Variable parameter EW-RLS algorithm with dead zone for the trajectory tracking of the joints of the manipulator

2004 ◽  
Author(s):  
Yuncan Xue ◽  
Hongbin Du ◽  
Huihe Shao
Keyword(s):  
Trajectory Tracking ◽  
Dead Zone ◽  
Variable Parameter ◽  
Rls Algorithm

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 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 A Robust Adaptive Trajectory Tracking Algorithm Using SMC and Machine Learning for FFSGRs with Actuator Dead Zones

2019 ◽  
Vol 9 (18) ◽  
pp. 3837 ◽  
Author(s):  
Lin Jia ◽  
Yaonan Wang ◽  
Changfan Zhang ◽  
Kaihui Zhao ◽  
Li Liu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Steady State ◽  
Trajectory Tracking ◽  
Dead Zone ◽  
Lyapunov Theory ◽  
Tracking Algorithm ◽  
Convergence Time ◽  
Model Uncertainties ◽  
Friction Forces ◽  
State Error

The actuator dead zone of free-form surface grinding robots (FFSGRs) is very common in the grinding process and has a great impact on the grinding quality of a workpiece. In this paper, an improved trajectory tracking algorithm for an FFSGR with an asymmetric actuator dead zone was proposed with consideration of friction forces, model uncertainties, and external disturbances. The presented control algorithm was based on the machine learning and sliding mode control (SMC) methods. The control compensator used neural networks to estimate the actuator’s dead zone and eliminate its effects. The robust SMC compensator acted as an auxiliary controller to guarantee the system’s stability and robustness under circumstances with model uncertainties, approximation errors, and friction forces. The stability of the closed-loop system and the asymptotic convergence of tracking errors were evaluated using Lyapunov theory. The simulation results showed that the dead zone’s non-linearity can be estimated correctly, and satisfactory trajectory tracking performance can be obtained in this way, since the influences of the actuator’s dead zone were eliminated. The convergence time of the system was reduced from 1.1 to 0.8 s, and the maximum steady-state error was reduced from 0.06 to 0.015 rad. In the grinding experiment, the joint steady-state error decreased by 21%, which proves the feasibility and effectiveness of the proposed control method.

scholarly journals Constraint-Following Servo Control for the Trajectory Tracking of Manipulator with Flexible Joints and Mismatched Uncertainty

Machines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 202
Author(s):  
Fangfang Dong ◽  
Bin Yu ◽  
Xiaomin Zhao ◽  
Shan Chen ◽  
Haijun Liu
Keyword(s):  
Trajectory Tracking ◽  
Dead Zone ◽  
Fundamental Equation ◽  
Servo Control ◽  
Flexible Joints ◽  
Constraint Force ◽  
Mismatched Uncertainty ◽  
Common Application ◽  
Flexible Joint Manipulator ◽  
Fractional Type

Trajectory tracking is a common application method for manipulators. However, the tracking performance is hard to improve if the manipulators contain flexible joints and mismatched uncertainty, especially when the trajectory is nonholonomic. On the basis of the Udwadia–Kalaba Fundamental Equation (UKFE), the prescribed position or velocity trajectories are creatively transformed into second-order standard differential form. The constraint force generated by the trajectories is obtained in closed form with the help of UKFE. Then, a high-order fractional type robust control with an embedded fictitious signal is proposed to achieve practical stability of the system, even if the mismatched uncertainty exists. Only the bound of uncertainty is indispensable, rather than the exact information. A leakage type of adaptive law is proposed to estimate such bound. By introducing a dead-zone, the control will be simplified when the specific parameter enters a certain area. Validity of the proposed controller is verified by numerical simulation with two-link flexible joint manipulator.

Dynamic Damping and Stiffness Characteristics of the Rolling Tire

2001 ◽  
Vol 29 (4) ◽  
pp. 258-268 ◽  
Author(s):  
G. Jianmin ◽  
R. Gall ◽  
W. Zuomin
Keyword(s):  
Dynamic Behavior ◽  
Variable Parameter ◽  
Low Frequency ◽  
Vertical Load ◽  
Frequency Range ◽  
Inflation Pressure ◽  
Vehicle Simulation ◽  
Dynamic Damping ◽  
Speed Range ◽  
Stiffness Characteristics

Abstract A variable parameter model to study dynamic tire responses is presented. A modified device to measure terrain roughness is used to measure dynamic damping and stiffness characteristics of rolling tires. The device was used to examine the dynamic behavior of a tire in the speed range from 0 to 10 km/h. The inflation pressure during the tests was adjusted to 160, 240, and 320 kPa. The vertical load was 5.2 kN. The results indicate that the damping and stiffness decrease with velocity. Regression formulas for the non-linear experimental damping and stiffness are obtained. These results can be used as input parameters for vehicle simulation to evaluate the vehicle's driving and comfort performance in the medium-low frequency range (0–100 Hz). This way it can be important for tire design and the forecasting of the dynamic behavior of tires.

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