无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制，提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响，建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动，建立油门机械腿和制动机械腿的运动学模型。在此基础上，分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器，并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入，分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中，为了减少控制抖振，滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰，避免了油门控制与制动控制之间的频繁切换，并实现了精确稳定的车速控制。

Nonlinear Fuzzy Sliding Mode Speed Control for Unmanned Driving Robotic Vehicle

The accurate and stable speed control, in different driving conditions for an unmanned driving robotic vehicle (UDRV) was estimated using the fuzzy sliding mode speed control method with a nonlinear disturbance observer (NDO). The vehicle longitudinal dynamics model was established by determining modeling uncertainties and external disturbances. The throttle mechanical leg kinematics model and the brake mechanical leg kinematics model of an unmanned driving robot (UDR) was established by analyzing the structure and movement of the throttle mechanical leg and the brake mechanical leg; the mechanical legs are used to manipulate the pedals of a vehicle with automatic transmission. The throttle/brake switching controller, throttle fuzzy sliding mode controller, and brake fuzzy sliding mode controller were designed, and the stability of the control system was proved based on this analysis. The throttle/brake switching controller was designed to achieve switching of control between the throttle and the brake by taking the derivative of vehicle target speed as the input. The throttle fuzzy sliding mode controller and the brake fuzzy sliding mode controller was designed to achieve control of the throttle and brake by recording actual vehicle speed and speed error as the input and the linear motor displacement of both the throttle mechanical leg and the brake mechanical leg as the output, respectively. Furthermore, to reduce control chattering, the sliding mode feedback control gain of the fuzzy sliding mode controller was adjusted online using the fuzzy logic algorithm. The NDO of the fuzzy sliding mode controller was designed to estimate and compensate for modeling uncertainties and external disturbances of the UDRV. The comparison results between the simulation and experiment demonstrate that the proposed method accurately estimates and compensates for the modeling uncertainties and external disturbances in the UDRV. In addition, frequent switching of control between the throttle and the brake is eliminated, and accurate and stable speed control is achieved.