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Wu Q, Lin F, Zhao H, Zhang C, Sun H. A deterministic robust control with parameter optimization for uncertain two-wheel driven mobile robot. ISA TRANSACTIONS 2024; 146:29-41. [PMID: 38104021 DOI: 10.1016/j.isatra.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 11/08/2023] [Accepted: 12/08/2023] [Indexed: 12/19/2023]
Abstract
The uncertainty in mobile robot greatly affects control accuracy. This makes it difficult to apply to more rigorous high-precision engineering fields. Therefore, the fuzzy set theory is introduced to describe the uncertainty. Based on that, the fuzzy mobile robot system is established. The virtual speed controller using backstepping method is designed. Then, a robust control method is proposed to guarantee the uniform boundedness and uniform ultimate boundedness of the controlled system. Furthermore, the balance optimization problem of the performance and cost of the controlled system is explored. By minimizing the performance index containing fuzzy numbers, the optimal control parameter is obtained. Compared with the linear quadratic regulator algorithm, which is the representative optimal robust controller, the proposed control method and optimization strategy based on fuzzy set theory are verified to be effective. The control accuracy is further improved.
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Affiliation(s)
- Qilin Wu
- School of Advanced Manufacturing Engineering, Hefei University, Hefei 230601, China.
| | - Fei Lin
- School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China; AnHui Key Laboratory of Digital Design and Manufacturing, Hefei University of Technology, Hefei 230009, China
| | - Han Zhao
- School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China; AnHui Key Laboratory of Digital Design and Manufacturing, Hefei University of Technology, Hefei 230009, China
| | - Chunpeng Zhang
- School of Advanced Manufacturing Engineering, Hefei University, Hefei 230601, China
| | - Hao Sun
- School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China; AnHui Key Laboratory of Digital Design and Manufacturing, Hefei University of Technology, Hefei 230009, China.
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Zhao K, Liu W, Zhou R, Dai W, Wu S, Qiu P, Yin Y, Jia N, Yi J, Huang G. Model-free fast integral terminal sliding-mode control method based on improved fast terminal sliding-mode observer for PMSM with unknown disturbances. ISA TRANSACTIONS 2023:S0019-0578(23)00429-9. [PMID: 37798205 DOI: 10.1016/j.isatra.2023.09.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 07/03/2023] [Accepted: 09/22/2023] [Indexed: 10/07/2023]
Abstract
This paper presents a novel model-free fast integral terminal sliding-mode control (MFFITSMC) method based on an improved fast terminal sliding-mode observer (IFTSMO) for permanent magnet synchronous motor (PMSM) drive system, which can effectively eliminate the impact caused by unknown disturbances, such as parameter perturbations and external disturbances. The PMSM mathematical model with unknown disturbances is first established, and the ultra-local model (ULM) of the PMSM speed loop is constructed. Next, the model-free fast integral terminal sliding-mode controller is designed in the speed loop based on the ULM. Then, the IFTSMO is designed to precisely estimate the unknown term of the ULM, and the estimated unknown term is fed back to the MFFITSMC controller to perform compensation for unknown disturbances in real time. Finally, compared with the proportional-integral (PI) control method and the conventional model-free sliding-mode control (MFSMC) method, the results of simulations and experiments demonstrate that the presented MFFITSMC method reduces the dependence on the precise model and achieves the purpose of anti-disturbance control of the PMSM drive system.
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Affiliation(s)
- Kaihui Zhao
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China; School of Engineering, Tokyo University of Technology, Hachioji 192-0982, Japan.
| | - Wenchang Liu
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Ruirui Zhou
- School of Traffic and Transportation Engineering, Central South University, Changsha 410073, China.
| | - Wangke Dai
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Sicheng Wu
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Pengqi Qiu
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Yang Yin
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Ning Jia
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Jinwu Yi
- College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
| | - Gang Huang
- College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China.
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