Digital robust preview control of path tracking

2005 ◽  
Vol 219 (1) ◽  
pp. 111-116
Author(s):  
Y G Tan ◽  
D K Liu ◽  
F Liu ◽  
Z D Zhou
Keyword(s):  
Control Systems ◽  
Tracking Control ◽  
Control Method ◽  
Path Tracking ◽  
Trajectory Control ◽  
Control Problems ◽  
Preview Control ◽  
Input Signals ◽  
Simulation Results ◽  
Reference Input

A robust optimal preview control method is presented in this paper for path tracking control problems to improve robustness and tracking precision of path tracking control systems. The known path information is used as reference input signals. Simulation results show that this method is valid not only for improving the performance of highly accurate trajectory control but also for improving system stabilization.

scholarly journals Path Tracking Control Method of a Modular Omnidirectional Vehicle.

2000 ◽  
Vol 66 (648) ◽  
pp. 2713-2720 ◽  
Author(s):  
Masafumi HASHIMOTO ◽  
Noriaki SUIZU ◽  
Fuminori OBA
Keyword(s):  
Tracking Control ◽  
Control Method ◽  
Path Tracking

scholarly journals Automatic Parking Path Planning and Tracking Control Research for Intelligent Vehicles

2020 ◽  
Vol 10 (24) ◽  
pp. 9100
Author(s):  
Chenxu Li ◽  
Haobin Jiang ◽  
Shidian Ma ◽  
Shaokang Jiang ◽  
Yue Li
Keyword(s):  
Path Planning ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Vehicle Control ◽  
Path Tracking ◽  
Intelligent Vehicles ◽  
Parking System ◽  
Automatic Parking ◽  
Real Vehicle

As a key technology for intelligent vehicles, automatic parking is becoming increasingly popular in the area of research. Automatic parking technology is available for safe and quick parking operations without a driver, and improving the driving comfort while greatly reducing the probability of parking accidents. An automatic parking path planning and tracking control method is proposed in this paper to resolve the following issues presented in the existing automatic parking systems, that is, low degree of automation in vehicle control; lack of conformity between segmented path planning and real vehicle motion models; and low success rates of parking due to poor path tracking. To this end, this paper innovatively proposes preview correction which can be applied to parking path planning, and detects the curvature outliers in the parking path through the preview algorithm. In addition, it is also available for correction in advance to optimize the reasonable parking path. Meanwhile, the dual sliding mode variable structure control algorithm is used to formulate path tracking control strategies to improve the path tracking control effect and the vehicle control automation. Based on the above algorithm, an automatic parking system was developed and the real vehicle test was completed, thus exploring a highly intelligent automatic parking technology roadmap. This paper provides two key aspects of system solutions for an automatic parking system, i.e., parking path planning and path tracking control.

Dynamic Autonomous Car Mobile Analysis Simulating Mechanical Systems Analysis – First Dynamic Characteristics of Running Mouse –

1998 ◽  
Vol 10 (6) ◽  
pp. 488-493
Author(s):  
Shigeki Toyama ◽  
◽  
Yasuo Murakuki
Keyword(s):  
Dynamic Characteristics ◽  
Systems Analysis ◽  
Tracking Control ◽  
Mechanical Systems ◽  
Dc Motor ◽  
Path Tracking ◽  
Running Performance ◽  
Tire Force ◽  
Simulation Results

This paper dynamically simulates a small running 2DW2C automobile (mouse) and simulates path tracking control. Our purpose was to optimize mouse design using simulation results. We added tire force and DC motor force to A1 Motion, a simulator for analyzing mechanical systems developed in our laboratory, and improved the simulator simulating a running automobile. Experiments with a small 2DW2C automobile compared experimental and simulation results involving dynamic characteristics of an actual mouse. We got correct simulation results using this model and simulator. We studied its running performance, affected by its wheelbase and caster length, and evaluated path tracking control using closoidal curves.

Robust Trajectory Tracking Control of Autonomous Quad-Rotor UAV Based on Double Loop Frame

2011 ◽  
Vol 467-469 ◽  
pp. 1421-1426
Author(s):  
Zhi Cheng Hou ◽  
X. Gong ◽  
Y. Bai ◽  
Y.T. Tian ◽  
Q. Sun
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
External Disturbance ◽  
Double Loop ◽  
Trajectory Tracking Control ◽  
Stability Augmentation ◽  
Aerial Vehicle ◽  
Simulation Results ◽  
Control Quantity

This paper deals with the under-actuated characteristic of a quad-rotor unmanned aerial vehicle (UAV). By designing the double loop configuration, the autonomous trajectory tracking is realized. The model uncertainty, external disturbance and the senor noise are also taken into consideration. Then the controller is put forward in the inner loop. An optimal stability augmentation control (SAC) method is used to stabilize the horizon position and keep it away from oscillation. By calculating the nonlinear decouple map, control quantity is converted to the speeds of the four rotors. At last some simulation results and the prototype implementation prove that the control method is effective.

scholarly journals Pre-Work for the Birth of Driver-Less Scraper (LHD) in the Underground Mine: The Path Tracking Control Based on an LQR Controller and Algorithms Comparison

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7839
Author(s):  
Haoxuan Yu ◽  
Chenxi Zhao ◽  
Shuai Li ◽  
Zijian Wang ◽  
Yulin Zhang
Keyword(s):  
Tracking Control ◽  
Control Method ◽  
Clustering Algorithms ◽  
Development Trend ◽  
Path Tracking ◽  
Linear Quadratic ◽  
Trajectory Tracking Control ◽  
Linear Quadratic Optimal Control ◽  
The Future ◽  
Lqr Controller

