Fuzzy Sliding Mode Controller Design Research Articles

An Adaptive Fuzzy Sliding Mode Control Design For Multiuse Grid Interconnected Inverter to intensify power quality in microgrid

: This paper presents a vigorous control design and a robust controller for a Multifunctional grid interconnected inverter [MFGII] beneath disturbed load conditions. This MFGII controller algorithm uses DQ theory to assess the unacceptable parts of grid current such as harmonics, and required load reactive current. This decoupled method of control design makes normal Grid interconnected inverter to MFGII and also helps in reducing the computational burden which further makes the system more robust. Furthermore, Adaptive Fuzzy sliding mode control (AFSMC) algorithm prepares the system sturdy and effective in improving the dynamic performance during uncertainties. Henceforward, settling time and overshoot are reduced with fast dynamic response. The MFGII infuses the RES to grid at PCC which in addition to Real power injection also provides reactive power compensation, balance the load and mitigate harmonics. The results obtained from FOSMC are compared with AFSMC under the variation of solar irradiation and load.

Fuzzy sliding mode control design for the stabilization of wind power generation system with permanent magnet synchronous generator

In order to control the influence of wind power generation incorporated into the power grid and keep the original power grid stable, this paper investigates the Takagi–Sugeno fuzzy model and the nonlinear switched system for permanent magnet synchronous generator in wind power generation system. By introducing fuzzy sliding mode control method, the stability of power system can be guaranteed. To do this, the integral sliding mode surface and fuzzy sliding mode control law are designed to reduce the influence of nonlinear disturbance on power system. In addition, the appropriate Lyapunov function is selected for derivation and proof. At the same time, the gain matrix is solved by linear matrix inequalities, which makes the model globally asymptotically stable. Finally, the stability of the system model is verified by simulation results.

Adaptive Fuzzy Sliding Mode Control of Omnidirectional Mobile Robots with Prescribed Performance

Adaptive fuzzy sliding-mode control design for omnidirectional mobile robots with prescribed performance is presented in this work. First, an error transformation which transforms the constrained variable into an unconstrained one is carried out. Next, a fuzzy logic system (FLS) for approximating the unknown dynamics is constructed. Based on such a model, a nominal adaptive linearizing controller incorporating a serial-parallel model (SPM)-based composite algorithm, which improves the tracking performance of the overall closed-loop system, is synthesized. To solve the so-called “loss of controllability” problem, a smooth-switching algorithm is embedded which hands over the control authority to an auxiliary sliding-mode controller until the danger is safely bypassed. The proposed design ensures the semi-globally uniformly ultimately bounded stability of the closed-loop signals. Simulation works demonstrating the validity of the proposed design are presented in the final.

Adaptive fuzzy sliding mode controller design for PMLSM position control

We focus a modern methodology in this paper for adding the fuzzy logic control as well as sliding model control. This combination can enhance the MLS position control robustness and enhanced performance of it.In the start, for an application in an area to control the loops placement and position for the synchronous motor what has permanent magnetic linearity we tend to control the fuzzy sliding mode control. To resolve the chattering issues a designed controller is investigated and, in this way, steady state motion in sliding with higher accuracy is obtained. In this case, method of online tuning with the help of fuzzy logic is used in order to adjust the thickness of boundary layer and switching gains.For the suggested scheme technique, the outcomes of simulation suggest that with the classical SMC the accurate state and good dynamic performance is compared due to force chattering resistance, response by quick dynamic force and external disturbance elements and robustness against them.

Fuzzy Sliding Mode Controller Design and Analysis of an SQEIAR Epidemic Model for COVID-19 to Determine the Quarantine Rate

Fuzzy Sliding Mode Controller Design and Analysis of an SQEIAR Epidemic Model for COVID-19 to Determine the Quarantine Rate

Single dimension-based fuzzy sliding mode control design for the stabilisation of underactuated unmanned underwater vehicle

Single dimension-based fuzzy sliding mode control design for the stabilisation of underactuated unmanned underwater vehicle

Single dimension based fuzzy sliding mode control design for the stabilisation of underactuated unmanned underwater vehicle

Single dimension based fuzzy sliding mode control design for the stabilisation of underactuated unmanned underwater vehicle

Fuzzy Non-singular Terminal Sliding Mode Controller Design for Nonlinear Systems with Input Saturation

The current work has proposed an approach to the controller design of a fuzzy non-singular terminal sliding mode (NTSM) for a type of planar systems with input saturation. On the basis of a modified version of NTSM, a category of saturated NTSM controller is first constructed to ensure that the states can reach the sliding surface and finite-time converge to the origin. On this basis, a fuzzy logic controller including two fuzzy input variables and a fuzzy output variable is developed to adaptively adjust the control gain such that the gain of the NTSM controller can be automatically minimized. This also implies that the chattering phenomenon encountered by most conventional sliding mode control (SMC) schemes can be significantly attenuated without sacrificing inherent properties. Finally, in comparison with a traditional SMC method, the superiority of the presented algorithm is confirmed by the comparative simulation results in terms of chattering alleviation and robustness.

