Adaptive Neural Fault-Tolerant Control of a 3-DOF Model Helicopter System

Abstract

Abstract-In this paper, an adaptive neural fault-tolerant control scheme is proposed for the three degrees of freedom model helicopter, subject to system uncertainties, unknown external disturbances, and actuator faults. To tackle the system uncertainty and the nonlinear actuator fault problems, the neural network disturbance observer is developed based on the radial basis function neural network. The unknown external disturbance and the unknown neural network approximation error are treated as a compound disturbance that is estimated by another nonlinear disturbance observer. A disturbance observer based adaptive neural fault-tolerant control scheme is then developed to track the desired system output in the presence of system uncertainty, external disturbance, and actuator faults. The stability of the whole closed-loop system is analyzed using the Lyapunov method, which guarantees the convergence of all closed-loop signals. Finally, the simulation results are presented to illustrate the effectiveness of the new control design techniques.

Integrated fault tolerant attitude control approach for satellite attitude system with sensor faults

“…It is necessary to cut down the external disturbance's effect to an acceptable level. Many different control schemes including robust control, iterative learning control, variable structure control, adaptive control, and passivity‐based control are proposed for solving the disturbance attenuation problem, and it should be noted that control and sliding mode control are most favored by scientists.…”

“…Recently, an adaptive fractional order sliding mode controller with a neural estimator is proposed in the work of Fei and Lu for a class of linear systems with nonlinear disturbances. Compared with traditional integer order sliding mode controller in other works, the new proposed fractional order sliding mode controller contains a fractional order term in the sliding surface, such that the design control approach have better antidisturbance ability and strong robustness. Motivated by the result obtained in the work of Fei and Lu, a novel integrated FE and FTC approach is presented to a satellite attitude system under sensor faulty case.…”

Adaptive Constrained Control for Uncertain Nonlinear Time-Delay System with Application to Unmanned Helicopter

“…In [9], the neural network was introduced into a class of nonlinear systems with unknown coefficient matrices. Combining RBFNN (radial basis function neural network) and disturbance observer, fault tolerant control method was presented to deal with input saturated system with actuator faults in [10]. Moreover, the disturbance observer is a valid method to deal with external disturbance [11].…”

Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

“…Thus, it is necessary to develop the robust control scheme to handle the unknown disturbance [31]. To fully utilize the dynamic information of the unknown external disturbance, the disturbance observer can be employed to design the robust output control scheme for the robot manipulator [32][33][34]. Recently, many disturbance observers have been designed to compensate for the disturbance effect.…”