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Obstacle avoidance method of autonomous vehicle based on fusion improved A*APF algorithm

Qian Yubin, Sun Hongtao, Feng Song

Bulletin of the Polish Academy of Sciences. Technical Sciences

2023

Vol. 71, nr 2

art. no. e144624

This paper proposes an autonomous obstacle avoidance method combining improved A-star (A*) and improved artificial potential field (APF) to solve the planning and tracking problems of autonomous vehicles in a road environment. The A*APF algorithm to perform path planning tasks, and based on the longitudinal braking distance model, a dynamically changing obstacle influence range is designed. When there is no obstacle affecting the controlled vehicle, the improved A* algorithm with angle constraint combined with steering cost can quickly generate the optimal route and reduce turning points. If the controlled vehicle enters the influence domain of obstacle, the improved artificial potential field algorithm will generate lane changing paths and optimize the local optimal locations based on simulated annealing. Pondering the influence of surrounding participants, the four-mode obstacle avoidance process is established, and the corresponding safe distance condition is analyzed. A particular index is introduced to comprehensively evaluate speed, risk warning, and safe distance factors, so the proposed method is designed based on the fuzzy control theory. In the tracking task, a model predictive controller in the light of the kinematics model is devised to make the longitudinal and lateral process of lane changing meet comfort requirements, generating a feasible autonomous lane-change path. Finally, the simulation was performed in the Matlab/Simulink and Carsim combined environment. The proposed fusion path generation algorithm can overcome the shortcomings of the traditional single method and better adapt to the dynamic environment. The feasibility of the obstacle avoidance algorithm is verified in the three-lane simulation scenario to meet safety and comfort requirements.

Decentralized static output tracking control of interconnected and disturbed Takagi–Sugeno systems

Jabri Dalel, Guelton Kevin, Belkhiat Djamel E.C., Manamanni Noureddine

International Journal of Applied Mathematics and Computer Science

2020

Vol. 30, no. 2

225--238

This article describes a new procedure for the design of decentralized output-feedback tracking controllers for a class of interconnected Takagi–Sugeno (TS) fuzzy systems with external bounded disturbances and measurement noise. The main idea consists in transforming the decentralized tracking control problem, by using the descriptor redundancy formulation, to a robust decentralized stabilization one. The non-parallel distributed compensation (non-PDC) controllers proposed here are synthesized to satisfy robust H∞ tracking performance with disturbance attenuation. The decentralized controllers design conditions are given in terms of LMIs via extended quadratic Lyapunov functions. Finally, simulations are presented: two numerical examples are dedicated to compare the conservatism of the proposed approach regarding the previous results available in the literature; then, the effectiveness of the decentralized controller design methodology is illustrated with a closed-loop simulation of two inverted pendulums connected by a spring.