scholarly journals A Type-2 Fuzzy Approach to Driver-Automation Shared Driving Lane Keeping Control of Semi-autonomous Vehicles under Imprecise Premise Variable

2021 ◽  
Author(s):  
Yue Liu ◽  
Qing Xu ◽  
Hongyan Guo ◽  
Hui ZHANG
Keyword(s):  
Control System ◽  
Control Method ◽  
Fuzzy Controller ◽  
System Stability ◽  
Linear Matrix ◽  
Direct Lyapunov Method ◽  
Steering Control ◽  
Driving Model ◽  
Lane Keeping

Abstract The driver-automation shared driving is a transition to fully-autonomous driving, in which human driver and vehicular controller cooperatively share the control authority. This paper investigates the shared steering control of semiautonomous vehicles with uncertainty from imprecise parameter. By considering driver’s lane-keeping behaviour on the vehicle system, a driver-automation shared driving model is introduced for control purpose. Based on the interval type-2 (IT2) fuzzy theory, moreover, the driver-automation shared driving model with uncertainty from imprecise parameter is described using an IT2 fuzzy model. After that, the corresponding IT2 fuzzy controller is designed and a direct Lyapunov method is applied to analyze the system stability. In this work, sufficient design conditions in terms of linear matrix inequalities are derived, to guarantee the closed-loop stability of the driver-automation shared control system. Meanwhile, an H ∞ performance is studied to ensure the robustness of the control system. Finally, simulationbased results are provided to demonstrate the performance of the proposed control method. Furthermore, an existing type-1 fuzzy controller is introduced as comparison, to verify the superiority of the proposed IT2 fuzzy controller.

Independent wheel control system design for highly automated driving

2021 ◽  
pp. 095440702110065
Author(s):  
Shihuan Li ◽  
Lei Wang
Keyword(s):  
Control System ◽  
Control Method ◽  
Autonomous Driving ◽  
Control System Design ◽  
Steering Control ◽  
Automated Driving ◽  
Accuracy And Precision ◽  
Actual Observation ◽  
Control Scheme ◽  
Interference Measurement

For L4 and above autonomous driving levels, the automatic control system has been redundantly designed, and a new steering control method based on brake has been proposed; a new dual-track model has been established through multiple driving tests. The axle part of the model was improved, the accuracy of the transfer function of the model was verified again through acceleration-slide tests; a controller based on interference measurement was designed on the basis of the model, and the relationships between the controller parameters was discussed. Through the linearization of the controller, the robustness of uncertain automobile parameters is discussed; the control scheme is tested and verified through group driving test, and the results prove that the accuracy and precision of the controller meet the requirements, the robustness stability is good. Moreover, the predicted value of the model fits well with the actual observation value, the proposal of this method provides a new idea for avoiding car out of control.

scholarly journals Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4181 ◽  
Author(s):  
Chun-Hui Lin ◽  
Shyh-Hau Wang ◽  
Cheng-Jian Lin
Keyword(s):  
Mobile Robots ◽  
Control Method ◽  
Fuzzy Controller ◽  
Bee Colony ◽  
Load Carrying ◽  
Navigation Control ◽  
Interval Type ◽  
Navigation Method ◽  
Neural Fuzzy

In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implemented for cooperative load-carrying mobile robots. In WFM learning, the proposed DGABC performs better than the original artificial bee colony algorithm and other improved algorithms. Furthermore, the results of cooperative load-carrying navigation control tests demonstrate that the proposed cooperative load-carrying method and the navigation method can enable the robots to carry the task item to the goal and complete the navigation mission efficiently.

