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Design of robust control based on linear matrix inequality and a novel hybrid PSO search technique for autonomous underwater vehicle
Applied Ocean Research ( IF 4.3 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.apor.2020.102231
Elham Yazdani Bejarbaneh , Mojtaba Masoumnezhad , Danial Jahed Armaghani , Binh Thai Pham

Abstract The control of Autonomous Underwater Vehicle (AUV) is considered as a challenging problem, mainly due to the AUV's nonlinear and uncertain dynamics. In fact, the underwater vehicles require a robust control scheme in order to maneuver to any given point and track a moving target regardless of external disturbances. The main aim of this work consists of proposing two different designs of a robust control system for the nonlinear model of an AUV. The first controller is a PID that optimizes its gains using a novel hybrid PSO algorithm, combining Sine Cosine Algorithm (SCA) and Levy Flight (LF) distribution. The second one is a state feedback control that uses the Linear Matrix Inequality (LMI) approach to guarantee the closed-loop stability in the sense of the Lyapunov stability theory. The proposed control schemes are developed based on the Linear Parameter Varying (LPV) model to take into account the time-varying nature of AUV. The performance quality of these two controllers is evaluated based on the depth control of an AUV in the presence of parametric uncertainty. In order to assess the trajectory tracking, an attitude control system for the underwater vehicle is also developed using the proposed control methodologies. Finally, the obtained simulation results demonstrate that the proposed PSOSCALF-tuned PID not only shows higher robustness in the presence of parametric uncertainties and disturbances but also gives stunning time-domain performances compared to the LMI-based state feedback control.

中文翻译:

基于线性矩阵不等式的鲁棒控制设计和一种新型的自主水下航行器混合PSO搜索技术

摘要 自主水下航行器(AUV)的控制被认为是一个具有挑战性的问题,主要是由于AUV的非线性和不确定动力学。事实上,水下航行器需要一个强大的控制方案,以便在不受外部干扰的情况下机动到任何给定点并跟踪移动目标。这项工作的主要目的包括为 AUV 的非线性模型提出两种不同的鲁棒控制系统设计。第一个控制器是一个 PID,它使用一种新颖的混合 PSO 算法优化其增益,结合了正弦余弦算法 (SCA) 和 Levy Flight (LF) 分布。第二种是状态反馈控制,它使用线性矩阵不等式(LMI)方法来保证李雅普诺夫稳定性理论意义上的闭环稳定性。所提出的控制方案是基于线性参数变化 (LPV) 模型开发的,以考虑 AUV 的时变特性。在存在参数不确定性的情况下,基于 AUV 的深度控制来评估这两个控制器的性能质量。为了评估轨迹跟踪,还使用所提出的控制方法开发了水下航行器的姿态控制系统。最后,获得的仿真结果表明,与基于 LMI 的状态反馈控制相比,所提出的 PSOSCALF 调谐 PID 不仅在存在参数不确定性和干扰的情况下表现出更高的鲁棒性,而且还提供了惊人的时域性能。在存在参数不确定性的情况下,基于 AUV 的深度控制来评估这两个控制器的性能质量。为了评估轨迹跟踪,还使用所提出的控制方法开发了水下航行器的姿态控制系统。最后,获得的仿真结果表明,与基于 LMI 的状态反馈控制相比,所提出的 PSOSCALF 调谐 PID 不仅在存在参数不确定性和干扰的情况下表现出更高的鲁棒性,而且还提供了惊人的时域性能。在存在参数不确定性的情况下,基于 AUV 的深度控制来评估这两个控制器的性能质量。为了评估轨迹跟踪,还使用所提出的控制方法开发了水下航行器的姿态控制系统。最后,获得的仿真结果表明,与基于 LMI 的状态反馈控制相比,所提出的 PSOSCALF 调谐 PID 不仅在存在参数不确定性和干扰的情况下表现出更高的鲁棒性,而且还提供了惊人的时域性能。
更新日期:2020-08-01
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