Interval type-2 adaptive fuzzy sliding mode control design of reentry attitude for reusable launch vehicles

Interval type-2 adaptive fuzzy sliding mode control design of reentry attitude for reusable launch vehicles

Adaptive fuzzy sliding mode control design for vehicle steer-by-wire systems

This paper presents a novel adaptive fuzzy sliding mode (AFSM) control scheme for a vehicle steer-by-wire (SbW) system. Initially, the dynamics of the SbW system are described by a second-order differential equation where the Coulomb friction and the self-aligning torque are treated as external disturbances. Furthermore, an AFSM controller is designed for the SbW system, which utilizes an adaptive law to estimate both the Coulomb friction and the self-aligning torque, a sliding mode control component to deal with the parametric uncertainties and unmodeled dynamics, and a fuzzy strategy to strike a good balance between the chattering-alleviation and the tracking precision. The stability of the control system is verified in the sense of Lyapunov, and the selection of control parameters is provided in detail. Lastly, experiments are carried out under various road conditions. The experimental results demonstrate that the developed AFSM controller possesses superiority in terms of higher tracking accuracy, stronger robustness and a better balance between the control precision and smoothness in comparison with a conventional sliding mode (CSM) controller and a boundary layer-based adaptive sliding mode (BLASM) controller.

Fuzzy sliding mode control of a wearable rehabilitation robot for wrist and finger

PurposeThe purpose of this paper is to introduce a new design for a finger and wrist rehabilitation robot. Furthermore, a fuzzy sliding mode controller has been designed to control the system.Design/methodology/approachFollowing an introduction regarding the hand rehabilitation, this paper discusses the conceptual and detailed design of a novel wrist and finger rehabilitation robot. The robot provides the possibility of rehabilitating each phalanx individually which is very important in the finger rehabilitation process. Moreover, due to the model uncertainties, disturbances and chattering in the system, a fuzzy sliding mode controller design method is proposed for the robot.FindingsWith the novel design for moving the DOFs of the system, the rehabilitation for the wrist and all phalanges of fingers is done with only two actuators which are combined in one device. These features make the system a good choice for home rehabilitation. To control the robot, a fuzzy sliding mode controller has been designed for the system. The fuzzy controller does not affect the coefficient of the sliding mode controller and uses the overall error of the system to make a control signal. Thus, the dependence of the controller to the model decreases and the system is more robust. The stability of the system is proved by the Lyapunov theorem.Originality/valueThe paper provides a novel design of a hand rehabilitation robot and a controller which is used to compensate the effects of the uncertain parameters and chattering phenomenon.

A new fuzzy sliding mode controller design for delta operator time-delay nonlinear systems

ABSTRACTThis paper investigates the sliding mode control (SMC) problem for a class of delta operator uncertain time-delay nonlinear systems through Takagi–Sugeno fuzzy models. Some new sufficient conditions for asymptotic stability analysis of the sliding motion are obtained in terms of linear matrix inequalities with some convexification techniques. Then two new dynamic SMC design methods are synthesised to force the resulting closed-loop system states onto the sliding surface in finite time. Two simulation examples are finally given to illustrate the effectiveness of the proposed approaches.

Fuzzy sliding mode control design based on stability margins

Fuzzy Sliding Mode Control (FSMC) algorithms have been widely studied and implemented to combine the robustness of the classical sliding mode control with lower chattering levels, but industrial implementation requires a robustness measurement such as the stability margins. Due to the significance of stability margins in control systems, the computation of the phase Margin (PM) and gain margin (GM) in FSMC has already been proposed with the self-sustained oscillations considered as an unstable behavior. However, a procedure to obtain the desired PM and GM from the FSMC design itself has not been developed yet. Hence, in this study, a method to design FSMC algorithms with desired PM and GM is presented. The describing function (DF) and harmonic balance (HB) techniques were used to identify the limit cycles; then, a step-by-step process to tune the FSMC parameters was provided. Examples and simulations are presented to validate the proposed method.

Fuzzy Sliding Mode Controller Design for a Cooperative Robotic System With Uncertainty for Handling an Object

This paper proposes a control framework for a cooperative robotic system to grasp and handle an object with known geometry in the presence of uncertainty in robot dynamics. Based on passive decomposition approach, dynamic equations of the cooperative robotic system are decomposed into two decoupled systems, shape and locked systems. The locked system and the shape system are controlled by two fuzzy sliding mode controllers (SMCs). Stability is studied through passivity property and Lyapunov theorem. Simulation results confirm that the proposed control scheme works well.