Automated steering controller design for vehicle lane keeping combining linear active disturbance rejection control and quantitative feedback theory

2018 ◽  
Vol 232 (7) ◽  
pp. 937-948 ◽  
Author(s):  
Zhengrong Chu ◽  
Christine Wu ◽  
Nariman Sepehri
Keyword(s):  
Disturbance Rejection ◽  
Control Method ◽  
Controller Design ◽  
Active Disturbance Rejection Control ◽  
Quantitative Feedback Theory ◽  
Steering Control ◽  
Parameter Uncertainties ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Lane Keeping

In this article, a new automated steering control method is presented for vehicle lane keeping. This method is a combination between the linear active disturbance rejection control and the quantitative feedback theory. The structure of the steering controller is first determined based on the linear active disturbance rejection control, then the controller is tuned in the framework of the quantitative feedback theory to meet the prescribed design specifications on sensitivity and closed-loop stability. The parameter uncertainties of the vehicle system are considered at the tuning stage. The proposed steering controller is simulated and tested on a scale vehicle. Both the simulation and experimental results demonstrate that the scale vehicle controlled by the proposed controller is able to perform the lane keeping. In the experiments, the lateral offset between the scale vehicle and the road centerline is regulated within the acceptable ranges of ±0.03 m during straight lane keeping and ±0.15 m during curved lane keeping. The proposed controller is easy to be implemented and is simple without requiring complex calculations and measurements of vehicle states. Simulations also show that the control method can be implemented on a full-scale vehicle.

scholarly journals Research on vehicle active steering control based on linear matrix inequality and hardware in the loop test scheme design and implement for active steering

2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989210 ◽  
Author(s):  
Guangfei Xu ◽  
Peisong Diao ◽  
Xiangkun He ◽  
Jian Wu ◽  
Guosong Wang ◽  
...  
Keyword(s):  
Linear Matrix Inequality ◽  
Model Uncertainty ◽  
Control Method ◽  
Steering System ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Steering Control ◽  
Sensor Noise ◽  
Active Steering ◽  
Active Steering Control

In the research process of automotive active steering control, due to the model uncertainty, road surface interference, sensor noise, and other influences, the control accuracy of the active steering system will be reduced, and the driver’s road sense will become worse. The traditional robust controller can solve the model uncertainty, pavement disturbance and sensor noise in the design process, but cannot consider the performance enough. Therefore, this article proposes an active steering control method based on linear matrix inequality. In this method, the model uncertainty, road interference, sensor noise, yaw velocity, and slip side angle tracking errors are all considered as constraint targets, respectively, so that the performance and robust stability of the active front steering system can be guaranteed. Finally, simulation and hardware in the loop experiment are implemented to verify the effect of active front steering system under the linear matrix inequality controller. The results show that the proposed control method can achieve better robust performance and robust stability.

Modeling and Simulation of Nonlinear Networked Control System Based on Fuzzy Control

2012 ◽  
Vol 426 ◽  
pp. 368-371
Author(s):  
Sheng Li Song ◽  
Y. Chen ◽  
S.J. Huang ◽  
L.H Yang ◽  
R. He
Keyword(s):  
Control System ◽  
Nonlinear Problem ◽  
Control Method ◽  
Fuzzy Controller ◽  
Good Control ◽  
Networked Control System ◽  
Networked Control ◽  
Packet Dropout ◽  
Data Packet Dropout ◽  
Nonlinear Networked Control System

In the nonlinear networked control system (NCS), the conventional control method is difficult to achieve good control performance, due to the nonlinear problem associated with the disturbance factors, such as network induced time delay and data packet dropout. Considering this situation, this paper is aimed to propose a nonlinear networked control system based on T-S fuzzy model, which does not rely on specific network parameters or mathematical model. The nonlinear problem and the uncertainties of network can be both processed by the designed fuzzy controller. Then this approach is applied to nonlinear motor servo system, simulation of the example model is implemented in Matlab/Simulink associated with True Time toolbox. The results show that the proposed method not only is convenient for modeling, but also upgrade the performance of control system.

Disturbance Rejection of Interval Type-2 Fuzzy Systems Based on Equivalence-Input-Disturbance Approach

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
P. Selvaraj ◽  
R. Sakthivel ◽  
O. M. Kwon ◽  
M. Muslim
Keyword(s):  
Disturbance Rejection ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Reference Signal ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Input Disturbance ◽  
Interval Type ◽  
Fuzzy State

This paper focuses on the problem of disturbance rejection for a class of interval type-2 (IT-2) fuzzy systems via equivalence-input-disturbance (EID)-based approach. The main objective of this work is to design a fuzzy state-feedback controller combined with a disturbance estimator such that the output of the fuzzy system perfectly tracks the given reference signal without steady-state error and produces an EID to eliminate the influence of the actual disturbances. By constructing a suitable Lyapunov function and using linear matrix inequality (LMI) technique, a new set of sufficient conditions is established in terms of linear matrix inequalities for the existence of fuzzy controller. Finally, a simple pendulum model is considered to illustrate the effectiveness and applicability of the proposed EID-based control design.

