Development of a Control Strategy for Accurate Path Tracking of Intelligent Vehicles

2019 ◽  
Author(s):  
M.G. Mehrabi
Keyword(s):  
Control Strategy ◽  
Path Tracking ◽  
Intelligent Vehicles

scholarly journals Emergency collision avoidance control strategy based on four-wheel steering and differential braking

2021 ◽  
Author(s):  
Haiqing Li ◽  
Yongfu Li ◽  
Taixiong Zheng ◽  
Jiufei Luo ◽  
Zonghuan Guo
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Tracking Control ◽  
Development Trend ◽  
Path Tracking ◽  
Intelligent Vehicles ◽  
Control Mode ◽  
Avoidance Control ◽  
Driving Stability

Abstract Path tracking control strategy of emergency collision avoidance is the research hotspot for intelligent vehicles, and active four-wheel steering and integrated chassis control such as differential braking are the development trend for the control system of intelligent vehicle. Considering both driving performance and path tracking performance, an active obstacle avoidance controller integrated with four-wheel steering (4WS), active rear steering (ARS) and differential braking control (RBC) based on adaptive model predictive theory (AMPC) is proposed. The designed active obstacle avoidance control architecture is composed of two parts, a supervisor and an MPC controller. The supervisor is responsible for selecting the appropriate control mode based on driving vehicle information and threshold of lateral and roll stability. In addition, a non-linear predict model is employed to obtain the future states of the driving vehicle. Then the AMPC is used to calculate the desired steering angle and differential braking toque when the driving stability indexes exceed the safety threshold. Finally, the proposed collision avoidance path tracking control strategy was simulated under emergency conditions via Carsim-Simulink co-simulation. The results show that the controller based on AMPC can be used to tracking the path of obstacle avoidance and has good performance in driving stability under emergencies.

Path Tracking of a UAV via an Underactuated Control Strategy

2011 ◽  
Vol 17 (2) ◽  
pp. 194-213 ◽  
Author(s):  
Guilherme V. Raffo ◽  
Manuel G. Ortega ◽  
Francisco R. Rubio
Keyword(s):  
Control Strategy ◽  
Path Tracking ◽  
Underactuated Control

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.

scholarly journals Suspended Load Path Tracking Control Strategy Using a Tilt-Rotor UAV

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
M. A. Santos ◽  
B. S. Rego ◽  
G. V. Raffo ◽  
A. Ferramosca
Keyword(s):  
Control Strategy ◽  
Degrees Of Freedom ◽  
Unscented Kalman Filter ◽  
Equations Of Motion ◽  
Suspended Load ◽  
Path Tracking ◽  
Total System ◽  
Load Path ◽  
Tilt Rotor ◽  
Lagrange Formulation

This work proposes a control strategy to solve the path tracking problem of a suspended load carried by a tilt-rotor unmanned aerial vehicle (UAV). Initially, the equations of motion for the multibody mechanical system are derived from the load’s perspective by means of the Euler-Lagrange formulation, in which the load’s position and orientation are chosen as degrees of freedom. An unscented Kalman filter (UKF) is designed for nonlinear state estimation of all the system states, assuming that available information is provided by noisy sensors with different sampling rates that do not directly measure the load’s attitude. Furthermore, a model predictive control (MPC) strategy is proposed for path tracking of the suspended load with stabilization of the tilt-rotor UAV when parametric uncertainties and external disturbances affect the load, the rope’s length and total system mass vary during taking-off and landing, and the desired yaw angle changes throughout the trajectory. Finally, numerical experiments are presented to corroborate the good performance of the proposed strategy.

scholarly journals A HEURISTIC CASCADING FUZZY LOGIC APPROACH TO REACTIVE NAVIGATION FOR UAV

2014 ◽  
Vol 15 (2) ◽  
Author(s):  
Yew-Chung Chak ◽  
Renuganth Varatharajoo
Keyword(s):  
Fuzzy Logic ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Tracking Control ◽  
Path Tracking ◽  
Reactive Navigation ◽  
Logic Control ◽  
Fuzzy Logic Approach ◽  
Avoidance Control ◽  
Logic Approach

ABSTRACT: The capability of navigating Unmanned Aerial Vehicles (UAVs) safely in unknown terrain offers huge potential for wider applications in non-segregated airspace. Flying in non-segregated airspace present a risk of collision with static obstacles (e.g., towers, power lines) and moving obstacles (e.g., aircraft, balloons). In this work, we propose a heuristic cascading fuzzy logic control strategy to solve for the Conflict Detection and Resolution (CD&R) problem, in which the control strategy is comprised of two cascading modules. The first one is Obstacle Avoidance control and the latter is Path Tracking control. Simulation results show that the proposed architecture effectively resolves the conflicts and achieve rapid movement towards the target waypoint.ABSTRAK: Keupayaan mengemudi Kenderaan Udara Tanpa Pemandu (UAV) dengan selamat di kawasan yang tidak diketahui menawarkan potensi yang besar untuk aplikasi yang lebih luas dalam ruang udara yang tidak terasing. Terbang di ruang udara yang tidak terasing menimbulkan risiko perlanggaran dengan halangan statik (contohnya, menara, talian kuasa) dan halangan bergerak (contohnya, pesawat udara, belon). Dalam kajian ini, kami mencadangkan satu strategi heuristik kawalan logik kabur yang melata untuk menyelesaikan masalah Pengesanan Konflik dan Penyelesaian (CD&R), di mana strategi kawalan yang terdiri daripada dua modul melata. Hasil simulasi menunjukkan bahawa seni bina yang dicadangkan berjaya menyelesaikan konflik dan mencapai penerbangan pesat ke arah titik laluan sasaran.KEYWORDS: fuzzy logic; motion planning; obstacle avoidance; path tracking; reactive navigation; UAV

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