Adaptive Preview based Control System for Unmanned Vehicle Path Tracking

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
Wei Zhou
Keyword(s):  
Control System ◽  
Root Mean Square ◽  
Tracking Control ◽  
Tracking Error ◽  
Path Tracking ◽  
Mean Square ◽  
Steering Control ◽  
Deviation Angle ◽  
Control Module ◽  
Unmanned Vehicle

The unmanned vehicle control technology is constantly updated. How to accurately track the path has become a key issue. For this reason, a path tracking control system for an unmanned vehicle is designed. The system control module solves the lateral and longitudinal control problems of the unmanned vehicle. The preview compensation controller corrects the deviation of the vehicle approaching the normal track. The steering control module changes the direction of the vehicle based on the motor command signal. In the software part, the kinematics model of the unmanned vehicle in the plane rectangular coordinate system is built. In this model, the steering geometric track is constructed based on the Stanley algorithm. Track tracking preview model can adjust the preview adaptively according to the lateral deviation and heading angle deviation of the vehicle and gets the adaptive preview point. The simulation results show that the maximum absolute value of preview deviation angle, the root mean square of preview deviation angle and the root mean square of tracking error are lower. The effect of path tracking control is better. The effect of path tracking control is less affected by vehicle speed and road environment.

scholarly journals Adaptive Feedforward Control of a Pressure Compensated Differential Cylinder

2020 ◽  
Vol 10 (21) ◽  
pp. 7847
Author(s):  
Konrad Johan Jensen ◽  
Morten Kjeld Ebbesen ◽  
Michael Rygaard Hansen
Keyword(s):  
Control System ◽  
Root Mean Square ◽  
Motion Control ◽  
Experimental Verification ◽  
Feedforward Control ◽  
Position Error ◽  
Mean Square ◽  
Model Uncertainties ◽  
Feedforward Controller ◽  
Adaptive Feedforward

This paper presents the design, simulation and experimental verification of adaptive feedforward motion control for a hydraulic differential cylinder. The proposed solution is implemented on a hydraulic loader crane. Based on common adaptation methods, a typical electro-hydraulic motion control system has been extended with a novel adaptive feedforward controller that has two separate feedforward states, i.e, one for each direction of motion. Simulations show convergence of the feedforward states, as well as 23% reduction in root mean square (RMS) cylinder position error compared to a fixed gain feedforward controller. The experiments show an even more pronounced advantage of the proposed controller, with an 80% reduction in RMS cylinder position error, and that the separate feedforward states are able to adapt to model uncertainties in both directions of motion.

Experimental Validations on Vision-Based Path Tracking With Preview Four Wheel Steering Control

2019 ◽  
Author(s):  
Yansong Peng ◽  
Fengchen Wang ◽  
Saikrishna Gurumoorthy ◽  
Yan Chen ◽  
Mutian Xin
Keyword(s):  
Tracking Control ◽  
Low Cost ◽  
Experimental Tests ◽  
Front Wheel ◽  
Path Tracking ◽  
Steering Control ◽  
Tracking Errors ◽  
The Road ◽  
Experimental Validations ◽  
Lateral Offset

Abstract In this paper, a vision-based path-tracking control strategy using four-wheel steering (4WS) is experimentally investigated via an automated ground vehicle (AGV). A low-cost monocular camera is used to continuously perceive the upcoming lane boundaries via capturing the preview road image frames. Based on the applied image processing algorithms, the vehicle lateral offset error with respect to the road center line and the heading angle error with respect to the road curvature are calculated in real time for the control purpose. The 4WS path-tracking controller is designed to minimize the two path-tracking errors of the AGV. The AGV with the 4WS system is utilized to perform the experimental tests on road to validate the path-tracking control design. For comparison, the road test is also conducted for the path-tracking control with only the front wheel steering. The experimental results show that the proposed 4WS is able to achieve better path-tracking performance.

scholarly journals Self-Optimizing Path Tracking Controller for Intelligent Vehicles Based on Reinforcement Learning

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 31
Author(s):  
Jichang Ma ◽  
Hui Xie ◽  
Kang Song ◽  
Hao Liu
Keyword(s):  
Reinforcement Learning ◽  
Pid Control ◽  
Tracking Control ◽  
Tracking Error ◽  
Path Tracking ◽  
Pid Controllers ◽  
Model Parameters ◽  
Control Parameters ◽  
Tracking Controller ◽  
Complex Trajectories

