Driver-behavior-based robust steering control of unmanned driving robotic vehicle with modeling uncertainties and external disturbance

2020 ◽  
Vol 234 (6) ◽  
pp. 1585-1596
Author(s):  
Gang Chen ◽  
ShuHua Su
Keyword(s):  
Path Planning ◽  
Control Method ◽  
Driver Behavior ◽  
External Disturbance ◽  
Steering Control ◽  
Planning Strategy ◽  
Human Driver ◽  
Modeling Uncertainties ◽  
Robotic Vehicle ◽  
The Stability

In this paper, a steering robust control method based on professional driver behavior with modeling uncertainties and external disturbance is proposed for an unmanned driving robotic vehicle, to realize the accurate and stable steering control like a professional human driver. An unmanned driving robotic vehicle nonlinear dynamics model considering modeling uncertainties and external disturbance is established. A driver behavior model composed of an adaptive preview model, a driver path planning model, and a driver desired yaw rate model is established, with the influences on preview time and driver path planning strategy, respectively. On the basis of this, a robust steering controller based on professional driver behavior is presented, by taking road information, driver reaction delay time, and vehicle driving status as inputs and the servo motor rotation angle of the steering mechanical arm as output. The stability of the control system with modeling uncertainties and external disturbance is proved. A comparison of the analysis results of simulation and experiment among the proposed control method, other existing control methods, and professional human driver demonstrates the effectiveness of the proposed method.

scholarly journals Multiobjective Trajectory Optimization and Adaptive Backstepping Control for Rubber Unstacking Robot Based on RFWNN Method

2018 ◽  
Vol 2018 ◽  
pp. 1-19
Author(s):  
Le Liang ◽  
Yanjie Liu ◽  
Hao Xu
Keyword(s):  
Trajectory Optimization ◽  
Control Method ◽  
External Disturbance ◽  
Backstepping Control ◽  
Adaptive Robust Control ◽  
Robot Dynamics ◽  
Adaptive Backstepping ◽  
Recycling Process ◽  
Adaptive Backstepping Control ◽  
Modeling Uncertainties

Multiobjective trajectory optimization and adaptive backstepping control method based on recursive fuzzy wavelet neural network (RFWNN) are proposed to solve the problem of dynamic modeling uncertainties and strong external disturbance of the rubber unstacking robot during recycling process. First, according to the rubber viscoelastic properties, the Hunt-Crossley nonlinear model is used to construct the robot dynamics model. Then, combined with the dynamic model and the recycling process characteristics, the multiobjective trajectory optimization of the rubber unstacking robot is carried out for the operational efficiency, the running trajectory smoothness, and the energy consumption. Based on the trajectory optimization results, the adaptive backstepping control method based on RFWNN is adopted. The RFWNN method is applied in the main controller to cope with time-varying uncertainties of the robot dynamic system. Simultaneously, an adaptive robust control law is developed to eliminate inevitable approximation errors and unknown disturbances and relax the requirement for prior knowledge of the controlled system. Finally, the validity of the proposed control strategy is verified by experiment.

A finite-time H-infinite adaptive fault-tolerant controller considering time delay for flutter suppression of airfoil flutter

2019 ◽  
Vol 234 (2) ◽  
pp. 293-307
Author(s):  
Gao Ming-Zhou ◽  
Chen Xin-Yi ◽  
Han Rong ◽  
Yao Jian-Yong
Keyword(s):  
Finite Time ◽  
Control Method ◽  
Controller Design ◽  
Fault Tolerant ◽  
Linear Matrix ◽  
Control Methods ◽  
Actuator Faults ◽  
Control Delay ◽  
Modeling Uncertainties ◽  
The Stability

To suppress airfoil flutter, a lot of control methods have been proposed, such as classical control methods and optimal control methods. However, these methods did not consider the influence of actuator faults and control delay. This paper proposes a new finite-time H∞ adaptive fault-tolerant flutter controller by radial basis function neural network technology and adaptive fault-tolerant control method, taking into account actuator faults, control delay, modeling uncertainties, and external disturbances. The theoretic section of this paper is about airfoil flutter dynamic modeling and adaptive fault-tolerant controller design. Lyapunov function and linear matrix inequality are employed to prove the stability of the proposed control method of this paper. The numeral simulation section further proves the effectiveness and robustness of the proposed control algorithm of this paper.

