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The design of an IMC-PID controller based on MEOTF and its application to non-square processes with time delay†

Published online by Cambridge University Press:  04 September 2014

QIBING JIN ,
LITING CAO ,
KUN HE ,
KEWEN WANG  and
BEIYAN JIANG
QIBING JIN
Affiliation:
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China Email: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]
LITING CAO
Affiliation:
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China Email: [email protected]; [email protected]; [email protected]; [email protected]; [email protected] Beijing Union University, Beijing, China
KUN HE
Affiliation:
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China Email: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]
KEWEN WANG
Affiliation:
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China Email: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]
BEIYAN JIANG
Affiliation:
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China Email: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]
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Abstract

It is difficult to design a controller directly for non-square multi-variable systems with time delay. In the current paper, we propose a new design method for an Internal Model Control PID controller based on a modified effective open-loop transfer function (MEOTF) for non-square processes with time delay. The MEOTF method is used to decompose the complex non-square process into several equivalent independent single-input/single-output processes. Using the Taylor Particle Swarm Optimisation (Taylor-PSO) model reduction method, the MEOTF of the non-square process is approximated by a reduced order form. The reduced form of the MEOTF is then used to design the Internal Model Control PID controller, which is then used for the original non-square process. To improve the robust stability, a first-order filter is added in the feedback loop. Finally, we present simulation results showing the validity and reliability of this method. In particular, our method has a strong anti-interference characteristic and retains its good control performance in the presence of model perturbation and interference.

Type
Paper
Information
Mathematical Structures in Computer Science , Volume 24 , Special Issue 5: Mathematical Method in Intelligent Computing and Automation , October 2014 , e240511
Copyright
Copyright © Cambridge University Press 2014 

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Footnotes

†

This work was supported by 863 Project (2008AA042131) and 973 Project (2007CB714300).

References

Chen, P. Y., Ou, L. L., Gu, D. Y. and Zhang, W. D. (2009) Robust analytical scheme for linear non-square systems. 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, Edinburgh University Press 1890–1895.Google Scholar
Chen, P. Y., Ou, L. L., Sun, J. and Zhang, W. D. (2008) Modified internal model control and its application in non-square processes. Control and Decision 23 (5)581–584.Google Scholar
Davison, E. J. (1976) Multivariable tuning regulators: The feed forward and robust control of a general servo mechanism problem. IEEE Transactions on Automatic Control 20 (9)17–41.Google Scholar
Dijkstra, E. W. (1976) A Discipline of Programming, Prentice-Hall.Google Scholar
He, M. J., Cai, W. J., Wu, B. F. and He, M. (2005) Simple decentralized PID controller design method based on dynamic relative interaction analysis. Industrial and Engineering Chemistry Research 44 (8)8334–8344.Google Scholar
Huang, H. P., Jeng, J. C., Chiang, C. H. and Pan, W. (2003) A direct method for multi-loop PI/PID controller design. Journal of Process Control 13 (7)736–745.Google Scholar
Jin, Q. B., Guo, Y. and Liu, Z. Y. (2010) Modified internal model control and its application in non-square processes. International Conference on Measuring Technology and Mechatronics Automation 898–901.Google Scholar
Jin, Q. B., Liu, S. W., Quan, L. and Cao, L. T. (2011) Internal model control based on singular value decomposition and its application in non-square processes. Acta Automatica Sinica 37 (3)354–359.CrossRefGoogle Scholar
Kennedy, J. and Eberhart, R. C. (1995) Particle swarm optimization. Proceedings IEEE International Conference on Neural Networks 1942–1948.Google Scholar
Liu, H., Yuan, W. Y. and Jiang, D. Q. (2003) Matrix Theory and Application, Beijing: Chemical Industry Press 200–205.Google Scholar
Normey-Rico, J. E., Bordons, C. and Camacho, E. F. (1997) Improving the Robustness of Dead Time Compensating PI Controllers. Control Engineering Practice 5–6 801–810.CrossRefGoogle Scholar
Rao, A. S. and Chidambaram, M. (2006) Smith delay compensator for multivariable non-square systems with multiple time delays. Computer and Chemical Engineering 30 (8)1243–1255.CrossRefGoogle Scholar
Rivera, D. E., Morari, M. and Skogestad, S. (1986) Internal model control: 4. PID controller Design. Industrial and Engineering Chemistry Process Design and Development 25 (1)252–265.CrossRefGoogle Scholar
Roy, A. and Iqbal, K. (2005) PID controller tuning for the first-order-plus-dead-time process model via Hermite–Biehler theorem. ISA Transactions 363–378.CrossRefGoogle Scholar
Sarma, K. L. N. and Chidambaram, M. (2005) Centralized PI/PID controllers for non-square systems with RHP zeros. Journal of Indian Institute Science 85 (4)201–214.Google Scholar
Shi, Y. and Eberhart, R. C. (1998) A modified particle swarm optimizer. IEEE International Conference of Evolutionary Computation 69–73.Google Scholar
Tanttu, J. T. and Lieslehto, J. (1991) A comparative study of some multivariable PI controller tuning methods. Intelligent tuning and adaptive control 8 (39)357–362.Google Scholar
Treiber, H. (1984) Multivariable control of non-square systems. Industrial and Engineering Chemistry Process Design and Development 23 (4)854–857.Google Scholar
Vu, T. N. L. and Lee, M. (2010) Independent design of multi-loop PI/PID controllers for interacting multivariable processes. Acta Automatica Sinica 20 (9)922–933.Google Scholar
Xiong, Q. and Cai, W. J. (2006) Effective transfer function method for decentralized control system design of multi-input multi-output processes. Journal of Process Control 16 (7)773–784.Google Scholar
Xue, D. Y. (1994) Control System Optimal Reduction Technique and its Applications. Control and Decision 9 (6)420–425.Google Scholar
Yao, Y. J., Wang, J. and Pan, L. D. (2008) Decoupling internal model control for multi-variable non-square system with time delays. Journal of Chemical Industry and Engineering 59 (7)1737–1742.Google Scholar
Zhu, Z. X. (1996) Structural analysis and stability conditions of decentralized control systems. Process Design and Control 35 (7)736–745.Google Scholar