Control of a DC motor using feedback linearization and gray wolf optimization algorithm
Apstrakt
The aim of this study is to investigate nonlinear DC motor behavior and to control velocity as output variable. The linear model is designed, but as it is experimentally verified that it does not describe the system well enough it is replaced by the nonlinear one. System's model has been obtained taking into account Coulomb and viscous friction in the firmly nonlinear environment. In the frame of the paper the dynamical analysis of the nonlinear feedback linearizing control is carried out. Furthermore, a metaheuristic optimization algorithm is set up for finding the coefficient of the proportional-integral feedback linearizing controller. For this purpose Gray wolf optimization technique is used. Moreover, after the introduction of the control law, analysis of the pole placement and stability of the system is establish. Optimized nonlinear control signal has been applied to the real object with simulated white noise and step signal as disturbances. Finally, for several desired output s...ignals, responses with and without disruption are compared to illustrate the approach proposed in the paper. Experimental results obtained on the given system are provided and they verify nonlinear control robustness.
Ključne reči:
stochastic disturbance robustness / nonlinear systems and control / nonlinear friction modeling / gray wolf optimization / Feedback linearization techniqueIzvor:
Advances in Mechanical Engineering, 2022, 14, 3Izdavač:
- Sage Publications Ltd, London
Finansiranje / projekti:
- MISSION4.0 - Deep Machine Learning and Swarm Intelligence-Based Optimization Algorithms for Control and Scheduling of Cyber-Physical Systems in Industry 4.0 (RS-ScienceFundRS-AI-6523109)
- Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200105 (Univerzitet u Beogradu, Mašinski fakultet) (RS-MESTD-inst-2020-200105)
- COST Action [CA18203]
- Integritet opreme pod pritiskom pri istovremenom delovanju zamarajućeg opterećenja i temperature (RS-MESTD-Technological Development (TD or TR)-35011)
- Dinamika hibridnih sistema složenih struktura. Mehanika materijala (RS-MESTD-Basic Research (BR or ON)-174001)
DOI: 10.1177/16878132221085324
ISSN: 1687-8132
WoS: 000770025700001
Scopus: 2-s2.0-85127025297
Kolekcije
Institucija/grupa
Mašinski fakultetTY - JOUR AU - Vesović, Mitra AU - Jovanović, Radiša AU - Trišović, Nataša PY - 2022 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3770 AB - The aim of this study is to investigate nonlinear DC motor behavior and to control velocity as output variable. The linear model is designed, but as it is experimentally verified that it does not describe the system well enough it is replaced by the nonlinear one. System's model has been obtained taking into account Coulomb and viscous friction in the firmly nonlinear environment. In the frame of the paper the dynamical analysis of the nonlinear feedback linearizing control is carried out. Furthermore, a metaheuristic optimization algorithm is set up for finding the coefficient of the proportional-integral feedback linearizing controller. For this purpose Gray wolf optimization technique is used. Moreover, after the introduction of the control law, analysis of the pole placement and stability of the system is establish. Optimized nonlinear control signal has been applied to the real object with simulated white noise and step signal as disturbances. Finally, for several desired output signals, responses with and without disruption are compared to illustrate the approach proposed in the paper. Experimental results obtained on the given system are provided and they verify nonlinear control robustness. PB - Sage Publications Ltd, London T2 - Advances in Mechanical Engineering T1 - Control of a DC motor using feedback linearization and gray wolf optimization algorithm IS - 3 VL - 14 DO - 10.1177/16878132221085324 ER -
@article{ author = "Vesović, Mitra and Jovanović, Radiša and Trišović, Nataša", year = "2022", abstract = "The aim of this study is to investigate nonlinear DC motor behavior and to control velocity as output variable. The linear model is designed, but as it is experimentally verified that it does not describe the system well enough it is replaced by the nonlinear one. System's model has been obtained taking into account Coulomb and viscous friction in the firmly nonlinear environment. In the frame of the paper the dynamical analysis of the nonlinear feedback linearizing control is carried out. Furthermore, a metaheuristic optimization algorithm is set up for finding the coefficient of the proportional-integral feedback linearizing controller. For this purpose Gray wolf optimization technique is used. Moreover, after the introduction of the control law, analysis of the pole placement and stability of the system is establish. Optimized nonlinear control signal has been applied to the real object with simulated white noise and step signal as disturbances. Finally, for several desired output signals, responses with and without disruption are compared to illustrate the approach proposed in the paper. Experimental results obtained on the given system are provided and they verify nonlinear control robustness.", publisher = "Sage Publications Ltd, London", journal = "Advances in Mechanical Engineering", title = "Control of a DC motor using feedback linearization and gray wolf optimization algorithm", number = "3", volume = "14", doi = "10.1177/16878132221085324" }
Vesović, M., Jovanović, R.,& Trišović, N.. (2022). Control of a DC motor using feedback linearization and gray wolf optimization algorithm. in Advances in Mechanical Engineering Sage Publications Ltd, London., 14(3). https://doi.org/10.1177/16878132221085324
Vesović M, Jovanović R, Trišović N. Control of a DC motor using feedback linearization and gray wolf optimization algorithm. in Advances in Mechanical Engineering. 2022;14(3). doi:10.1177/16878132221085324 .
Vesović, Mitra, Jovanović, Radiša, Trišović, Nataša, "Control of a DC motor using feedback linearization and gray wolf optimization algorithm" in Advances in Mechanical Engineering, 14, no. 3 (2022), https://doi.org/10.1177/16878132221085324 . .