Path planning and robust fuzzy output-feedback control for unmanned ground vehicles with obstacle avoidance

2020 ◽  
pp. 095440702097831
Author(s):  
Yimin Chen ◽  
Chuan Hu ◽  
Yechen Qin ◽  
Mingjun Li ◽  
Xiaolin Song
Keyword(s):  
Feedback Control ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Unmanned Ground Vehicles ◽  
Ground Vehicles ◽  
Velocity Signal ◽  
Moving Obstacles ◽  
Avoidance Strategy

Obstacle avoidance strategy is important to ensure the driving safety of unmanned ground vehicles. In the presence of static and moving obstacles, it is challenging for the unmanned ground vehicles to plan and track the collision-free paths. This paper proposes an obstacle avoidance strategy consists of the path planning and the robust fuzzy output-feedback control. A path planner is formed to generate the collision-free paths that avoid static and moving obstacles. The quintic polynomial curves are employed for path generation considering computational efficiency and ride comfort. Then, a robust fuzzy output-feedback controller is designed to track the planned paths. The Takagi–Sugeno (T–S) fuzzy modeling technique is utilized to handle the system variables when forming the vehicle dynamic model. The robust output-feedback control approach is used to track the planned paths without using the lateral velocity signal. The proposed obstacle avoidance strategy is validated in CarSim® simulations. The simulation results show the unmanned ground vehicle can avoid the static and moving obstacles by applying the designed path planning and robust fuzzy output-feedback control approaches.

Robust H∞ output-feedback control for path following of autonomous ground vehicles

2016 ◽  
Vol 70-71 ◽  
pp. 414-427 ◽  
Author(s):  
Chuan Hu ◽  
Hui Jing ◽  
Rongrong Wang ◽  
Fengjun Yan ◽  
Mohammed Chadli
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Path Following ◽  
Ground Vehicles ◽  
Autonomous Ground Vehicles

Energy-based output feedback control of the underactuated 2DTORA system with saturated inputs

2020 ◽  
Vol 42 (14) ◽  
pp. 2822-2829
Author(s):  
Kexin Xu ◽  
Xianqing Wu ◽  
Miao Ma ◽  
Yibo Zhang
Keyword(s):  
Feedback Control ◽  
Lyapunov Function ◽  
Output Feedback ◽  
Control Method ◽  
Actuator Saturation ◽  
Output Feedback Control ◽  
Lyapunov Theory ◽  
Velocity Signal ◽  
Feedback Control Method ◽  
The Stability

In this paper, we consider the control issues of the two-dimensional translational oscillator with rotational actuator (2DTORA) system, which has two translational carts and one rotational rotor. An output feedback controller for the 2DTORA system is proposed, which can prevent the unwinding behaviour. In addition, the velocity signal unavailability and actuator saturation are taken into account, simultaneously. In particular, the dynamics of the 2DTORA system are given first. On the basis of the passivity and control objectives of the 2DTORA system, an elaborate Lyapunov function is constructed. Then, based on the introduced Lyapunov function, a novel output feedback control method is proposed straightforwardly for the 2DTORA system. Lyapunov theory and LaSalle’s invariance principle are utilized to analyse the stability of the closed-loop system and the convergence of the states. Finally, simulation results are provided to illustrate the excellent control performance of the proposed controller in comparison with the existing method.

Path planning of collision avoidance for unmanned ground vehicles: A nonlinear model predictive control approach

2020 ◽  
pp. 095965182093784
Author(s):  
Peng Hang ◽  
Sunan Huang ◽  
Xinbo Chen ◽  
Kok Kiong Tan
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Predictive Control ◽  
Nonlinear Model Predictive Control ◽  
Unmanned Ground Vehicles ◽  
Lateral Stability ◽  
Ground Vehicles ◽  
Moving Obstacles ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In addition to the safety of collision avoidance, the safety of lateral stability is another critical issue for unmanned ground vehicles in the high-speed condition. This article presents an integrated path planning algorithm for unmanned ground vehicles to address the aforementioned two issues. Since visibility graph method is a very practical and effective path planning algorithm, it is used to plan the global collision avoidance path, which can generate the shortest path across the static obstacles from the start point to the final point. To improve the quality of the planned path and avoid uncertain moving obstacles, nonlinear model predictive control is used to optimize the path and conduct second path planning with the consideration of lateral stability. Considering that the moving trajectories of moving obstacles are uncertain, multivariate Gaussian distribution and polynomial fitting are utilized to predict the moving trajectories of moving obstacles. In the collision avoidance algorithm design, a series of constraints are taken into consideration, including the minimum turning radius, safe distance, control constraint, tracking error, etc. Four simulation conditions are carried out to verify the feasibility and accuracy of the comprehensive collision avoidance algorithm. Simulation results indicate that the algorithm can deal with both static and dynamic collision avoidance, and lateral stability.

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