A practical robust bounded control for permanent magnet linear motor with inequality constraints. (May 2022)

• Record Type: Journal Article
• Authors: Zhen, Shengchao; Hao, Junjian; Liu, Xiaoli; Wu, Qilin; Zhao, Han; Chen, Ye-Hwa
• Is Part Of: Control engineering practice. Volume 122(2022)
• Publication Date: 2022-05
• Subjects: Bounded control -- Inequality constraints -- Linear motor -- Robust control -- Uncertainty; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2022.105068
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: A novel practical robust bounded control for permanent magnet linear motor (PMLM) with inequality constraints is proposed, aiming to achieve a better performance in the trajectory tracking of PMLM. Firstly, a tangent function, which is a monotonic unbounded function in one period, is used to transform the constrained output state variables into unconstrained ones. After this transformation, the displacement of the PMLM is always kept within a range, regardless of various uncertainties. Also, the dynamic model is transformed into a new form. Secondly, based on the transformed dynamic model, a novel model-based and error-based control is put forward. Theoretical analysis is provided to demonstrate that the proposed control satisfies requirements of uniform boundedness as well as uniform ultimate boundedness. Thirdly, simulations and experiments are carried out, according to which, the proposed control shows an excellent performance, and the effectiveness of the novel control is demonstrated. Highlights: A special tangent function is constructed to transform the constrained displacement of PMLM into an unconstrained variable. This method ensures that the displacement of PMLM is always kept within a given range. The possibility of collisions is avoided. Based on the transformed dynamic model, a novel practical robust bounded control is proposed. The controller has the characteristics of simple structure, few adjustment parameters and simple adjustment process, which is very practical for engineers. Simulations and experiments are carried out, results show that the performance of PMLM under the novel control is better than other control methods compared and the position constraint problem in PMLM can be handled.