Type-2 Fuzzy Sliding Mode Control Research Articles

Interval type-2 fuzzy sliding mode control for a cable-driven parallel robot with elastic cables using metaheuristic optimization methods

In this paper, a supervisory interval type-2 fuzzy adaptive sliding mode control scheme is addressed for cable robots. In the proposed control scheme, intelligent methods are combined with conventional sliding mode control to achieve optimal adjustment of control parameters. This approach ensures accurate tracking performance, despite the structural constraints of cable robots. These constraints include the production of purely tensile forces and the effects due to inherent elasticity, which will make the design of the controller challenging. For this purpose, the internal force concept is utilized to ensure the tension style of cables. Additionally, considering a compensator part in the proposed controller and applying the singular perturbation theorem, the vibration effects of elastic cables are handled, and stability is proved through the second Lyapunov method. Therefore, the desired performance of the control system will be guaranteed for the movements that stimulate the vibration modes of cables. An interval type-2 fuzzy logic controller is proposed to adjust the control gain, effectively reducing the chattering level. Moreover, a supervisory interval type-2 fuzzy logic control system is introduced to regulate the gains within the sliding surface. The Grasshopper Optimization Algorithm is employed to select the optimal parameters for the membership functions of the fuzzy system. The results of the conducted simulations show that the desired tracking performance is provided, despite different uncertain parameters and the structural constraints of the considered cable robot.

Fault tolerant control of two tanks system using gain-scheduled type-2 fuzzy sliding mode controller

To save the robustness of type 2 fuzzy logic control technique and to avoid the high energy consumption that represents the sliding mode control (SMC) technique control technique, without failing the performance of the system, we propose a new fault tolerant control method based on gain-scheduled sliding mode control with interval type 2 fuzzy logic (FTCGST2FSMC) applied to the hydraulic system (two tanks system) with an actuator fault. The proposed control scheme avoids a difficult modeling, due to the chatter effect of the SMC, guarantees the stability studied by Lyapunov with the robustness of the system. The gains of the control with the SMC controller are modified and changed by an adaptation with a technique based on type 2 fuzzy logic, used to improve the gains of the controller when the fault is added, the proposed FTCGST2FSMC controller has been compared with the sliding mode controller. The results obtained confirm the robustness and the performance of this method, in the presence of the actuator fault effect.

Security Interval Type-2 Fuzzy Sliding Mode Control Under Multistrategy Injection Attack: Design, Analysis, and Optimization

In this work, the security sliding mode control problem is considered for interval type-2 (IT2) fuzzy systems, where the sensor-controller channel may be subject to the false data injection attack with multi-strategy attack model. The different attack patterns at each instant is described via a random categorical distribution. It is noted that the injected false data may result in the system state to exceed the modeling domain. In order to cope with the above phenomenon, a reconstruction method of the controller's membership functions is proposed via analyzing the variation range of the attacked state, and then, an IT2 fuzzy sliding mode controller is designed. The explicit relation between the raw state signal and attacked state is established, based on which stability conditions dependent on the regional boundaries of membership functions are obtained for the input-to-state stability in probability of the closed-loop system. Meanwhile, a framework of security performance optimization is established via searching a desirable sliding matrix, which may be solved via the particle swarm optimization algorithm. Furthermore, the proposed security control scheme is extended to the case of imperfectly matched premises, where the controller may have different fuzzy rules from the fuzzy system. Finally, the proposed security control scheme is verified by two simulations examples.

An adaptive type-2 fuzzy sliding mode tracking controller for a robotic manipulator

<abstract> <p>With the wide application of intelligent manufacturing and the development of diversified functions of industrial manipulator, the requirements for the control accuracy and stability of the manipulator servo system are also increasing. The control of industrial manipulator is a time-varying system with nonlinear and strong coupling, which is often affected by uncertain factors, including parameter changing, environmental interference, joint friction and so on. Aiming at the problem of the poor control accuracy of the manipulator. Under the complex disturbance environment, control accuracy of the manipulator will be greatly affected, so this paper proposes an adaptive type-2 fuzzy sliding mode control (AT2FSMC) method applied to the servo control of the industrial manipulator, which realizes the adaptive adjustment of the boundary layer thickness to suppress the trajectory error caused by the external disturbance and weakens the chattering problem of the sliding mode control. The simulation results on a two-axis manipulator indicate that, with the presence of external disturbances, the proposed control method can help the manipulator maintain control signal stability and improve tracking accuracy. It also suppressed chattering produced by sliding mode control (SMC) and strengthening the robustness of the system. Compared with other conventional trajectory tracking control methods, the effectiveness of the proposed method can be reflected. Finally, the proposed method is tested in an actual manipulator to complete a practical trajectory to prove its feasibility.</p> </abstract>

