scholarly journals Trajectory Tracking Control in Real-Time of Dual-Motor-Driven Driverless Racing Car Based on Optimal Control Theory and Fuzzy Logic Method

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Gang Li ◽  
Sucai Zhang ◽  
Lei Liu ◽  
Xubin Zhang ◽  
Yuming Yin
Keyword(s):  
Optimal Control ◽  
Fuzzy Logic ◽  
Optimal Control Theory ◽  
Tracking Control ◽  
Control Method ◽  
Steering Control ◽  
Trajectory Tracking Control ◽  
Differential Drive ◽  
Active Steering ◽  
Fuzzy Logic Method

To improve the accuracy and timeliness of the trajectory tracking control of the driverless racing car during the race, this paper proposes a track tracking control method that integrates the rear wheel differential drive and the front wheel active steering based on optimal control theory and fuzzy logic method. The model of the lateral track tracking error of the racing car is established. The model is linearized and discretized, and the quadratic optimal steering control problem is constructed. Taking advantage of the differential drive of dual-motor-driven racing car, the dual motors differential drive fuzzy controller is designed and integrated driving with active steering control. Simulation analysis and actual car verification show that this integrated control method can ensure that the car tracks different race tracks well and improve the track tracking control accuracy by nearly 30%.

A novel tracking control method for the distributed-drive and active-steering articulated virtual rail train

2021 ◽  
pp. 095965182110274
Author(s):  
Dehua Zhang ◽  
Caijin Yang ◽  
Weihua Zhang ◽  
Yao Cheng
Keyword(s):  
Control System ◽  
Data Storage ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Generation ◽  
Front Axle ◽  
Steering Control ◽  
Differential Distribution ◽  
Target Trajectory ◽  
Active Steering

To realize the running control of distributed-drive and active-steering articulated virtual rail trains travelling on urban roads under non-contact virtual rail constraints, target trajectory generation and active-steering control are crucial issues. In this article, a novel tracking control method is proposed, which includes a dynamic target trajectory generation and a new active-steering tracking control system. First, a distributed-drive and active-steering articulated virtual rail train kinematics model with n-sections is derived, and then a new target trajectory generation method is proposed using data filtering and compression, coordinate transformation and spline difference, and the simulation comparison shows that the proposed method has less data storage space and high computational efficiency. Second, a new active-steering tracking control system composed of a rear axle preview active-steering controller, a front axle coordinated steering controller, and a differential-distribution controller is designed to achieve tracking control and coordinated movement of distributed-drive and active-steering articulated virtual rail train. Finally, a distributed-drive and active-steering articulated virtual rail train simulation model was constructed in ADAMS, and then simulations are performed under three rail conditions and compared with the other two methods, which show that the proposed method has good tracking control accuracy, adaptability, and superiority under various rails and different speeds.

Trajectory Tracking Control of Mobile Robot Based on Self-Adaptive PID Combined with Preview and Fuzzy Logic

2012 ◽  
Vol 590 ◽  
pp. 268-271 ◽  
Author(s):  
Da Lei Li ◽  
Zhan Shu He ◽  
Yue Feng Yin
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Mobile Robot ◽  
Trajectory Tracking ◽  
Pid Control ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Tracking Control ◽  
Adaptive Pid Control ◽  
Self Adaptive

A new method for controlling the steering and trajectory of the electric mobile robot is proposed. In order to control the robot’s position and heading, the path error and the heading error of the robot are taken into the control closed loop. On the basis of the self-adaptive PID control method combined with preview theory and fuzzy logic, a trajectory tracking control system is designed. Finally, experiments and simulation are conducted to test the control system. Both experimental and simulation results show that the mobile robot can approach the target trajectory quickly and then move along it, which confirm the validity and the efficiency of the trajectory tracking control system.

scholarly journals A 4-DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation

2021 ◽  
Vol 11 (13) ◽  
pp. 5865
Author(s):  
Muhammad Ahsan Gull ◽  
Mikkel Thoegersen ◽  
Stefan Hein Bengtson ◽  
Mostafa Mohammadi ◽  
Lotte N. S. Andreasen Struijk ◽  
...  
Keyword(s):  
Upper Limb ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Mechanical Design ◽  
Trajectory Tracking Control ◽  
Upper Limb Exoskeleton ◽  
And Performance ◽  
Physically Disabled People ◽  
Human Upper Limb

Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.