With the depletion of surface resources, mining will develop toward the deep surface in the future, the objective conditions such as the mining environment will be more complex and dangerous than now, and the requirements for personnel and equipment will be higher and higher. The efficient mining of deep space is inseparable from movable and flexible production and transportation equipment such as scrapers. In the new era, intelligence is leading to the development trend of scraper (LHD), path tracking control is the key to the intelligent scraper (LHD), and it is also an urgent problem to be solved for unmanned driving. This paper describes the realization of the automatic operation of articulating the scraper (LHD) from two aspects, a mathematical model and trajectory tracking control method, and it focuses on the research of the path tracking control scheme in the field of unmanned driving, that is, an LQR controller. On this basis, combined with different intelligent clustering algorithms, the parameters of the LQR controller are optimized to find the optimal solution of the LQR controller. Then, the path tracking control of an intelligent LHD unmanned driving technology is studied, focusing on the optimization of linear quadratic optimal control (LQR) and the intelligent cluster algorithms AGA, QPSO, and ACA; this research has great significance for the development of the intelligent scraper (LHD). As mining engineers, we not only need to conduct research for practical engineering projects but also need to produce theoretical designs for advanced mining technology; therefore, the area of intelligent mining is the one we need to explore at present and in the future. Finally, this paper serves as a guide to starting a conversation, and it has implications for the development and the future of underground transportation.

scholarly journals Research on LHD (Scraper) Path Tracking Control Based on LQR and Predict Pose Information

2021 ◽  
Author(s):  
Yulin Zhang ◽  
Chenxi Zhao ◽  
Zijian Wang ◽  
Haoxuan Yu
Keyword(s):  
Tracking Control ◽  
Control Method ◽  
Optimal Solution ◽  
Development Trend ◽  
Path Tracking ◽  
Trajectory Tracking Control ◽  
New Era ◽  
Transportation Equipment ◽  
Lqr Controller ◽  
Mining Work

With the depletion of shallow surface resources, the future mining work will develop towards the deep surface, and the objective conditions such as the mining environment will be more complex and dangerous than now, and the requirements for personnel and equipment will be higher and higher. The efficient exploitation of deep space cannot be separated from such mobile and flexible production and transportation equipment as scraper. In the new era, intelligence is the development trend of the LHD, and path tracking control technology is the key to the intelligent LHD, and it is also an urgent problem to be solved for its unmanned driving. This paper describes the realization of the automatic operation function of articulated LHD from two aspects of mathematical model and trajectory tracking control method, and focuses on the research of the path tracking control scheme in the field of unmanned driving, that is, LQR controller. On this basis, the parameters of the LQR controller are optimized by combining different intelligent cluster algorithms to find the optimal solution of the LQR controller.

scholarly journals Research on Path Planning and Tracking Control of Automatic Parking System

2022 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Bingzhan Zhang ◽  
Zhiyuan Li ◽  
Yaoyao Ni ◽  
Yujie Li
Keyword(s):  
Path Planning ◽  
Predictive Control ◽  
Tracking Control ◽  
Path Tracking ◽  
Preview Control ◽  
Laboratory Environment ◽  
Incremental Model ◽  
Quintic Polynomial ◽  
Parking System ◽  
Automatic Parking

In this paper, we focus on the parking path planning and path tracking control under parallel parking conditions with automatic parking system as the research object. In order to solve the problem of discontinuity of curvature in the path planning of traditional arc-straight combined curve, a quintic polynomial is used to smooth the path. we design a path tracking controller based on the incremental model predictive control (MPC). The preview control based on pure tracking algorithm is used as the comparison algorithm for path tracking. The feasibility of the controller is verified by building a Simulink/CarSim co-simulation platform. In addition, the practicality of the parking controller is further verified by using the ROS intelligent car in the laboratory environment.

Optimal Tracking Control for Discrete-time Systems with Time-delay Based on the Preview Control Method

2019 ◽  
Vol 7 (5) ◽  
pp. 452-461
Author(s):  
Haishan Xu ◽  
Fucheng Liao
Keyword(s):  
Optimal Control ◽  
Time Delay ◽  
Discrete Time ◽  
Tracking Control ◽  
Control Method ◽  
Reference Signal ◽  
Control Law ◽  
Preview Control ◽  
Optimal Tracking ◽  
Delayed System

Abstract In this paper, the optimal tracking control problem for discrete-time with state and input delays is studied based on the preview control method. First, a transformation is introduced. Thus, the system is transformed into a non-delayed system and the tracking problem of the time-delay system is transformed into the regulation problem of a non-delayed system via processing of the reference signal. Then, by applying the preview control theory, an augmented system for the non-delayed system is derived, and a controller with preview function is designed, assuming that the reference signal is previewable. Finally, the optimal control law of the augmented error system and the optimal control law of the original system are obtained by letting the preview length of the reference signal go to zero.

A Unified Hamiltonian Approach for LQ and H∞ Preview Control Algorithms

1999 ◽  
Vol 121 (3) ◽  
pp. 365-369 ◽  
Author(s):  
Lawrence Mianzo ◽  
Huei Peng
Keyword(s):  
Discrete Time ◽  
Tracking Control ◽  
Control Algorithms ◽  
Hamiltonian Approach ◽  
Test Rig ◽  
Preview Control ◽  
Durability Test ◽  
Simulation Results

A framework for solving both the continuous and discrete-time LQ and H∞ preview control algorithms is presented in this paper. The tracking control of an automotive durability test rig is used as an application example. Simulation results are presented to illustrate the effectiveness of the preview control algorithms.

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