Interval Fuzzy Type-2 Sliding Mode Control Design of Six-DOF Robotic Manipulator

The remarkable features of hybrid SMC assisted with fuzzy systems supplying parameters of the controller have led to significant success of these control approaches, especially in the control of multi-input and multi-output nonlinear systems. The development of type-1 fuzzy systems to type-2 fuzzy systems has improved the performance of fuzzy systems due to the ability to model uncertainties in the expression of expert knowledge. Accordingly, in this paper, the basic approach of designing and implementing the interval type-2 fuzzy sliding mode control was proposed. According to the introduced systematic design procedure, complete optimal design of a type-2 fuzzy system structure was presented in providing sliding mode control parameters by minimizing tracking error and control energy. Based on the proposed method, the need for expert knowledge as the main challenge in designing fuzzy systems was eliminated. In addition, the possibility to limit the control outputs to deal with actuators’ saturation was made available. The control method was implemented on a six-degree-of-freedom robot manipulator that was exposed to severe external disturbances, and its performance was compared to a type-1 fuzzy system as well as to the conventional SMC. The achievements revealed improved performance of the combined control system of fuzzy sliding mode type-2 in comparison with its control counterparts.

Automatic Control of a Mobile Manipulator Robot Based on Type-2 Fuzzy Sliding Mode Technique

In this paper, an automatic control method based on type-2 fuzzy sliding mode control for a mobile arm robot is presented. These types of robots have very complex dynamics due to the uncertainty of the arm parameters and the mobility of their base, so conventional control methods do not provide a suitable solution. The proposed method proves convergence with Lyapunov theory, and its convergence is mathematically guaranteed. A type-2 fuzzy system is responsible for approximating unmodulated dynamics, nonlinear terms, and uncertain parameters. In simulations, the performance of the proposed method with different situations, including uncertainty in arm parameters, uncertainty in mobile robot parameters (arm robot base), uncertainty in load, as well as indeterminacy in modeling have been applied. The comparison with two conventional controllers shows the efficiency and superiority of the proposed method.

Enhancement of the Tracking Performance for Robot Manipulator by Using the Feed-forward Scheme and Reasonable Switching Mechanism

Robot manipulator has become an exciting topic for many researchers during several decades. They have investigated the advanced algorithms such as sliding mode control, neural network, or genetic scheme to implement these developments. However, they lacked the integration of these algorithms to explore many potential expansions. Simultaneously, the complicated system requires a lot of computational costs, which is not always supported. Therefore, this paper presents a novel design of switching mechanisms to control the robot manipulator. This investigation is expected to achieve superior performance by flexibly adjusting various strategies for better selection. The Proportional-Integral-Derivative (PID) scheme is well-known, easy to implement, and ensures rapid computation while it might not have much control effect. The advanced interval type-2 fuzzy sliding mode control properly deals with nonlinear factors and disturbances. Consequently, the PID scheme is switched when the tracking error is less than the threshold or is far from the target. Otherwise, the interval type-2 fuzzy sliding mode control scheme is activated to cope with unknown factors. The main contributions of this paper are (i) the recommendation of a suitable switching mechanism to drive the robot manipulator, (ii) the successful integration of the interval type-2 fuzzy sliding mode control to track the desired trajectory, and (iii) the launching of several tests to validate the proposed controller with robot model. From these achievements, it would be stated that the proposed approach is effective in tracking performance, robust in disturbance-rejection, and feasible in practical implementation.

Blockchain based optimal decision making of dispatchable units in smart grids considering the high uncertainty effects

