自主地面车辆模型预测超扭滑模控制

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2019-09-01 DOI:10.2478/pomr-2019-0057
H. Esfahani, R. Szlapczynski
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引用次数: 13

摘要

摘要本文提出了一种新的鲁棒模型预测控制(MPC)算法,用于在存在时变外部扰动(包括风、波浪和洋流)以及动态不确定性的情况下自主水面车辆(ASV)的轨迹跟踪。为了实现鲁棒性,采用了基于滑模控制的MPC设计程序和超扭曲项。MPC算法由于其实现的简单性和快速的动态响应而被认为是一种有效的方法。所提出的混合控制器已在MATLAB/Simulink环境中实现。组合模型预测超扭滑模控制(MP-STSMC)算法的结果表明,该算法在瞬态响应、鲁棒性和稳态响应方面显著优于传统MPC算法,并且与超扭滑模控制器(STMMC)算法相比,具有有效的抖振衰减。
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Model Predictive Super-Twisting Sliding Mode Control for an Autonomous Surface Vehicle
Abstract This paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been known as an effective approach for the implementation simplicity and its fast dynamic response. The proposed hybrid controller has been implemented in MATLAB / Simulink environment. The results for the combined Model Predictive Super-Twisting Sliding Mode Control (MP-STSMC) algorithm have shown that it significantly outperforms conventional MPC algorithm in terms of the transient response, robustness and steady state response and presents an effective chattering attenuation in comparison with the Super-Twisting Sliding Mode Control (STSMC) algorithm.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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