摘要
针对智能小车转向时跟踪精度差、响应时间较慢的问题,提出了一种基于机器视觉的智能小车转向系统的滑模控制方法。首先,以感知路面信息的智能小车为研究对象,对其转向系统进行了原理分析及数学建模。通过对永磁直流电机工作过程的分析,建立了电枢电压平衡方程和转矩平衡方程,得出了相应的传递函数,并采用实验方法对传递函数参数进行了辨识。其次,针对上述被控对象,设计了滑模控制器,并进行了稳定性证明。利用Matlab/Simulink仿真结果验证了滑模控制算法的有效性。理论结果和实验验证相结合表明,相较于PID(proportional integral differential)控制,滑模控制具有较好的跟踪精度和响应速度。在频率为20 Hz时,跟踪精度提高了89.3%。此外,滑模控制能够克服系统的不确定性,尤其是对于非线性系统,显示出良好的控制效果。
To solve the problem of poor tracking accuracy and slow response of intelligent car steering systems,a sliding mode control method of intelligent car steering system based on machine vision was proposed.Firstly,the intelligent car,which senses road information,was the research object.The principal analysis and mathematical modeling of the steering system were carried out.By analyzing the working process of the permanent-magnet direct current motor,the armature voltage balance equation and torque balance equation were listed,the transfer functions were obtained,and the transmission parameters were identified by experimental methods.Secondly,the sliding mode controller was designed for the above-mentioned controlled object,and its stability was proven.Matlab/Simulink simulation results verify the effectiveness of the sliding mode control algorithm.Finally,the combination of theoretical results and experimental verification shows that compared with PID(proportional integral differential)control,sliding mode control has better tracking accuracy and response speed at 20 Hz,the tracking accuracy is increased by 89.3%,and the system uncertainty can be overcome,especially for nonlinear systems.
作者
王启明
万璇
张振东
孙涛
吴光辉
WANG Qiming;WAN Xuan;ZHANG Zhendong;SUN Tao;WU Guanghui(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《上海理工大学学报》
CAS
CSCD
北大核心
2023年第6期645-652,共8页
Journal of University of Shanghai For Science and Technology
基金
国家自然科学基金资助项目(52175239)
上海市科委青年英才扬帆计划(19YF1434600)
上海市高校本科重点教改项目(AA4306001-2020-003)。
关键词
转向差速控制
智能小车
滑模控制
机器视觉
steering differential control
intelligent car
sliding mode control
machine vision
