An adaptive tracking control system with 2-delay feedforward compensators

Author(s):  
Naoki Mizuno
Author(s):  
Dehua Zhang ◽  
Caijin Yang ◽  
Weihua Zhang ◽  
Yao Cheng

To achieve the running control of the all-wheel-driving and active-steering articulated vehicles (AWDASAVs) with n-units, an adaptive tracking control method is proposed in this paper, which includes a real-time target trajectory generation and an adaptive tracking control system. Firstly, the AWDASAV kinematics model is derived, and then the front-axle trace as the target trajectory is computed for all rear-axle steering by using data compressing and filtering, coordinate transformation, and local spline differences, which has small data storage and high computational efficiency and makes it easier to use in AWDASAV. Secondly, an adaptive tracking control system composed of an adaptive active steering controller and a differential distribution controller is designed to achieve accurate trajectory tracking and coordinated movement for AWDASAV. Finally, the AWDASAV simulation model with five-units was built in ADAMS by code development for cross-validation simulation, and the simulations with two cases at various speeds are carried out to verify the simulation model and control method. To further investigate the proposed method, the influence of three parameters on the tracking control performance and comparison with different control methods are carried out. The results exhibit excellent tracking control performance.


Author(s):  
Thanglong Mai

In this research, an adaptive tracking control method for the nonholonomic robot system is addressed based on the hybrid Proportional–Integral–Derivative (PID) technique. The proposed hybrid PID scheme first applies the merits of the traditional PID method, with the online self-learning capability for the PID – gains, to force tracking errors to zero in the presence of uncertainties. Then, in order to improve the tracking performance, an adaptive Fuzzy Neural Networks (FNN) approximator and an adaptive robust controller type-compensator are utilized to relax the uncertainties problems of the robot control system. Moreover, the nonholonomic constraint force stability of the mobile manipulator robot is also considered by an adaptive control scheme. The design of online updating laws for the proposed controllers and FNN approximator are designed by applying the Lyapunov stability theorem. Thus, besides the improvement for tracking control performance, the stability of the proposed control system is also maintained. The effectiveness, robustness and adaptability of the proposed control strategy are verified by comparative numerical simulation results.


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