Variable parameter robust gradient estimation algorithm with dead zone for the trajectory tracking of the joints of the manipulator

2004 ◽  
Author(s):  
Yuncan Xue ◽  
Zhiqian Mei ◽  
Jinlong Jiang ◽  
Qiwen Yang
Keyword(s):  
Trajectory Tracking ◽  
Dead Zone ◽  
Variable Parameter ◽  
Estimation Algorithm ◽  
Gradient Estimation

Adaptive Sliding Mode Control for Depth Trajectory Tracking of Remotely Operated Vehicle with Thruster Nonlinearity

2016 ◽  
Vol 70 (1) ◽  
pp. 149-164 ◽  
Author(s):  
Zhenzhong Chu ◽  
Daqi Zhu ◽  
Simon X. Yang ◽  
Gene Eu Jan
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Dead Zone ◽  
Adaptive Sliding Mode Control ◽  
Remotely Operated Vehicle ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode ◽  
Saturation Nonlinearity ◽  
Mode Control

This paper focuses on depth trajectory tracking control for a Remotely Operated Vehicle (ROV) with dead-zone nonlinearity and saturation nonlinearity of thruster; an adaptive sliding mode control method based on neural network is proposed. Through the analysis of dead-zone nonlinearity and saturation nonlinearity of thruster, the depth trajectory tracking control system model of a ROV which uses thruster control signals as system input has been established. According to the principle of sliding mode control, an adaptive sliding mode depth trajectory tracking controller is built by using three-layer feed-forward neural network for online identification of unknown items. The selection method and update laws of the control parameters are also given. The uniform ultimate boundedness of trajectory tracking error is analysed by Lyapunov theorem. Finally, the effectiveness of the proposed method is illustrated by simulations.

scholarly journals Parameter Adaptive Sliding Mode Trajectory Tracking Strategy with Initial Value Identification for the Swing in a Hydraulic Construction Robot

2022 ◽  
Author(s):  
Jingwei hou ◽  
Dingxuan Zhao ◽  
Zhuxin Zhang
Keyword(s):  
Trajectory Tracking ◽  
Sliding Mode ◽  
Estimation Algorithm ◽  
Robust Adaptive Control ◽  
Identification Algorithm ◽  
Initial Value ◽  
Robust Adaptive ◽  
Adaptive Control Strategy ◽  
The Moment ◽  
Tracking Strategy

Abstract A novel trajectory tracking strategy is developed for a double actuated swing in a hydraulic construction robot. Specifically, a nonlinear hydraulic dynamics model of a double actuated swing is established, and a robust adaptive control strategy is designed to enhance the trajectory tracking performance. When an object is grabbed and unloaded, the inertia of a swing considerably changes, and the performance of the estimation algorithm is generally inadequate. Thus, it is necessary to establish an algorithm to identify the initial value of the moment of inertia of the object. To this end, this paper proposes a novel initial value identification algorithm based on a two-DOF robot gravity force identification method combined with computer vision information. The performance of the identification algorithm is enhanced. Simulations and experiments are performed to verify the effect of the novel control scheme.

scholarly journals Trajectory Tracking of Autonomous Ground Vehicles with Actuator Dead Zones

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Pengfei Zhang ◽  
Qiyuan Chen ◽  
Tingting Yang
Keyword(s):  
Trajectory Tracking ◽  
Control Strategy ◽  
Tracking Control ◽  
Dead Zone ◽  
Fixed Time ◽  
Reference Trajectory ◽  
Ground Vehicles ◽  
Trajectory Tracking Control ◽  
Dead Zones ◽  
Autonomous Ground Vehicles

This paper investigates the trajectory tracking problem of autonomous ground vehicles (AGVs). The dynamics considered feature external disturbances, model uncertainties, and actuator dead zones. First, a novel time-varying yaw guidance law is proposed based on the line of sight method. By a state transformation, the AGV is proved to realize trajectory tracking control under the premise of eliminating guidance deviation. Second, a fixed time dead zone compensation control method is introduced to ensure the yaw angle tracking of the presented guidance. Furthermore, an improved fixed-time disturbance observer is proposed to compensate for the influence of the actuator dead zone on disturbance observation. Finally, the trajectory tracking control strategy is designed, and simulation comparison shows the effectiveness of the compensate method. The CarSim–MATLAB cosimulation shows that the proposed control strategy effectively makes the AGV follow the reference trajectory.

scholarly journals Enhancement of the Moving Horizon Estimation Performance Based on an Adaptive Estimation Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Steve Alan Talla Ouambo ◽  
Alexandre Teplaira Boum ◽  
Adolphe Moukengue Imano ◽  
Jean-Pierre Corriou
Keyword(s):  
Dynamical Systems ◽  
Least Squares ◽  
Adaptive Estimation ◽  
Dead Zone ◽  
Estimation Algorithm ◽  
Research Topic ◽  
Moving Horizon Estimation ◽  
Forgetting Factor ◽  
Constrained Dynamical Systems ◽  
Variable Forgetting Factor

Although moving horizon estimation (MHE) is a very efficient technique for estimating parameters and states of constrained dynamical systems, however, the approximation of the arrival cost remains a major challenge and therefore a popular research topic. The importance of the arrival cost is such that it allows information from past measurements to be introduced into current estimates. In this paper, using an adaptive estimation algorithm, we approximate and update the parameters of the arrival cost of the moving horizon estimator. The proposed method is based on the least-squares algorithm but includes a variable forgetting factor which is based on the constant information principle and a dead zone which ensures robustness. We show by this method that a fairly good approximation of the arrival cost guarantees the convergence and stability of estimates. Some simulations are made to show and demonstrate the effectiveness of the proposed method and to compare it with the classical MHE.

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