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LQR Control and Optimization for Trajectory Tracking of Biomimetic Robotic Fish Based on Unreal Engine
oleh: Ming Wang, Kunlun Wang, Qianchuan Zhao, Xuehan Zheng, He Gao, Junzhi Yu
Format: | Article |
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Diterbitkan: | MDPI AG 2023-06-01 |
Deskripsi
A realistic and visible dynamic simulation platform can significantly facilitate research on underwater robots. This paper uses the Unreal Engine to generate a scene that resembles real ocean environments, before building a visual dynamic simulation platform in conjunction with the Air-Sim system. On this basis, the trajectory tracking of a biomimetic robotic fish is simulated and assessed. More specifically, we propose a particle swarm optimization algorithm-based control strategy to optimize the discrete linear quadratic regulator controller for the trajectory tracking problem, as well as tracking and controlling discrete trajectories with misaligned time series through introducing a dynamic time warping algorithm. Simulation analyses of the biomimetic robotic fish following a straight line, a circular curve without mutation, and a four-leaf clover curve with mutation are carried out. The obtained results verify the feasibility and effectiveness of the proposed control strategy.