scholarly journals Adaptive robust control for free-floating space robot with unknown uncertainty based on neural network

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881151
Author(s):  
Zhang Wenhui ◽  
Li Hongsheng ◽  
Ye Xiaoping ◽  
Huang Jiacai ◽  
Huo Mingying
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Robust Control ◽  
Control Method ◽  
External Disturbance ◽  
Adaptive Robust Control ◽  
Lyapunov Theory ◽  
Space Robot ◽  
Neural Network Controller ◽  
The Stability

It is difficult to obtain a precise mathematical model of free-floating space robot for the uncertain factors, such as current measurement technology and external disturbance. Hence, a suitable solution would be an adaptive robust control method based on neural network is proposed for free-floating space robot. The dynamic model of free-floating space robot is established; a computed torque controller based on exact model is designed, and the controller can guarantee the stability of the system. However, in practice, the mathematical model of the system cannot be accurately obtained. Therefore, a neural network controller is proposed to approximate the unknown model in the system, so that the controller avoids dependence on mathematical models. The adaptive learning laws of weights are designed to realize online real-time adjustment. The adaptive robust controller is designed to suppress the external disturbance and compensate the approximation error and improve the robustness and control precision of the system. The stability of closed-loop system is proved based on Lyapunov theory. Simulations tests verify the effectiveness of the proposed control method and are of great significance to free-floating space robot.

Model-based robust control design and experimental validation of SCARA robot system with uncertainty

2022 ◽  
pp. 107754632110421
Author(s):  
ShengChao Zhen ◽  
MuCun Ma ◽  
XiaoLi Liu ◽  
Feng Chen ◽  
Han Zhao ◽  
...  
Keyword(s):  
Robust Control ◽  
Control Algorithm ◽  
Lyapunov Method ◽  
Control Method ◽  
External Disturbance ◽  
Scara Robot ◽  
Model Based ◽  
Robust Control Design ◽  
Robot Performance ◽  
The Stability

In this paper, we design a novel robust control method to reduce the trajectory tracking errors of the SCARA robot with uncertainties including parameters such as uncertainty of the mechanical system and external disturbance, which are time-varying and nonlinear. Then, we propose a deterministic form of the model-based robust control algorithm to deal with the uncertainties. The proposed control algorithm is composed of two parts according to the assumed upper limit of the system uncertainties: one is the traditional proportional-derivative control, and the other is the robust control based on the Lyapunov method, which has the characteristics of model-based and error-based. The stability of the proposed control algorithm is proved by the Lyapunov method theoretically, which shows the system can maintain uniformly bounded and uniformly ultimately bounded. The experimental platform includes the rapid controller prototyping cSPACE, which is designed to reduce programming time and to improve the efficiency of the practical operation. Moreover, we adopt different friction models to investigate the effect of friction on robot performance in robot joints. Finally, numerical simulation and experimental results indicate that the control algorithm proposed in this paper has desired control performance on the SCARA robot.

Vehicle stability enhancement and rollover prevention by a nonlinear predictive control method

2018 ◽  
Vol 41 (8) ◽  
pp. 2135-2149 ◽  
Author(s):  
M. Selçuk Arslan ◽  
Mert Sever
Keyword(s):  
Predictive Control ◽  
Control Method ◽  
Vertical Load ◽  
Steering Control ◽  
Yaw Rate ◽  
Rollover Prevention ◽  
Nonlinear Predictive Control ◽  
Predictive Controller ◽  
The Stability ◽  
Stability Enhancement

In this study, a nonlinear predictive control method is developed for the active steering control of a sport utility vehicle. The method is tested on a nonlinear mathematical model of an 11-degree-of-freedom vehicle. The system performance is evaluated by considering that the control law must keep the actual yaw rate close to the desired yaw rate and minimizing the vertical load changes at each wheel. The latter is proposed for this work. The vertical load changes play an important role in the dynamics and the stability of the system. The effectiveness of the control method is demonstrated through numerical simulation by using a vehicle model that includes three case studies: rapid lane change at low and high velocities and the fishhook manoeuvre. The results show that the stability of the vehicle is maintained and its rollover propensity is decreased. In addition, the proposed controller is compared with a well-known linear model predictive controller.

