An adaptive fractional-order nonsingular terminal sliding mode controller for a microgyroscope is presented with uncertainties and external disturbances using a fuzzy neural network compensator based on a backstepping technique. First, the dynamic of the microgyroscope is transformed into an analogical cascade system to guarantee the application of a backstepping design. Then, a fractional-order nonsingular terminal sliding mode surface is designed which provides an additional degree of freedom, higher precision, and finite convergence without a singularity problem. The proposed control scheme requires no prior knowledge of the unknown dynamics of the microgyroscope system since the fuzzy neural network is utilized to approximate the upper bound of the lumped uncertainties and adaptive algorithms are derived to allow online adjustment of the unknown system parameters. The chattering phenomenon can be reduced simultaneously by the fuzzy neural network compensator. The stability and finite time convergence of the system can be established by the Lyapunov stability theorem. Finally, simulation results verify the effectiveness of the proposed controller and the comparison of root mean square error between different fractional orders and integer order is given to signify the high precision tracking performance of the proposed control scheme.

This paper addresses the path following problem of an underactuated autonomous underwater vehicle (AUV) with the aim of dealing with parameter uncertainties and current disturbances. An adaptive robust control system was proposed by employing fuzzy logic, backstepping and sliding mode control theory. Fuzzy logic theory is adopted to approximate unknown system function, and the controller was designed by combining sliding mode control with backstepping thought. Firstly, the longitudinal speed was controlled, then the yaw angle was made as input of path following error to design the calm function and the change rate of path parameters. The controller stability was proved by Lyapunov stable theory. Simulation and outfield tests were conducted and the results showed that the controller is of excellent adaptability and robustness in the presence of parameter uncertainties and external disturbances. It is also shown to be able to avoid the chattering of AUV actuators.

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This paper presents a novel swarm control framework for path following of multiple underactuated unmanned marine vehicles (UMVs) with uncertain dynamics and unmeasured velocities. Main contributions are as follows: (1) unlike previous master-slave formation control, a swarm system function with distributed and self-organized capability is designed; (2) a center-of-swarm (COS) guidance scheme without vehicle number constraints is proposed for swarm path following, where an improved artificial potential field (APF) using ring-shaped repulsion is further employed for collision avoidance and obstacle avoidance; (3) a nonlinear velocity observer is incorporated into the proposed swarm control framework to estimate the unmeasured velocities, thereby contributing to robust controllers based on fuzzy sliding mode against uncertain dynamics and time-varying disturbances. Simulations are carried out to illustrate the universal applicability and effectiveness of the proposed swarm control framework. INDEX TERMS Unmanned marine vehicles, swarm control, velocity observer, center-of-swarm guidance, fuzzy sliding mode.