Fuzzy Backstepping Sliding Mode Control Research Articles

Speed Control of Switched Reluctance Motor using Adaptive Fuzzy Backstepping Sliding Mode Control

Speed Control of Switched Reluctance Motor using Adaptive Fuzzy Backstepping Sliding Mode Control

Optimization of wind energy extraction for variable speed wind turbines using fuzzy backstepping sliding mode control based on multi objective PSO

This study addresses the problem of designing a nonlinear feedback control strategy for horizontal axis variable speed wind turbines in the below-rated wind speed operating region (whether the wind turbine is offshore or onshore). The objective is to operate the wind turbines to maximum wind energy extraction while reducing the mechanical load. To overcome both issues, a robust nonlinear control strategy based on sliding mode control (SMC) is proposed which tries to seek for an improved performance. The proposed controller has been developed to compensate for negative consequences of external disturbances, measurement noises and unmodeled dynamics. This control strategy exploits a tracking controller that keeps an optimal value for the ratio between the rotor angular speed and the wind speed. For maximum wind energy extraction, the control algorithm employs the sliding mode state output feedback torque controller to provide robustness, combined with backstepping scheme to ensure better performance in the presence of matched and mismatched uncertainties. Next, a fuzzy logic system (FLS) approach is introduced to the backstepping sliding mode controller (BSMC) to achieve better mechanical loads prevention suffered by the transmission shaft by adjusting the parameters of the controller. Finally, multi-objective particle swarm optimization (MOPSO) algorithm is used to find the optimal values for the adjustable parameters of the proposed fuzzy BSMC (FBSMC). To validate the proposed control structure, FAST aeroelastic simulator is used. The obtained results illustrate that the presented control scheme has satisfactory performance.

A new approach in cancer treatment regimen using adaptive fuzzy back-stepping sliding mode control and tumor-immunity fractional order model

Cancer is one of the leading factors of human mortality. The main goal of this article is to present and control a tumor treatment immunity. It can adaptively benefit from the advantages of back-stepping control, the sliding mode control, fuzzy control, and parameter estimation. The cancerous tumor proposed model is a Multi-Input Multi-Output (MIMO) nonlinear fractional-order model. A new back-stepping model based on the sliding mode controller is designed in this paper to deal with the convergence velocity and achieve a robust controller. A new combined Back-Stepping controller with the approach of sliding mode has been designed to solve the convergence velocity challenge, and to face the ordinary back-stepping robustness issue of the controller. Since nonlinear expressions are considered in an indefinite model, a fuzzy controller has been applied to model them. The parameters are estimated using the least-squares method to solve the challenge of uncertainty in parameters. The Back-Stepping model, combined with the sliding mode, has benefited from the advantage of a sliding mode controller, namely, its robustness against uncertainties. The simulation results have demonstrated that the proposed controller has led tumor cells to zero with a higher velocity compared to the integer-order model controller and the adaptive fuzzy conventional Back-Stepping controller.

Adaptive Fuzzy Backstepping Sliding Mode Control for a 3-DOF Hydraulic Manipulator with Nonlinear Disturbance Observer for Large Payload Variation

The paper proposes an adaptive fuzzy position control for a 3-DOF hydraulic manipulator with large payload variation. The hydraulic manipulator uses electrohydraulic actuators as primary torque generators to enhance carrying payload of the manipulator. The proposed control combines backstepping sliding mode control, fuzzy logic system (FLS), and a nonlinear disturbance observer. The backstepping sliding mode control includes a sliding mode control for manipulator dynamics and a PI control for actuator dynamics. The fuzzy logic system is utilized to adjust the control gain and robust gain of the sliding mode control (SMC) based on the output of the nonlinear disturbance observer to compensate the payload. The Lyapunov approach and backstepping technique are used to prove the stability and robustness of the whole system. Some simulations are implemented, and the results are compared to other controllers to exhibit the effectiveness of the proposed control.

Three-Dimensional Path Following of an Underactuated AUV Based on Fuzzy Backstepping Sliding Mode Control

This paper addresses the problem of three-dimensional (3D) path following control for underactuated autonomous underwater vehicles in the presence of parameter uncertainties and external disturbances. Firstly, 3D path following error model was established based on virtual guidance method. Then, an adaptive robust control system was proposed using backstepping and sliding mode control, and we adopt fuzzy logic theory to approximate unknown nonlinear function to solve the problems of nonlinearity, uncertainties and external disturbances in the path following. System stability was proved by Lyapunov stable theory. Finally, simulations were conducted and the results showed that the controller is of excellent adaptability and robustness in the presence of parameter uncertainties and external disturbances.

An innovative fuzzy backstepping sliding mode controller for a Tri-Rotor Unmanned Aerial Vehicle

The dynamical model of a Tri-Rotor Unmanned Aerial Vehicle (UAV) is presented in this paper. The Tri-Rotor has three rotors with two fixed-pitch propellers and a tiltable propeller to control the yaw displacement. The model is obtained via the Newton–Euler approach and a nonlinear control strategy called fuzzy backstepping sliding mode control is proposed for the attitude stabilization and altitude tracking of the vehicle. The designed controller consists of a backstepping sliding mode controller and a fuzzy logic controller. For the problem of determining the backstepping sliding mode control coefficients, an optimization method of gradient descent algorithm has been used. However, the control precision of the backstepping sliding mode is intimately dependent on the precision of coefficients. Besides, the uncertain unmodeled coefficients as well as the characteristics of the complex electromechanical system could cause the coefficients not be invariable. Therefore, a fuzzy logic controller is proposed to compensate the coefficients uncertainty to improve the robustness. The effectiveness of the proposed control algorithm is demonstrated via certain simulation results based on the actual parameters of UAV, and its advantages are indicated in comparison with the backstepping sliding mode control without fuzzy logic control.

Design of adaptive fuzzy backstepping sliding mode control for MIMO uncertain discrete-time nonlinear systems based on noisy measurements

This paper presents an adaptive fuzzy backstepping sliding mode control for multi-input and multi-output uncertain nonlinear systems in semi-strict feedback form. The systems are described by a discrete-time state equation with uncertainties viewed as the modeling errors and the unknown external disturbances, and the observation of the states is taken with independent measurement noises. Combining the adaptive fuzzy backstepping control with the sliding mode control approach for the comprehensive improvement in the stability and the robustness, the adaptive fuzzy backstepping sliding mode control is approximately designed where the design parameters are selected using an appropriate Lyapunov function. The uncertainities are approximated as fuzzy logic systems using the fuzzy inference approach based on the extended single input rule modules to reduce the number of the fuzzy IF-THEN rules. The estimates for the un-measurable states and the adjustable parameters are taken by the proposed simplified weighted least squares estimator. It is proved that the trajectory of the tracking error and the sliding surface is uniformly ultimately bounded. The effectiveness of the proposed approach is indicated through the simulation experiment of a simple numerical system.

Path following of an Underactuated AUV Based on Fuzzy Backstepping Sliding Mode Control

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.

Fuzzy Backstepping Sliding Mode Control for Mismatched Uncertain System

Fuzzy Backstepping Sliding Mode Control for Mismatched Uncertain System

Adaptive fuzzy backstepping sliding mode control for MEMS gyroscope

Adaptive fuzzy backstepping sliding mode control for MEMS gyroscope