Fuzzy sliding mode control design of Markovian jump systems with time-varying delay

This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.

Adaptive TSK fuzzy sliding mode control design for switched reluctance motor DTC drive systems with torque sensorless strategy

This study proposes a novel Adaptive Takagi-Sugeno-Kang (TSK) Fuzzy Sliding Mode controller (abbreviated as AFSC) and investigates the application for a switched reluctance motor (SRM) direct torque control (DTC) drive system without a torque sensor. The sliding mode controller (SMC) is used for reducing the influence of uncertainties and external disturbances, and it performs fast responses. The parameters of the adaptive TSK fuzzy controller (AFC) are adjusted online for further reducing error residues after applying the SMC. Lyapunov stability theory is used for deriving the stability condition of the SMC and the adaptive update law of the AFC. The stability of the overall closed-loop system is also analyzed. To verify the performance and practicality of the controller developed for this study, the AFSC is employed as the speed controller in a SRM DTC drive system. The experimental results reveal that the steady-state speed error is maintained between ±2 rpm when the motor load torque is 1 Nm, and the motor operates at low, medium, high, and variable speeds. Comparing with the conventional SMC, a faster and smoother speed and torque responses are achieved. Moreover, the proposed control strategy is superior to the conventional SMC with respect to robustness for external disturbances.

Fuzzy sliding mode controller design for semi-active seat suspension with neuro-inverse dynamics approximation for MR damper

To improve the ride comfort of car, this paper proposed a semi-active seat suspension with magneto-rheological (MR) damper and designed a new fuzzy sliding mode controller with expansion factor (FSMCEF) based on the neuro-inverse dynamics approximation of the MR damper. This FSMCEF combines the advantages of both sliding mode controller (SMC) and fuzzy controller (FC) with expansion factor (EF), and it takes an ideal skyhook model as the reference, and creates a sliding mode control law based on the errors dynamics between the seat suspension and its reference model. Further fuzzy rules are used to suppress the chattering occurred in the above sliding mode control by fuzzifying the sliding mode surface and its derivative. Moreover, in order to compute the required control current for MR damper after solving the desired control force using FSMCEF, this paper presented a BP algorithm based neural network inverse model, located between the FSMCEF and the MR damper, taking the displacement, velocity of the MR damper and the desired control force output by FSMCEF as its input, and predicting the control current required to input MR damper. The predicting error and stability of the neural network inverse model for MR is investigated by sample testing. In addition, the stability analysis of FSMCEF is also completed by under nominal system and non-nominal system with parameter uncertainty and external disturbance. The results of numerical simulations show that the vibration reduction effect of the semi-active seat is obviously improved using FSMCEF compared with using PID controller and SMC.

Application of direct adaptive fuzzy slidingmode control into a class of non-affine discrete nonlinear systems

Direct adaptive fuzzy sliding mode control design for discrete non-affine nonlinear systems is presented for trajectory tracking problems with disturbance. To obtain adaptiveness and eliminate chattering of sliding mode control, a dynamic fuzzy logical system is used to implement an equivalent control, in which the parameters are self-tuned online. Stability of the sliding mode control is validated using the Lyapunov analysis theory. The overall system is adaptive, asymptotically stable, and chattering-free. A numerical simulation and an application to a robotic arm with two degrees of freedom further verify the good performance of the control design.

Quantized feedback fuzzy sliding mode control design via memory-based strategy

This paper is concerned with the sliding mode control (SMC) design for a class of Takagi–Sugeno (T–S) fuzzy nonlinear systems subject to model uncertainties and input quantization mismatch. A novel memory-based sliding surface is presented which includes not only the current states but also the past state information of the systems. Sufficient conditions for the design of the switching gains are given via linear matrix inequality(LMI) technique, and then the reaching conditions of the sliding surface is constructed to ensure the reachability of the sliding manifold. Furthermore, an adaptive neuro-fuzzy inference system(ANFIS) is introduced for reducing the high-frequency chattering induced by the signum function term in the sliding mode control. The effectiveness of the proposed methodology is illustrated by Matlab simulations.

Exponential function based fuzzy sliding mode control of uncertain nonlinear systems

In this paper, exponential function based fuzzy sliding-mode control design for uncertain nonlinear systems is proposed. The fuzzy sliding mode control was successful in robust performance once the system is in sliding phase. However during reaching phase the system is vulnerable to external disturbances and perturbations. The proposed controller is designed by considering the crisp sliding surface as input, defining the output membership functions on universe of control with exponential function based gain. The rule base of the controller is designed based on sliding mode control law. The exponential function will dynamically adapts the variation of the controlled system. The designed controller will improve the performance of the system during reaching phase. The performance of the proposed controller is tested on uncertain nonlinear systems by simulation and validated by experimentation results.