear Model Predictive Controller Based on Quantitatively Analyzing

Tomohiro Henmi

Department of Electro-Mechanical Engineering, National Institute of Technology, Kagawa College
355 Chokushicho, Takamatsu, Kagawa 761-8058, Japan

Received:

March 17, 2016

Accepted:

June 14, 2016

Published:

October 20, 2016

Keywords:

nonlinear model predictive control, analytical tuning method of control parameters, reference trajectory, tracking control

Abstract

The parameter-tuning method we discuss is for an Adaptive Nonlinear Model Predictive Controller (ANMPC). The MPC is optimization-based controller and decides control input to realize system output that tracks a reference trajectory through “optimal computation.” The reference trajectory is ideal trajectory of system output to converge on a desired value, i.e. controlled system performance depends on the reference trajectory. As a MPC controller which applies to the nonlinear systems, our group has already proposed an adaptive nonlinear MPC (ANMPC) for a tracking control problem of nonlinear two-link planar manipulators. This ANMPC uses a new reference trajectory having control parameters that must be tuned based on the desired controlled system’s responses and properties. To reduce troublesome parameter tuning, we propose new parameter-tuning method for ANMPC by a quantitative analysis of the relationship between a system’s behavior and ANMPC parameters. Numerically simulating the two-link nonlinear manipulator’s tracking control under various conditions demonstrates that proposed tuning method tunes the ANMPC effectively.

ANMPC controller

Cite this article as:

T. Henmi, “Control Parameters Tuning Method of Nonlinear Model Predictive Controller Based on Quantitatively Analyzing,” J. Robot. Mechatron., Vol.28 No.5, pp. 695-701, 2016.

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References

[1] J. K. Maciejowski, “Predictive Control with Constraints,” Prentice Hall, New Jersey, 2002.
[2] W. H. Kwon and A. E. Pearson, “On Feedback Stabilization of Time-Varying Discrete Linear Systems,” IEEE Trans. Autom. Control, Vol.23, pp. 479-481, 1978.
[3] V. H. L. Cheng, “A Direct Way to Stabilize Continuous-Time and Discrete-Time Linear Time-Varying Systems,” IEEE Trans. Autom. Control, Vol.24, pp. 641-643, 1979.
[4] C. C. Chen and L. Shaw, “On Receding Horizon Feedback Control,” Automatica, Vol.18, pp. 349-352, 1982.
[5] T. Henmi, T. Ohta, M. Deng, and A. Inoue, “Tracking Control of The Two-link Manipulator using Nonlinear Model Predictive Control,” Proc. of IEEE Int. Conf. on Networking, Sensing and Control, pp. 761-766, 2009.
[6] T. Henmi, M. Deng, and A. Inoue, “Adaptive Control of a Two-link Planar Manipulator using Nonlinear Model Predictive Control,” Proc. of 2010 IEEE Int. Conf. on Mechatronics and Automation, pp. 1868-1873, 2010.
[7] S. Jung and T. Wen, “Nonlinear Model Predictive Control for Swing-UP of a Rotary Inverted Pendulum,” Trans. of the ASME, Vol.126, pp. 666-673, 2004.
[8] D. Q. Mayne and H. Michalska, “Receding Horizon Control of Nonlinear System,” IEEE Trans. Autom. Control, Vol.35, pp. 814-824, 1990.
[9] T. Kobayashi and T. Tani, “Application of Cooperative Control to Petroleum Plants Using Fuzzy Supervisory Control and Model Predictive Multi-variable Control,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.5, No.6, pp. 333-337, 2001.
[10] T. Kayahara and T. Henmi, “Anti-windup compensator for nonlinear model predictive control,” Proc. of 2012 Int. Conf. on Advanced Mechatronic Systems, pp. 406-411, 2012.
[11] A. Matsushita and T. Henmi, “The Performance Validation of an Actuator Fault Detection of a Nonlinear Model Predictive Controller in using Approximate Differentiation,” Proc. of 5th Int. Symposium on Advanced Control of Industrial Processes, pp. 397-402, 2014.
[12] S. Watanabe and M. Harada, “Optimal Tracking Control of a Micro Ground Vehicle,” J. of Robotics and Mechatronics, Vol.27, No.6, pp. 653-659, 2015.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] J. K. Maciejowski, “Predictive Control with Constraints,” Prentice Hall, New Jersey, 2002.

[2] [2] W. H. Kwon and A. E. Pearson, “On Feedback Stabilization of Time-Varying Discrete Linear Systems,” IEEE Trans. Autom. Control, Vol.23, pp. 479-481, 1978.

[3] [3] V. H. L. Cheng, “A Direct Way to Stabilize Continuous-Time and Discrete-Time Linear Time-Varying Systems,” IEEE Trans. Autom. Control, Vol.24, pp. 641-643, 1979.

[4] [4] C. C. Chen and L. Shaw, “On Receding Horizon Feedback Control,” Automatica, Vol.18, pp. 349-352, 1982.

[5] [5] T. Henmi, T. Ohta, M. Deng, and A. Inoue, “Tracking Control of The Two-link Manipulator using Nonlinear Model Predictive Control,” Proc. of IEEE Int. Conf. on Networking, Sensing and Control, pp. 761-766, 2009.

[6] [6] T. Henmi, M. Deng, and A. Inoue, “Adaptive Control of a Two-link Planar Manipulator using Nonlinear Model Predictive Control,” Proc. of 2010 IEEE Int. Conf. on Mechatronics and Automation, pp. 1868-1873, 2010.

[7] [7] S. Jung and T. Wen, “Nonlinear Model Predictive Control for Swing-UP of a Rotary Inverted Pendulum,” Trans. of the ASME, Vol.126, pp. 666-673, 2004.

[8] [8] D. Q. Mayne and H. Michalska, “Receding Horizon Control of Nonlinear System,” IEEE Trans. Autom. Control, Vol.35, pp. 814-824, 1990.

[9] [9] T. Kobayashi and T. Tani, “Application of Cooperative Control to Petroleum Plants Using Fuzzy Supervisory Control and Model Predictive Multi-variable Control,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.5, No.6, pp. 333-337, 2001.

[10] [10] T. Kayahara and T. Henmi, “Anti-windup compensator for nonlinear model predictive control,” Proc. of 2012 Int. Conf. on Advanced Mechatronic Systems, pp. 406-411, 2012.

[11] [11] A. Matsushita and T. Henmi, “The Performance Validation of an Actuator Fault Detection of a Nonlinear Model Predictive Controller in using Approximate Differentiation,” Proc. of 5th Int. Symposium on Advanced Control of Industrial Processes, pp. 397-402, 2014.

[12] [12] S. Watanabe and M. Harada, “Optimal Tracking Control of a Micro Ground Vehicle,” J. of Robotics and Mechatronics, Vol.27, No.6, pp. 653-659, 2015.