The projection synchronization issue of complex Lü chaotic systems is examined in this work. Firstly, the system is presented, the complex chaotic system is transformed into the equivalent real number system, on this basis, the existence of the projection synchronization problem is proved and solution is obtained by an algorithm. Secondly, combines feedback controller and uncertainty and disturbance estimator (UDE), where one is used to implement the projection synchronization of nominal complex chaotic systems and the UDE controller is used to remove uncertainty and disturbance. Finally, the validity of the proposed results is proved by numerical simulation.
This paper introduces the working principle of the underwater spherical detection robot BYSQ-3. Through the known kinematics and dynamic models of the underwater spherical robot, using the combination of dynamic feedback gain control and UDE control, several designs are designed. The simple physical controller realizes the stabilization control of the system, and ensures that the whole system can achieve global asymptotic stability quickly. It is simpler and simpler than the traditional nonlinear control method, and the simulation results show that the correctness and effectiveness of the theory are verified.
This paper mainly studies the partial anti-synchronization of laser hyperchaos system. First, transform complex systems into real systems. Secondly, in order to realize the full synchronization and partial anti synchronization of the system, the dynamic gain feedback control method and the dynamic feedback method based on uncertainty and disturbance estimator (UDE) are used to design simple and physically feasible controllers respectively. Finally, through MATLAB numerical simulation, it is proved that the error system is asymptotically stable, and the master-slave system realizes partial anti synchronization.
In order to ensure that mobile robots perform various tasks correctly, the research on efficient and practical path planning algorithms is of great significance. For the Artificial Potential Field algorithm, it is easy to fall into local minimums, the target points are unreachable, and the A* algorithm search time is long when planning the moving path. The speed is slow, the planned path is not smooth enough and it is not the optimal path. This paper proposes a mobile robot combined path planning algorithm based on the APF algorithm and the A* algorithm. This algorithm can solve the local oscillation problem while reducing the problem. Obstacle avoidance time, improve the efficiency of the navigation algorithm. From the results of MATLAB Simulation, it can be seen that the algorithm can complete path planning accurately and efficiently. The mobile robot can bypass the local minimum point and successfully reach the target point, achieving the expected path planning effect.
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