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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Particle Swarm Optimization for Acceleration Tracking Control of an Actuator System
verfasst von : Quoc-Dong Hoang, Bui Huu Nguyen, Luan N. T. Huynh
Erschienen in: Machine Learning and Mechanics Based Soft Computing Applications
Verlag: Springer Nature Singapore
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Abstract
In this study, a platform of a fluid-power actuator system with a combination of electro-hydraulic and pneumatic for acceleration tracking control is proposed. Furthermore, a control strategy is provided to obtain high-performance results in controlling the piston's motion. Here, the particle swarm optimization (PSO), a computational method, is appropriately utilized for selecting the parameters of the classical proportional integral derivative (PID) control. The tracking errors are eliminated without the challenge of the tuning process, and the control performance is further enhanced. In order to validate the effectiveness of the control strategy, the numerical simulation results are eventually given. The remarkable result of the paper is that the position tracking control is precisely guaranteed when applying only a traditional PID controller with optimized parameters by using the PSO algorithm.