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基于模糊逻辑控制的滑移转向底盘避障控制方法OA

Obstacle Avoidance Control Method of Electric Skid-Steering Chassis Based on Fuzzy Logic Control

中文摘要英文摘要

[目的/意义]目前,针对同时实现自动驾驶底盘轨迹跟踪和避障控制的研究还存在跟踪性能不足、执行器易抖动和系统复杂度过高的问题,提出了一种简洁算法同时实现底盘的轨迹跟踪和避障控制.[方法]利用模糊并行分布式补偿策略设计全局Takagi-Sugeno(T-S)模糊控制器,设计线性二次型调节器(Linear Quadratic Regu-lator,LQR)控制器作为每个局部系统的控制器,实现底盘的轨迹跟踪.在全局开环T-S模糊系统中设计一个新的LQRobs控制器用于实时动态轨迹规划,实现避障控制,并且设计了一个模糊控制器来动态调整增益矩阵.利用模糊融合控制器将两个控制器联合起来形成最终的控制输入.[结果和讨论]测试表明,在没有障碍物时,轨迹跟踪的横纵向跟踪误差分别为0.041 m和0.052 m.在有障碍物时,该方法可以实时生成参考轨迹实现避障控制.设计的模糊控制器可以根据工况实时调整LQRobs控制器的增益矩阵,与增益矩阵固定的LQRobs控制器相比,其跟踪误差降低了33.9%.[结论]该方法利用简洁的算法结构同时实现了底盘的轨迹跟踪和避障控制,为底盘的轨迹跟踪和避障控制研究提供了一种新的参考.

[Objective]Trajectory tracking and obstacle avoidance control are important components of autonomous driving chassis,but most current studies treat these two issues as two independent tasks,which will cause the chassis to stop trajectory tracking when fac-ing an obstacle,and then implement trajectory tracking again after completing obstacle avoidance.If the distance from the reference path after obstacle avoidance is too far,the subsequent tracking performance will be affected.There are also some studies on trajectory tracking and obstacle avoidance at the same time,but these studies are either not smooth enough and prone to chatter,or the control system is too complex.Therefore,a simple algorithm is proposed that can simultaneously implement trajectory tracking and obstacle avoidance control of the chassis in this research.[Methods]First,the kinematic model and kinematic error model of the chassis were designed.Since skid-steering was adopted,the kinematic model of the chassis was simplified to a two-wheel differential rotation robot model when designing the mathematical model.Secondly,the Takagi-Sugeno(T-S)fuzzy controller of the chassis was designed.Since the error model of the chassis was designed in advance,the T-S fuzzy model of the chassis could be designed.Based on the T-S model,a T-S fuzzy controller was designed using the parallel distributed compensation(PDC)algorithm.The linear quadratic regulator(LQR)controller was used as the state feedback controller of each fuzzy subsystem in the T-S fuzzy controller to form a global T-S fuzzy controller,which could realize the trajectory tracking function of the chassis when there were no obstacles.Secondly,the obsta-cle avoidance controller of the chassis was designed.A new LQRobs controller was designed in the global open-loop system to generate the reference trajectory to avoid obstacles.When the system detects an obstacle in the environment,the LQRobs controller starts work-ing,and generates a new path by judging the distance between the obstacle and the chassis,so that the chassis could avoid the obsta-cle.When the chassis bypassed the obstacle,the LQRobs controller stopped working.In order to better realize the obstacle avoidance function,a fuzzy controller was designed to adjust the gain matrices Q and R of the LQRobs controller in real time.Then,in order to re-alize trajectory tracking and obstacle avoidance controlled at the same time,a fuzzy fusion controller was designed to combine the two controllers to form the final chassis input,and the Mamdani fuzzy controller was selected to achieve it.Finally,the method was simu-lated and experimental tested.The simulation test used joint simulation test used MATLAB-Simulink and the experiments based on the self-developed electric multi-functional chassis were conducted.[Results and Discussions]The simulation results showed that when there were no obstacles,the control method could achieve stable trajectory tracking in the reference path composed of straight lines and curves.When there were obstacles,the vehicle could avoid them smoothly and quickly converge to the reference trajectory.When facing obstacles,the designed fuzzy logic LQRobs controller could adaptively change the controller gain matrix according to the vehi-cle's speed and the distance between the current obstacles to achieve rapid convergence.The experimental results showed that when there were no obstacles,the chassis could use the T-S fuzzy controller to achieve stable tracking of the reference trajectory,and the av-erage errors in the lateral and longitudinal directions of the entire tracking process were 0.041 and 0.052 m,respectively.When facing obstacles,the T-S fuzzy controller and the LQRobs controller realized the obstacle avoidance and tracking control of the chassis through joint control.The fuzzy controller was used to adjust the gain matrix of the LQRobs controller in real time,and the tracking er-ror was reduced by 33.9%compared with the controller with a fixed gain matrix.[Conclusions]The control system can simultaneously realize the trajectory tracking and obstacle avoidance control of the chassis,can quickly converge the tracking error to zero,and achieve smooth obstacle avoidance control.Although the control method proposed is simple and efficient,and the tracking and obsta-cle avoidance effects are significantly improved,the control method can only handle static obstacles on the reference path at present,and subsequent research will focus on dynamic obstacles.

李磊;佘小明;唐兴隆;张涛;董继伟;古愉川;周晓晖;冯伟;杨清慧

重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国重庆市农业科学院农业机械研究所,重庆 401329,中国||农业农村部西南山地智慧农业重点实验室(部省共建),重庆 401329,中国

信息技术与安全科学

滑移转向轨迹跟踪避障控制LQR模糊逻辑控制

skid steeringtrajectory trackingobstacle avoidance controlLQRfuzzy logic control

《智慧农业(中英文)》 2026 (1)

213-225,13

重庆市市级财政科技创新(cqaas2023sjczsy006,KYLX20240500075,KYLX20240500039)重庆市技术创新与应用发展专项面上项目(CSTB2023TIAD-GPX0037)重庆市科研机构绩效激励引导专项(cstc2022jxjl80008) Chongqing Municipal Fiscal Science and Technology Innovation(cqaas2023sjczsy006,KYLX20240500075,KYLX20240500039)Chongqing Municipal Technology Innovation and Application Development Special Project(CSTB2023TIAD-GPX0037)Chongqing Municipal Scientific Research Institutions Performance Incentive Guidance Special Project(cstc2022jxjl80008)

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