Using blockchain technology (BCT) in securing data has received a lot of attention these days. This technology is used not only as a new way with the aim of enhancing the cyber and physical security of power systems, but also has been applied to enhance the exchanged information between units. When Fuel Cell (FC), photovoltaic cells (PV) and wind turbines (WT) are used as sources of distributed generation (DG), there will be a situation called Islanding Micro-Grid (MG), so that this situation has the ability to control voltage, frequency and current of the system with no dependence on the utility. Hence, for overcoming load variations and disturbances, designing and implementing a robust controller is vital. Accordingly, a robust General Type-2 Fuzzy sliding mode controller (GT2FSMC) on the basis of gray wolf optimization algorithm is presented in the following study with the purpose of enhancing the power sharing amongst the distributed generations operating in the off-grid MG. The offered controller, in addition to warrant the stability and robust versus uncertainties of the lumped generated via extrinsic disturbances and un-modelled dynamics, has the ability to significantly decrease the control chattering inherent in primary sliding mode control. In the following paper, it is assumed that there are two distributed generations, each with specific duties. One has the duty of regulating the frequency and voltage through a reference signal, and another is responsible for working in load current control mode with the aim of sharing load correctly among each of them. For stopping malicious attacks, an assured policy framework according to the blockchain (BC) has been created to enhance the security of interchanged data among production units. Plus, two low-voltage parallel DG units exist in the MG. With the aim of evaluating the mentioned way, the simulation results have been done via MATLAB environment. According to the outcomes, it can be concluded that this mentioned controller has the ability of providing lower steady state error and Total Harmonic Distortion (THD) with faster response in comparison to the further controllers that generally are used. The simulation results show that the DG unit operations within the islanding MG have the ability of coordinating successfully under that mentioned control system with the aim of confirming stable operation of the throughout MG.

Adaptive type-2 fuzzy sliding mode control of steer-by-wire systems with event-triggered communication

The steering-by-wire (SbW) system is one of the main subsystems of automatic vehicles, realizing the steering control of autonomous vehicles. This paper proposes an event-triggered adaptive sliding mode control for the SbW system subject to the uncertain nonlinearity, time-varying disturbance, and limited communication resources. Firstly, an event-triggered nested adaptive sliding mode control is proposed for SbW systems. The uncertain nonlinearity is approximated by the interval type-2 fuzzy logic system (IT2 FLS). The time-varying disturbance, modeling error, and event-triggering error can be offset by robust terms of sliding mode control. The key advantage is that the high-frequency switching of sliding mode control only appears on the time derivate of control input without increasing the input-output relative degree of closed-loop SbW systems, such that the chattering phenomenon can be eliminated. Finally, theoretical analysis shows that the practical finite-time stability of the closed-loop SbW system can be achieved, and communication resources in the controller-to-actuator channels can be saved while avoiding the Zeno-behavior. Numerical simulations and experiments are given to evaluate the effectiveness of the proposed method.

Robust Model-Free Adaptive Interval Type-2 Fuzzy Sliding Mode Control for PEMFC System Using Disturbance Observer

This paper proposes a novel robust model-free adaptive interval type-2 fuzzy sliding mode control (MF-AIT2FSMC) for the proton exchange membrane fuel cell (PEMFC) system using nonlinear disturbance observer. The main control objective is to adjust the oxygen stoichiometry at its reference trajectory under load disturbances and parameter uncertainties, to avert the oxygen starvation problem and to obtain maximum net power. The referred MF-AIT2FSMC control strategy is composed of three parts: first, a nonlinear disturbance observer is proposed to estimate both oxygen and nitrogen partial pressures which are considered as unmeasurable variables. Second, a nonlinear disturbance observer-based intelligent proportional-integral (NDBO-iPI) control is derived, whereas the NDBO is used to estimate the unmodeled system dynamics via the knowledge of input and output signals. Third, adaptive interval type-2 fuzzy nonsingular fast terminal sliding mode control is inserted to NDBO-iPI control to compensate the NDBO estimation error, enhance the control performance and ensure the global controlled system stability. Furthermore, the entire controlled system stability is verified via the Lyapunov approach. Finally, the corresponding numerical simulation on the PEMFC system is obtained to demonstrate the effectiveness and efficiency of the proposed MF-AIT2FSMC technique by comparing with the NDBO-iPI and standard PID controller.

General type-2 fuzzy sliding mode control for motion balance adjusting of power-line inspection robot

In this paper, a novel general type-2 fuzzy sliding mode controller for motion balance adjusting of a power-line inspection robot is developed. The combination method between general type-2 fuzzy system and sliding mode control is different from the existing works. In this paper, sliding mode control is used to finish the motion balance adjusting work. The sliding mode surface is designed according to the Ackermann’s formula. And the general type-2 fuzzy system is used to strengthen the anti-interference ability of the power-line inspection robot. The general type-2 fuzzy sliding mode controller is developed by substituting an element of the sliding mode control law by the output of general type-2 fuzzy system. The novel combination method makes it possible to enhance the anti-interference ability of PLI robot while achieving motion balance control. According to the simulation results, the effectiveness of the proposed controller is proved. And it can also be known that the proposed method is not limited to the GT2FS, and its IT2FS and T1FS counterpart can also strengthen the anti-interference ability in different level.

