This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is int...This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback system.However,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied directly.To address this problem,an augmented system and an augmented performance index function are proposed firstly.Thus,the general nonlinear system is transformed into an affine nonlinear system.The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically.It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function.Moreover,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function online.The stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals.Finally,the effectiveness of the developed optimal parallel control method is verified in two cases.展开更多
针对空间狭小拥挤、地面不平的特殊装配环境,设计了一种5自由度全方位移动装配机器人.该机器人主要由基于4组并联布置的MY(mutual Yo Yo)轮的全方位移动平台和具有2自由度的并联举升机构组成.首先,针对该机器人的全方位运动和并联举升...针对空间狭小拥挤、地面不平的特殊装配环境,设计了一种5自由度全方位移动装配机器人.该机器人主要由基于4组并联布置的MY(mutual Yo Yo)轮的全方位移动平台和具有2自由度的并联举升机构组成.首先,针对该机器人的全方位运动和并联举升机构的2自由度结构特点,建立了机器人的整体运动学模型,并基于该模型对机器人进行了圆形曲线轨迹仿真.然后,设计双曲线滤波PD(proportional derivative)控制器对机器人的轨迹进行跟踪并分析其轨迹跟踪误差.该控制器能控制平均误差在5 mm左右,且误差随跟踪时间减小而减小.最后,通过实验结果验证了该运动学模型和仿真结果的正确性,且该控制器能迅速并精确地实现其轨迹跟踪,从而进一步验证了该全方位移动装配机器人的优越性.展开更多
The single-shaft parallel hybrid powertrain with the automatic mechanical transmission(AMT)is an efficient hybrid driving system in the hybrid electric bus(HEB),while the electromechanical coupling driving control bec...The single-shaft parallel hybrid powertrain with the automatic mechanical transmission(AMT)is an efficient hybrid driving system in the hybrid electric bus(HEB),while the electromechanical coupling driving control becomes a complicated question to find a transient optimal control method to distribute the power between the engine and the electric machine(EM).This paper proposes an innovative control method to deal with the complicated transient coupling driving process of the electromechanical coupling driving system,considering the accelerating condition and the cruising condition mostly in the city driving cycle of HEB.The EM might be operated at driving mode or generating mode to assist the diesel engine to work in its high-efficiency area.Therefore,the adaptive torque tracking controller has been brought forward to ensure that the EM implements the demand torque as well as compensate the torque fluctuation of diesel engine.The d?q axis mathematical model and back stepping method are employed to deduce the adaptive controller and its adaptive laws.Simulation results demonstrate that the proposed control scheme can make the output torque of two power sources respond rapidly to the demand torque from the powertrain in the given driving condition.The proposed method could be adopted in the real control of HEB to improve the efficiency of the hybrid driving system.展开更多
In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based ...In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre- view back propagation （BP） neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po- sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.展开更多
基金supported in part by the National Key Reseanch and Development Program of China(2018AAA0101502,2018YFB1702300)in part by the National Natural Science Foundation of China(61722312,61533019,U1811463,61533017)in part by the Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles。
文摘This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback system.However,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied directly.To address this problem,an augmented system and an augmented performance index function are proposed firstly.Thus,the general nonlinear system is transformed into an affine nonlinear system.The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically.It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function.Moreover,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function online.The stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals.Finally,the effectiveness of the developed optimal parallel control method is verified in two cases.
文摘针对空间狭小拥挤、地面不平的特殊装配环境,设计了一种5自由度全方位移动装配机器人.该机器人主要由基于4组并联布置的MY(mutual Yo Yo)轮的全方位移动平台和具有2自由度的并联举升机构组成.首先,针对该机器人的全方位运动和并联举升机构的2自由度结构特点,建立了机器人的整体运动学模型,并基于该模型对机器人进行了圆形曲线轨迹仿真.然后,设计双曲线滤波PD(proportional derivative)控制器对机器人的轨迹进行跟踪并分析其轨迹跟踪误差.该控制器能控制平均误差在5 mm左右,且误差随跟踪时间减小而减小.最后,通过实验结果验证了该运动学模型和仿真结果的正确性,且该控制器能迅速并精确地实现其轨迹跟踪,从而进一步验证了该全方位移动装配机器人的优越性.
基金supported by the National Natural Science Foundation of China(Grant No.51275557)the National Science-technology Support Plan Projects of China(Grant No.2013BAG14B01)
文摘The single-shaft parallel hybrid powertrain with the automatic mechanical transmission(AMT)is an efficient hybrid driving system in the hybrid electric bus(HEB),while the electromechanical coupling driving control becomes a complicated question to find a transient optimal control method to distribute the power between the engine and the electric machine(EM).This paper proposes an innovative control method to deal with the complicated transient coupling driving process of the electromechanical coupling driving system,considering the accelerating condition and the cruising condition mostly in the city driving cycle of HEB.The EM might be operated at driving mode or generating mode to assist the diesel engine to work in its high-efficiency area.Therefore,the adaptive torque tracking controller has been brought forward to ensure that the EM implements the demand torque as well as compensate the torque fluctuation of diesel engine.The d?q axis mathematical model and back stepping method are employed to deduce the adaptive controller and its adaptive laws.Simulation results demonstrate that the proposed control scheme can make the output torque of two power sources respond rapidly to the demand torque from the powertrain in the given driving condition.The proposed method could be adopted in the real control of HEB to improve the efficiency of the hybrid driving system.
基金Supported by the National Natural Science Foundation of China(No.11072106,No.51005133 and No.51375009)
文摘In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre- view back propagation （BP） neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po- sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.
