A novel control approach: Combination of Self-tuning PID and PSO-Based ESO

Yanchun Chang; Feng Pan; Junyi Shu; Weixing Li; Qi Gao

doi:10.1007/978-3-319-20472-7_21

A novel control approach: Combination of Self-tuning PID and PSO-Based ESO

Yanchun Chang, Feng Pan, Junyi Shu, Weixing Li, Qi Gao^*

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This study focuses on the steady speed control of brushless DC motor with load torque disturbance from the cam and spring mechanism. Due to the nonlinearity and complexity of the load torque, the control system proposed in this paper is divided into the inner-loop compensator, which is to feed-forward compensate the disturbance, and the outer-loop controller. The inner-loop compensator uses a nonlinear extended state observer (ESO) to compensate the actual system as a nominal model, and the outer-loop pole assignment self-tuning PID controller is used to stabilize the nonlinear nominal model. Since a set of suitable nonlinear ESO parameters are difficult to get normally, particle swarm optimization (PSO) is employed to optimize the observer. The simulation results with high precision verify the effectiveness of the proposed control system.

Original language	English
Title of host publication	Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings
Editors	Ying Tan, Fernando Buarque, Andries Engelbrecht, Alexander Gelbukh, Swagatam Das, Yuhui Shi
Publisher	Springer Verlag
Pages	189-199
Number of pages	11
ISBN (Print)	9783319204710
DOIs	https://doi.org/10.1007/978-3-319-20472-7_21
Publication status	Published - 2015
Event	6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015 - Beijing, China Duration: 25 Jun 2015 → 28 Jun 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9141
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015
Country/Territory	China
City	Beijing
Period	25/06/15 → 28/06/15

Keywords

Brushless DC motor
Nonlinear extended state observer
Particle swarm optimization
Self-tuning PID

Access to Document

10.1007/978-3-319-20472-7_21

Cite this

Chang, Y., Pan, F., Shu, J., Li, W., & Gao, Q. (2015). A novel control approach: Combination of Self-tuning PID and PSO-Based ESO. In Y. Tan, F. Buarque, A. Engelbrecht, A. Gelbukh, S. Das, & Y. Shi (Eds.), Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings (pp. 189-199). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9141). Springer Verlag. https://doi.org/10.1007/978-3-319-20472-7_21

Chang, Yanchun ; Pan, Feng ; Shu, Junyi et al. / A novel control approach : Combination of Self-tuning PID and PSO-Based ESO. Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings. editor / Ying Tan ; Fernando Buarque ; Andries Engelbrecht ; Alexander Gelbukh ; Swagatam Das ; Yuhui Shi. Springer Verlag, 2015. pp. 189-199 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A novel control approach: Combination of Self-tuning PID and PSO-Based ESO",

abstract = "This study focuses on the steady speed control of brushless DC motor with load torque disturbance from the cam and spring mechanism. Due to the nonlinearity and complexity of the load torque, the control system proposed in this paper is divided into the inner-loop compensator, which is to feed-forward compensate the disturbance, and the outer-loop controller. The inner-loop compensator uses a nonlinear extended state observer (ESO) to compensate the actual system as a nominal model, and the outer-loop pole assignment self-tuning PID controller is used to stabilize the nonlinear nominal model. Since a set of suitable nonlinear ESO parameters are difficult to get normally, particle swarm optimization (PSO) is employed to optimize the observer. The simulation results with high precision verify the effectiveness of the proposed control system.",

keywords = "Brushless DC motor, Nonlinear extended state observer, Particle swarm optimization, Self-tuning PID",

author = "Yanchun Chang and Feng Pan and Junyi Shu and Weixing Li and Qi Gao",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015 ; Conference date: 25-06-2015 Through 28-06-2015",

year = "2015",

doi = "10.1007/978-3-319-20472-7_21",

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editor = "Ying Tan and Fernando Buarque and Andries Engelbrecht and Alexander Gelbukh and Swagatam Das and Yuhui Shi",

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Chang, Y, Pan, F, Shu, J, Li, W & Gao, Q 2015, A novel control approach: Combination of Self-tuning PID and PSO-Based ESO. in Y Tan, F Buarque, A Engelbrecht, A Gelbukh, S Das & Y Shi (eds), Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9141, Springer Verlag, pp. 189-199, 6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015, Beijing, China, 25/06/15. https://doi.org/10.1007/978-3-319-20472-7_21

A novel control approach: Combination of Self-tuning PID and PSO-Based ESO. / Chang, Yanchun; Pan, Feng; Shu, Junyi et al.
Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings. ed. / Ying Tan; Fernando Buarque; Andries Engelbrecht; Alexander Gelbukh; Swagatam Das; Yuhui Shi. Springer Verlag, 2015. p. 189-199 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9141).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T2 - 6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

AU - Chang, Yanchun

AU - Pan, Feng

AU - Shu, Junyi

AU - Li, Weixing

AU - Gao, Qi

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - This study focuses on the steady speed control of brushless DC motor with load torque disturbance from the cam and spring mechanism. Due to the nonlinearity and complexity of the load torque, the control system proposed in this paper is divided into the inner-loop compensator, which is to feed-forward compensate the disturbance, and the outer-loop controller. The inner-loop compensator uses a nonlinear extended state observer (ESO) to compensate the actual system as a nominal model, and the outer-loop pole assignment self-tuning PID controller is used to stabilize the nonlinear nominal model. Since a set of suitable nonlinear ESO parameters are difficult to get normally, particle swarm optimization (PSO) is employed to optimize the observer. The simulation results with high precision verify the effectiveness of the proposed control system.

AB - This study focuses on the steady speed control of brushless DC motor with load torque disturbance from the cam and spring mechanism. Due to the nonlinearity and complexity of the load torque, the control system proposed in this paper is divided into the inner-loop compensator, which is to feed-forward compensate the disturbance, and the outer-loop controller. The inner-loop compensator uses a nonlinear extended state observer (ESO) to compensate the actual system as a nominal model, and the outer-loop pole assignment self-tuning PID controller is used to stabilize the nonlinear nominal model. Since a set of suitable nonlinear ESO parameters are difficult to get normally, particle swarm optimization (PSO) is employed to optimize the observer. The simulation results with high precision verify the effectiveness of the proposed control system.

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SN - 9783319204710

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings

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A2 - Buarque, Fernando

A2 - Engelbrecht, Andries

A2 - Gelbukh, Alexander

A2 - Das, Swagatam

A2 - Shi, Yuhui

PB - Springer Verlag

Y2 - 25 June 2015 through 28 June 2015

ER -

Chang Y, Pan F, Shu J, Li W, Gao Q. A novel control approach: Combination of Self-tuning PID and PSO-Based ESO. In Tan Y, Buarque F, Engelbrecht A, Gelbukh A, Das S, Shi Y, editors, Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings. Springer Verlag. 2015. p. 189-199. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-20472-7_21

A novel control approach: Combination of Self-tuning PID and PSO-Based ESO

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