基于混合扩张状态观测器的农田平地机液压系统反步滑模控制研究OA北大核心CSTPCD
Backstepping Sliding Mode Control for Hydraulic System in Farmland Leveller Based on Hybrid Extended State Observer
为解决农田平地机液压系统在复杂地貌平地作业时控制精度低、抗干扰能力差等问题,设计了一种基于混合扩张状态观测器(HESO)的反步滑模控制器.其中,HESO基于输出反馈信号估计系统未知状态和总扰动,并在前馈通道中进行扰动补偿;基于快速趋近律设计的反步滑模控制器输出连续光滑的控制量,增强了系统鲁棒性,克服了系统非线性与参数不确定性问题;通过Lyapunov稳定性理论对所提出的观测器和控制器稳定性进行验证,得到误差一致有界稳定结论;通过AMESim和Matlab/Simulink联合仿真与田间试验对本文控制算法的有效性和优越性进行了验证.在两条地貌情况较为复杂波浪地中单次平地和地貌情况较为相似的两田块进行 3 次遍历试验表明,使用本文控制方法,平地后高程相较于平地前标高的平均绝对误差、最大绝对误差、绝对误差标准差分别为0.053、0.146、0.037 m和 0.02、0.041、0.011 m,较PID算法分别降低 36.35%、28.32%、31.37%和 62.6%、50%、51.83%.
In order to address the issues of low control accuracy and poor anti-interference capability of farmland leveller's hydraulic systems when operating on complex terrains,a backstepping sliding mode controller based on a hybrid extended state observer(HESO)was designed.The HESO estimated the system's unknown states and total disturbances based on output feedback signals and compensates for disturbances in the feedforward channel.The backstepping sliding mode controller,designed based on the fast reaching law,outputed continuous and smooth control quantities,enhancing the system's robustness and overcoming the issues of system nonlinearity and parameter uncertainty.The stability of the proposed observer and controller was proven by using Lyapunov stability theory,resulting in a conclusion of uniformly bounded stability of errors.The effectiveness and superiority of the control algorithm proposed were verified through joint simulations with AMESim and Matlab/Simulink,as well as field experiments.Single flattening experiments on two wavy terrains with relatively complex geomorphology and three traversal experiments on two similar terrains showed that using the proposed control method,the average absolute error,maximum absolute error,and standard deviation of the absolute error of the elevation after flattening compared with the pre-flattening elevation were 0.053 m,0.146 m,0.037 m,and 0.02 m,0.041 m,0.011 m,respectively.These values were reduced by 36.35%,28.32%,31.37%,and 62.6%,50%,51.83%respectively,compared with that of the PID algorithm.
魏新华;王庆壮;吉鑫;刘成良;汪岸哲
江苏大学农业工程学院,镇江 212013||智能农机装备理论与技术重点实验室,镇江 212013江苏大学农业工程学院,镇江 212013上海交通大学机械与动力工程学院,上海 200240
农业工程
农田平地机混合扩张状态观测器反步滑模控制联合仿真
farmland levellerhybrid extended state observerbackstepping sliding mode controljoint simulation
《农业机械学报》 2024 (007)
37-46 / 10
国家重点研发计划项目(2022ZD0115804)、江苏省农业自主创新项目(CX(22)2040)、江苏省重点研发计划项目(BE2021313)、江苏高校优势学科建设工程(四期)项目和常州市科技支撑计划(农业)项目(CE20212026)
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