Adaptive backstepping control for ship nonlinear active fin system based on disturbance observer and neural network

<span>Adaptive backstepping control based on disturbance observer and neural network for ship nonlinear active fin system is proposed. One disturbance observer is given to observe the disturbances of the system, by this way, the response time is shorten and the negative impact of disturbance and uncertain elements of the system is reduced. In addition, radial basic function neural network (RBFNN) is proposed to approach the unknown elements in the ship nonlinear active fin system, therefor the system can obtain good roll reduction effectiveness and overcome the uncertainties of the model, the designed controller can maintain the ship roll angle at desired value. Finally, the simulation results are given for a supply vessel to verify the successfulness of the proposed controller.</span>

Command-Filtered Adaptive Neural Network Backstepping Quantized Control for Fractional-order Nonlinear Systems with Asymmetric Actuator Dead-zone via Disturbance Observer

An adaptive neural network (NN) backstepping quantized control based on command filter and disturbance observer is proposed for fractional-order nonlinear systems with asymmetric actuator dead-zone and unknown external disturbance in this paper. An adaptive NN mechanism is designed to estimate unknown functions, and a command filter is introduced to estimate the virtual control variable as well as its derivative, so the ``explosion of complexity" issue can be avoided existed in the classical backstepping method. To handle the unknown external disturbance, a fractional-order disturbance observer is developed. Moreover, a hysteresis-type quantizer is used to quantify the final input signal to overcome the system performance damage caused by the actuator dead-zone. The quantized input signal can ensure that all the involved signals keep bounded and the tracking error converges to an arbitrarily small region of the origin. Finally, two examples are presented to verify the effectiveness of the proposed method.