The Active Front Steering Control Strategy Based on Driver Behavior

2013 ◽  
Vol 373-375 ◽  
pp. 1277-1282
Author(s):  
Jian Zhao ◽  
Yun Fu Su ◽  
Bing Zhu ◽  
Peng Fei Wang
Keyword(s):  
Driver Behavior ◽  
Driver Model ◽  
Steering Wheel ◽  
Steering Control ◽  
Active Steering ◽  
Active Front Steering ◽  
Reference Vehicle ◽  
The Stability ◽  
Prediction Control ◽  
Two Degree Of Freedom

Active Front Steering (AFS) is an important application to improve the stability of the vehicle, and the driver characteristic is also an important factor for the vehicle stability. In this article, a driver-behavior-based prediction control algorithm for AFS is proposed. According to the informed road trajectory, the ideal preview driver model is introduced to predict the future steering wheel angle. Based on this, a two-degree-of-freedom (2DOF) reference vehicle model and a PID controller are used to generate active steering control. The algorithm is verified by Carsim and Matlab/Simulink co-simulation, and the results show that trajectory tracking of the vehicle can be guarantee and driver manipulation duty can be reduced.

scholarly journals A New Adaptive Fuzzy PID Control Method and Its Applicance in FCBTM

2016 ◽  
Vol 11 (3) ◽  
pp. 394 ◽  
Author(s):  
Jingang Lai ◽  
Hong Zhou ◽  
Wenshan Hu
Keyword(s):  
Control Method ◽  
External Disturbance ◽  
Testing Machine ◽  
Three Dimensional ◽  
Test Results ◽  
Motor Speed ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
The Stability ◽  
Adaptive Fuzzy Pid Control

<p class="Abstract">The process of tension control for material testing using the Flexible ircuit Board testing machine (FCBTM) is featured with multi-variable, nonlinearity, ime delays and time variation. In order to ensure the tension precision, the stability of ervo motor’ speed and the reliability of test results, this paper establishes an accurate ystem model for the FCBTM, in which a novel three-dimensional adaptive fuzzy ID controller is designed. Specially, the simulation results show that the proposed daptive fuzzy control method is not only robust to the external disturbance but also ith more excellent dynamic and steady-state characteristics than traditional ones.</p>

scholarly journals Fault Diagnosis and Reconfigurable Control for Commercial Aircraft with Multiple Faults and Actuator Saturation

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 108
Author(s):  
Yishi Liu ◽  
Sheng Hong ◽  
Enrico Zio ◽  
Jianwei Liu
Keyword(s):  
Fault Diagnosis ◽  
Control Method ◽  
Actuator Saturation ◽  
Fault Tolerant ◽  
External Disturbance ◽  
Fault Tolerant Control ◽  
Adaptive Method ◽  
Reconfigurable Control ◽  
Multiple Faults ◽  
The Stability

Active fault-tolerant control systems perform fault diagnosis and reconfigurable control. There is a bidirectional uncertainty between them, and an integrated scheme is proposed here to account for that. The system considers both actuator and sensor faults, as well as the external disturbance. The diagnostic module is designed using an unknown input observer, and the controller is constructed on the basis of an adaptive method. The integrated strategy is presented, and the stability of the overall system is analyzed. Moreover, different kinds of anti-windup techniques are utilized to modify the original controllers, because of the different controller structures. A simulation of the integrated anti-windup fault-tolerant control method is demonstrated using a numerical model of Boeing 747. The results show that it can guarantee the stability of the post-fault aircraft and increase the control performance for the overall faulty system.

scholarly journals Robust Computed Torque Control for Uncertain Robotic Manipulatorss

2021 ◽  
Vol 17 (3) ◽  
pp. 22-28
Author(s):  
Maryam Sadeq Ahmed ◽  
Ali Hussien M Mary ◽  
Hisham Hassan Jasim
Keyword(s):  
Control Systems ◽  
Control Method ◽  
External Disturbance ◽  
Torque Control ◽  
Robotic Control ◽  
System Uncertainty ◽  
Computed Torque Control ◽  
And Performance ◽  
The Stability ◽  
Computed Torque

This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem.  The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.

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