Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-d...Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.展开更多
Improving the energy efficiency of an electric vehicle(EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller(IESC) for a four-wheel in...Improving the energy efficiency of an electric vehicle(EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller(IESC) for a four-wheel independent-drive EV(4 WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control inputs.In the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator(LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor(SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral(PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally,double-lane change(DLC) simulations are conducted using Car Sim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by5.23% and 2.95% compared with the rule-based control strategy for high-and low-friction DLC maneuvers, respectively.展开更多
In order to research stability of four-wheel independent driving (4WID) electric vehicle, a torque allocation method based on the tire longitudinal forces optimization distribution is adopted. There are two layers in ...In order to research stability of four-wheel independent driving (4WID) electric vehicle, a torque allocation method based on the tire longitudinal forces optimization distribution is adopted. There are two layers in the controller, which includes the upper layer and the lower layer. In the upper layer, according to the demand of the longitudinal force, PID controller is set up to calculate the additional yaw moment created by yaw rate and side-slip angle. In the lower layer, the additional yaw moment is distributed properly to each wheel limited by several constraints. Carsim is used to build up the vehicle model and MATLAB/Simulink is used to build up the control model and both of them are used to simulate jointly. The result of simulation shows that a torque allocation method based on the tire longitudinal forces optimization distribution can ensure the stability of the vehicle.展开更多
文摘Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.51675281,and 51805081)the National Science and Technology Major Project of China(Grant No.2018ZX04024001)+2 种基金the Fundamental Research Funds for the Central Universities(Grant Nos.30918011101,and 309181B8809)and the Graduate Student Innovation Project of Jiangsu Province,China(Grant No.KYLX15_0341)the Chinese Scholarship Council for providing a scholarship(Grant No.201506840033)
文摘Improving the energy efficiency of an electric vehicle(EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller(IESC) for a four-wheel independent-drive EV(4 WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control inputs.In the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator(LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor(SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral(PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally,double-lane change(DLC) simulations are conducted using Car Sim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by5.23% and 2.95% compared with the rule-based control strategy for high-and low-friction DLC maneuvers, respectively.
文摘In order to research stability of four-wheel independent driving (4WID) electric vehicle, a torque allocation method based on the tire longitudinal forces optimization distribution is adopted. There are two layers in the controller, which includes the upper layer and the lower layer. In the upper layer, according to the demand of the longitudinal force, PID controller is set up to calculate the additional yaw moment created by yaw rate and side-slip angle. In the lower layer, the additional yaw moment is distributed properly to each wheel limited by several constraints. Carsim is used to build up the vehicle model and MATLAB/Simulink is used to build up the control model and both of them are used to simulate jointly. The result of simulation shows that a torque allocation method based on the tire longitudinal forces optimization distribution can ensure the stability of the vehicle.