The path tracking control system is a crucial component for autonomous vehicles; it is challenging to realize accurate tracking control when approaching a wide range of uncertain situations and dynamic environments, particularly when such control must perform as well as, or better than, human drivers. While many methods provide state-of-the-art tracking performance, they tend to emphasize constant PID control parameters, calibrated by human experience, to improve tracking accuracy. A detailed analysis shows that PID controllers inefficiently reduce the lateral error under various conditions, such as complex trajectories and variable speed. In addition, intelligent driving vehicles are highly non-linear objects, and high-fidelity models are unavailable in most autonomous systems. As for the model-based controller (MPC or LQR), the complex modeling process may increase the computational burden. With that in mind, a self-optimizing, path tracking controller structure, based on reinforcement learning, is proposed. For the lateral control of the vehicle, a steering method based on the fusion of the reinforcement learning and traditional PID controllers is designed to adapt to various tracking scenarios. According to the pre-defined path geometry and the real-time status of the vehicle, the interactive learning mechanism, based on an RL framework (actor–critic—a symmetric network structure), can realize the online optimization of PID control parameters in order to better deal with the tracking error under complex trajectories and dynamic changes of vehicle model parameters. The adaptive performance of velocity changes was also considered in the tracking process. The proposed controlling approach was tested in different path tracking scenarios, both the driving simulator platforms and on-site vehicle experiments have verified the effects of our proposed self-optimizing controller. The results show that the approach can adaptively change the weights of PID to maintain a tracking error (simulation: within ±0.071 m; realistic vehicle: within ±0.272 m) and steering wheel vibration standard deviations (simulation: within ±0.04°; realistic vehicle: within ±80.69°); additionally, it can adapt to high-speed simulation scenarios (the maximum speed is above 100 km/h and the average speed through curves is 63–76 km/h).

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.

An Active and Passive Steering Controller Study of Rubber-Tired Automated Guideway Transit Vehicles

1980 ◽  
Vol 102 (3) ◽  
pp. 168-173 ◽  
Author(s):  
Y. K. Kwak ◽  
C. C. Smith
Keyword(s):  
Comparative Study ◽  
Root Mean Square ◽  
Tracking Error ◽  
Degree Of Freedom ◽  
Ride Quality ◽  
Mean Square ◽  
Vehicle Model ◽  
Percent Reduction ◽  
Vehicle Performance ◽  
Active Steering

A comparative study of an active and passive steering controller of a rubber-tired Automated Guideway Transit (AGT) vehicle excited by random guideway irregularities is discussed. The thirteen-degree-of-freedom vehicle model, which was previously developed for passively steered rubber-tired AGT vehicles, is modified to facilitate the coupling of the vehicle to an active steering controller. Vehicle performance with the active steering controller, as well as the passive one, is evaluated in terms of root mean square (rms) values of the system outputs of interest. For the same level of the average rms tracking error, a two-sensor proportional active steering controller can improve the ride quality (about 12 percent reduction in lateral rms acceleration) compared to the present passive steering controller for a typical AGT vehicle with random guideway irregularity inputs.

Implementation of Trailer Steering Control on a Multi-Unit Vehicle at High Speeds

2013 ◽  
Vol 136 (2) ◽  
Author(s):  
Richard Roebuck ◽  
Andrew Odhams ◽  
Kristoffer Tagesson ◽  
Caizhen Cheng ◽  
David Cebon
Keyword(s):  
Control System ◽  
High Speed ◽  
Tracking Error ◽  
Path Following ◽  
Stability Control ◽  
Substantial Improvement ◽  
Lateral Acceleration ◽  
Steering Control ◽  
Stability Margins ◽  
Stability Control System

A high-speed path-following controller for long combination vehicles (LCVs) was designed and implemented on a test vehicle consisting of a rigid truck towing a dolly and a semitrailer. The vehicle was driven through a 3.5 m wide lane change maneuver at 80 km/h. The axles of the dolly and trailer were steered actively by electrically-controlled hydraulic actuators. Substantial performance benefits were recorded compared with the unsteered vehicle. For the best controller weightings, performance improvements relative to unsteered case were: lateral tracking error 75% reduction, rearward amplification (RA) of lateral acceleration 18% reduction, and RA of yaw rate 37% reduction. This represents a substantial improvement in stability margins. The system was found to work well in conjunction with the braking-based stability control system of the towing vehicle with no negative interaction effects being observed. In all cases, the stability control system and the steering system improved the yaw stability of the combination.

Path tracking control of electromechanical micro-positioner by considering control effort of the system

2020 ◽  
pp. 095965182095327
Author(s):  
Mohammad Reza Gharib ◽  
Ali Koochi ◽  
Mojtaba Ghorbani
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Path Tracking ◽  
Lumped Parameter Model ◽  
Proportional Integral Derivative ◽  
Control Effort ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Micro Actuators ◽  
And Control

Position controlling with less overshoot and control effort is a fundamental issue in the design and application of micro-actuators such as micro-positioner. Also, tracking a considered path is very crucial for some particular applications of micro-actuators such as surgeon robots. Herein, a proportional–integral–derivative controller is designed using a feedback linearization technique for path tracking control of a cantilever electromechanical micro-positioner. The micro-positioner is simulated based on a 1-degree-of-freedom lumped-parameter model. Three different paths are considered, and the capability of the designed controller on the path tracking with lower error and control effort is investigated. The obtained results demonstrate the efficiency of the designed proportional–integral–derivative controller not only for reducing the tracking error but also for decreasing the control effort.

Sign in / Sign up

Export Citation Format

Share Document