Robust finite-time trajectory tracking control for a space manipulator with parametric uncertainties and external disturbances

2021 ◽  
pp. 095441002110147
Author(s):  
Qijia Yao
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Space Manipulator ◽  
Tracking Controller

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

Research on automobile four-wheel steering control system based on yaw angular velocity and centroid cornering angle

2021 ◽  
pp. 002029402110354
Author(s):  
Yifeng Zhang ◽  
Zhiwen Wang ◽  
Yuhang Wang ◽  
Canlong Zhang ◽  
Biao Zhao
Keyword(s):  
Optimal Control ◽  
Feedback Control ◽  
High Speed ◽  
Control Method ◽  
Response Speed ◽  
State Feedback Control ◽  
Steering Control ◽  
Yaw Rate ◽  
Simulink Simulation ◽  
Optimal Control Method

In order to improve the handling stability of four-wheel steering (4WS) cars, a two-degree-of-freedom 4WS vehicle dynamics model is constructed here, and the motion differential equation of the system model is established. Based on the quadratic optimal control theory, the optimal control of 4WS system is proposed in this paper. When running at low speed and high speed, through yaw rate feedback control, state feedback control, and optimal control, the 4WS cars are controlled based on yaw rate and centroid cornering angle with MATLAB/Simulink simulation. The result indicates that 4WS control based on the optimal control can improve the displacement of the cars. And, the optimal control of 4WS proposed in this paper can eliminate centroid cornering angle completely compared with other two traditional optimal control methods. Besides, the optimal control enjoys faster response speed and no overshoot happens. In conclusion, the optimal control method proposed in the paper represents better stability, moving track and stability, thereby further enhancing the handling property of cars.

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.

Dynamic trajectory-tracking control method of robotic transcranial magnetic stimulation with end-effector gravity compensation based on force sensors

2018 ◽  
Vol 45 (6) ◽  
pp. 722-731
Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Magnetic Stimulation ◽  
Control Method ◽  
Gravity Compensation ◽  
Trajectory Tracking Control ◽  
End Effector ◽  
Content Type ◽  
Dynamic Trajectory

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

Integrated Forward and Reverse Trajectory Tracking Control for Car-Like Ground Vehicle

2019 ◽  
Author(s):  
Yuanyan Chen ◽  
J. Jim Zhu ◽  
Letian Lin
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Kinematics And Dynamics ◽  
Test Results ◽  
Ground Vehicles ◽  
Steering Control ◽  
Original Design ◽  
Trajectory Tracking Control ◽  
Validation Test ◽  
Highly Nonlinear

Abstract Conventional automatic trajectory tracking control technics for car-like ground vehicles typically decompose the controller into separate longitudinal driving control and lateral-directional steering control, owing to the nonholonomic kinematic constraint, highly nonlinear dynamics and control under-actuation of such vehicles. However, such decoupled control techniques inevitably impose operational constraints on agile maneuvers that may be critical in evading impending collisions, preventing loss-of-control of the vehicle, and special maneuvers that are needed for law enforcement missions. Thus, integrated three-Degree-of-Freedom (3DOF) tracking control of car-like ground vehicles are highly desirable but remains a challenging problem. There also appears to be a lack of research on automated reverse driving. In our previous work [ASME DSCC2017-5372, DSCC2018-9148], design and hardware validation test results of an integrated 3DOF trajectory tracking controller based on nonlinear kinematics and dynamics vehicle model using Trajectory Linearization Control (TLC) for forward driving have been reported. The present paper supplements that work with design and hardware validation test results on vehicle backward driving at fast and low speeds. The reverse driving control incurs minimal alteration to the original design with minimal tuning efforts due to the model-based TLC control approach, and it should be readily scaled-up to full-size vehicles and adapted to different types of autonomous ground vehicles with the knowledge of vehicles’ kinematics and dynamics parameters.

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