Adaptive Fractional Sliding Mode Control Research Articles

Performance-guaranteed fractional-order sliding mode control for underactuated autonomous underwater vehicle trajectory tracking with a disturbance observer

This paper proposes a fractional-order sliding mode control method for an underactuated autonomous underwater vehicle (AUV) with random disturbances. First, a new fractional-order sliding mode disturbance observer (FOSMDO) is designed to estimate the random disturbance and unknown AUV’s model based on adaptive and fixed time . A strategy based on adaptive fractional sliding mode control is designed for motion control, and a line-of-sight guidance law with time-varying look-ahead distance is applied to achieve path following. Then, a new fractional-order sliding model controller is designed by constructing a fractional-order mode surface and proposing a prescribed performance function to ensure the control performance. The closed-loop stability is proved and analyzed, and the effectiveness and robustness of the controller are demonstrated by numeric simulations.

Bridge-Ship Collision Avoidance Control Based on AFSMC with a FRNN Estimator

For collision avoidance and maneuvering control in bridge areas, an adaptive fractional sliding mode control with fractional recurrent neural network (FRNN-AFSMC) is proposed. The uncertainties are estimated by FRNN, and the fractional gradient is adopted to improve the recurrent neural network (RNN). Its convergence has been proven. The influence of fractional order on algorithm performance is analyzed, and the simulation platform of ship collision avoidance control is built. Dynamic collision avoidance of multiple ships is simulated and verified. The results show the feasibility and effectiveness of dynamic autonomous collision avoidance motion control in a dynamic ocean environment.

A new adaptive fractional sliding mode control of a MEMS gyroscope

The Micro-Electro-Mechanical System (MEMS) gyroscope is a well-known device, which has been widely used in medicine due to its small size. In this study, a new adaptive fractional integral sliding mode controller is proposed for control of a MEMS gyroscope. The goal is to achieve an appropriate control method that includes high tracking performance and robustness against external disturbances. The fractional order integral sliding mode controller gains will be updated by a new adaptive law. The effectiveness of the proposed controller is validated by simulation results. Results show that the adaptive fractional integral sliding mode control controller successfully tracked the desired trajectory in comparison with the fractional integral sliding mode control method. The Lyapunov theory is used in order to show that the adaptive fractional integral sliding mode control is stable.

Dynamic Analysis and Adaptive Sliding Mode Controller for a Chaotic Fractional Incommensurate Order Financial System

In this study, the dynamic behavior and chaos control of a chaotic fractional incommensurate-order financial system are investigated. Using well-known tools of nonlinear theory, i.e. Lyapunov exponents, phase diagrams and bifurcation diagrams, we observe some interesting phenomena, e.g. antimonotonicity, crisis phenomena and route to chaos through a period doubling sequence. Adopting largest Lyapunov exponent criteria, we find that the system yields chaos at the lowest order of [Formula: see text]. Next, in order to globally stabilize the chaotic fractional incommensurate order financial system with uncertain dynamics, an adaptive fractional sliding mode controller is designed. Numerical simulations are used to demonstrate the effectiveness of the proposed control method.

Adaptive Fractional Sliding Mode Control of Active Power Filter Based on Dual RBF Neural Networks

This paper presents an adaptive fractional sliding mode control scheme based on dual radial basis function (RBF) neural networks (NNs) to enhance the performance of a three-phase shunt active power filter (APF), where a conventional integer-order sliding surface is changed into a fractional-order one to speed up the system response and optimize the control performance. Furthermore, the control scheme adopts a class of dual RBF NNs, in which the network weights can be updated online to approximate the nonlinear system functions and the upper bound of estimated disturbances, respectively, improving the system stability and robustness. Meanwhile, the adaptive control laws obtained by Lyapunov analysis can guarantee the system a stable operation. Finally, by comparing with the integer-order control strategy, the simulation results verify that this proposed controller has a better performance in the suppression of the harmonic, elimination of system uncertainties, and the reduction of current tracking error.