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Real-time trajectory tracking control of Stewart platform using fractional order fuzzy PID controller optimized by particle swarm algorithm
Industrial Robot ( IF 1.8 ) Pub Date : 2021-10-18 , DOI: 10.1108/ir-07-2021-0157
Zafer Bingul 1 , Oguzhan Karahan 2
Affiliation  

Purpose

The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and robustness against to different reference trajectories of a 6-DOF Stewart Platform (SP) in joint space.

Design/methodology/approach

For the optimal design of the proposed control approach, tuning of the controller parameters including membership functions and input-output scaling factors along with the fractional order rate of error and fractional order integral of control signal is tuned with off-line by using particle swarm optimization (PSO) algorithm. For achieving this off-line optimization in the simulation environment, very accurate dynamic model of SP which has more complicated dynamical characteristics is required. Therefore, the coupling dynamic model of multi-rigid-body system is developed by Lagrange-Euler approach. For completeness, the mathematical model of the actuators is established and integrated with the dynamic model of SP mechanical system to state electromechanical coupling dynamic model. To study the validness of the proposed FOFPID controller, using this accurate dynamic model of the SP, other published control approaches such as the PID control, FOPID control and fuzzy PID control are also optimized with PSO in simulation environment. To compare trajectory tracking performance and effectiveness of the tuned controllers, the real time validation trajectory tracking experiments are conducted using the experimental setup of the SP by applying the optimum parameters of the controllers. The credibility of the results obtained with the controllers tuned in simulation environment is examined using statistical analysis.

Findings

The experimental results clearly demonstrate that the proposed optimal FOFPID controller can improve the control performance and reduce reference trajectory tracking errors of the SP. Also, the proposed PSO optimized FOFPID control strategy outperforms other control schemes in terms of the different difficulty levels of the given trajectories.

Originality/value

To the best of the authors’ knowledge, such a motion controller incorporating the fractional order approach to the fuzzy is first time applied in trajectory tracking control of SP.



中文翻译:

粒子群算法优化分数阶模糊PID控制器的Stewart平台实时轨迹跟踪控制

目的

本文的目的是解决分数阶模糊 PID (FOFPID) 控制方法,以解决提高高精度跟踪性能和针对关节空间中 6 自由度 Stewart 平台 (SP) 的不同参考轨迹的鲁棒性的问题。

设计/方法/方法

对于所提出的控制方法的优化设计,通过使用粒子群优化离线调整控制器参数,包括隶属函数和输入输出比例因子,以及误差的分数阶率和控制信号的分数阶积分。 (PSO)算法。为了在仿真环境中实现这种离线优化,需要非常精确的具有更复杂动态特性的SP动态模型。因此,采用拉格朗日-欧拉方法建立了多刚体系统的耦合动力学模型。为了完整起见,建立了执行器的数学模型,并将其与SP机械系统的动力学模型相结合,以陈述机电耦合动力学模型。为了研究所提出的 FOFPID 控制器的有效性,使用这种精确的 SP 动态模型,其他已发布的控制方法,如 PID 控制、FOPID 控制和模糊 PID 控制也可以在仿真环境中使用 PSO 进行优化。为了比较调谐控制器的轨迹跟踪性能和有效性,通过应用控制器的最佳参数,使用 SP 的实验装置进行实时验证轨迹跟踪实验。使用统计分析检查在模拟环境中调整控制器获得的结果的可信度。通过应用控制器的最佳参数,使用 SP 的实验装置进行实时验证轨迹跟踪实验。使用统计分析检查在模拟环境中调整控制器获得的结果的可信度。通过应用控制器的最佳参数,使用 SP 的实验装置进行实时验证轨迹跟踪实验。使用统计分析检查在模拟环境中调整控制器获得的结果的可信度。

发现

实验结果清楚地表明,所提出的最优 FOFPID 控制器可以提高控制性能并减少 SP 的参考轨迹跟踪误差。此外,所提出的 PSO 优化 FOFPID 控制策略在给定轨迹的不同难度级别方面优于其他控制方案。

原创性/价值

据作者所知,这种将分数阶方法结合到模糊的运动控制器是第一次应用于 SP 的轨迹跟踪控制。

更新日期:2021-10-18
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