The Fuzzy Control Method in Semi-Active Suspension

2010 ◽  
Vol 159 ◽  
pp. 644-649
Author(s):  
Jing Hua Zhao ◽  
Wen Bo Zhang ◽  
He Hao
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Simulation Analysis ◽  
Reference Model ◽  
Active Suspension ◽  
Vibration Characteristic ◽  
Acceleration Signal ◽  
Logic Control

Based on the analysis of performance of vehicle and its suspension, half vehicle model of five DOF and road model were built and the dynamic equations of half vehicle were derived according to the parameters of a commercial vehicle. In addition, a novel fuzzy logic control system based on semi-active suspension was introduced to achieve the optimal vibration characteristic, with changing the adjustable dampers according to dynamic vertical body acceleration signal. The fuzzy control was designed based on non-reference model method that acceleration value was sent to the fuzzy controller directly. And then, simulation analysis of semi-active suspension with fuzzy control method were implemented on the B-class road surface. The results showed that the semi-active suspension control system introduced in this paper has better performance on vieicle vibration characteristic, compared to passive suspension.

Takagi-Sugeno Fuzzy Load-Following Control of Nuclear Reactors Based on Reactor Point Kinetics Equations

2014 ◽  
Author(s):  
Xiuchun Luan ◽  
Jie Zhou ◽  
Yu Zhai
Keyword(s):  
Control System ◽  
Linear Models ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Neutron Density ◽  
Load Following ◽  
Wide Range ◽  
Takagi Sugeno ◽  
Operating Points

A state differential feedback control system based Takagi-Sugeno (T-S) fuzzy model is designed for load-following operation of nonlinear nuclear reactor whose operating points vary within a wide range. Linear models are first derived from the original nonlinear model on several operating points. Next the fuzzy controller is designed via using the parallel distributed compensation (PDC) scheme with the relative neutron density at the equilibrium point as the premise variable. Last the stability analysis is given by means of linear matrix inequality (LMI) approach, thus the control system is guaranteed to be stable within a large range. The simulation results demonstrate that the control system works well over a wide region of operation.

PID Parameter Setting Based on Fuzzy Control Algorithm and its Application in the Temperature Control System of Airplane

2012 ◽  
Vol 588-589 ◽  
pp. 1503-1506
Author(s):  
Fang Ding ◽  
Tao Ma
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Control Method ◽  
Fuzzy Controller ◽  
Temperature Control System ◽  
System Control ◽  
Control Effect ◽  
Fuzzy Control Algorithm

This Temperature control system of aircraft cabin is a complex system with nonlinear, time-varying, model inaccurate and work environment uncertain. According to the system control requirements, the fuzzy controller with the characteristic of fast response speed, good stability and strong resistance to interference is used in the study. The system error is adjusted constantly by using fuzzy control algorithm and simulation study is conducted in the software Matlab. The results are showed that control effect of control method used in this study is better than the traditional PID control method, and dynamic performance, steady state accuracy and robustness of system is effectively improved.

A Stable Adaptive Control Method in Networked Control System

2011 ◽  
Vol 110-116 ◽  
pp. 4837-4844
Author(s):  
Yu Zhang ◽  
Peng Cheng ◽  
Teng Fei Yin
Keyword(s):  
Control System ◽  
Time Delay ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sampling Period ◽  
Networked Control System ◽  
Network Control ◽  
Control Logic ◽  
Network Time ◽  
Long Time

In this paper it has made study on long time-delay network control system which is greater than one sampling period, it has made modeling on sensor node time drive, controller node and actuator node event-driven system The special question has been considered which was brought more than one sampling period delay, the fuzzy control logic has been applied in MATLAB to design an adaptive Fuzzy controller, when the network time delay changes the controller parameters can be adjusted dynamically, to make dynamic compensation on network time delay, and through simulation experiments to verify the algorithm effectiveness.

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