Observer based adaptive interval type-2 fuzzy sliding mode control for unknown nonlinear systems

Observer based adaptive interval type-2 fuzzy sliding mode control for unknown nonlinear systems

Backstepping Sliding Mode Controller Improved with Interval Type-2 Fuzzy Logic Applied to the Dual Star Induction Motor

This paper proposes Interval type-2 Fuzzy sliding mode controller based on Backstepping (IT2FBSMC), to control the speed of a dual star induction machine (DSIM), in order to get a robust performance machine. An appropriate control strategy based on the coupling of three methods (Backstepping, sliding mode and type-2 Fuzzy controller) is used to build a robust controller used to approximate the discontinuous control eliminating the chattering phenomenon and guaranteeing the stability of the machine. Moreover, it forces the rotor angular speed to follow a desired reference signal. The simulation results obtained using Matlab/Simulink behavior are presented and discussed. The obtained results show that the controller can greatly alleviate the chattering effect and enhance the robustness of control systems with high accuracy.

Modified T2FSMC approach for solar panel systems

In this paper, we consider the control problem for solar panel systems such that the panel is perpendicular to the direction of sunlight, which is suitable for absorbing the sun's energy efficiently. Based on the existing Type-2 Fuzzy Sliding Mode Control (T2FSMC) method, we propose a Modified T2FSMC approach in this paper, where a bisection algorithm is used to compute the normalized gain. According to simulation results, the performance of Modified T2FSMC is significantly better compared to the performance of T2FSMC and Fuzzy Sliding Mode Control (FSMC). Specifically, Modified T2FSMC has a smaller steady-state error and is more robust to disturbance compared with FSMC. Moreover, Modified T2FSMC also has a smaller steady-state error compared to T2FSMC.

Solar Panel Control System Using an Intelligent Control: T2FSMC and Firefly Algorithm

Solar panel is a solar energy converter to electrical energy. On solar tracker, there is a controller which sets the movement of solar panel such that it is perpendicular with solar rays. Previous research had designed Type 2 Fuzzy Sliding Mode Control (T2FSMC) controller to control the position of solar panel. However, there was trial and error process to determine gain scale factor so the development of optimization method is needed. This paper aims to modify gain scale factor using Firefly algorithm to increase performance of system. The simulation shows that T2FSMC Firefly has better performance than T2FSMC. T2FSMC Firefly shows the increase of performance on rise time, settling time, and integral time absolute error.

A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics

ABSTRACTIn this paper, in order to achieve the best tracking control of a class of multi-input multi-output (MIMO) nonlinear systems with unknown dynamics and unknown disturbances, a new robust adaptive interval type-2 fuzzy sliding mode control law (AIT2-FSMCL) has been proposed. Based on developing interval type-2 fuzzy local models for some operating points of the controlled system, an interval type-2 fuzzy logic system (IT2-FLS) has been designed to better estimate the unknown nonlinear dynamics of the studied system. Then, to enhance the tracking control performance and ensure the system robustness in the presence of approximation errors, parameter variations, un-modelled dynamics and external disturbances, a new AIT2-fuzzy sliding mode system (AIT2-FSMS), has been introduced. In order to avoid the chattering phenomenon while keeping the system performance, the AIT2-FSMS uses three AIT2-fuzzy logic systems (AIT2-FLSs) to estimate the optimal gains of the AIT2-FSMCL. The adaptation laws have been derived using the Lyapunov stability approach. The mathematical proof shows that the closed-loop system with the proposed control approach is globally asymptotically stable. Finally, the proposed design method is applied to a two-link robot arm to validate the effectiveness of the proposed control approach.

Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter

In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter.The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller.Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults.

Indirect Adaptive Interval Type-2 Fuzzy Sliding Mode Controller Design for Flexible Air-breathing Hypersonic Vehicles

An indirect adaptive interval type-2 fuzzy sliding mode controller (AIT2-FSMC) for flexible air-breathing hypersonic vehicle (FAHV) longitudinal model is presented in this paper. The proposed controller is designed by combining an adaptive Mamdani linguistic based interval type-2 fuzzy logic system (IT2-FLS) with sliding mode control technique. For the sake of the FAHV longitudinal model stably controlled under parametric and structural uncertainties which mainly come from varying aerodynamic interferences, flexible modes in airframe mutual couplings and fuel consumptions in practical conditions, we decouple the model through feedback linearization and design the main controller by sliding mode control technique to achieve the system convergence. Moreover, three adaptive interval type-2 fuzzy logic systems, which uses difference combinations of velocity and altitude tracking errors, pitch angle and slip slide angle as the inputs of antecedent sets, are designed to estimate nonlinear time varying functions and inverse matrix with bounded uncertainties. The adaptive law of the IT2-FSMC is derived through Lyapunov synthesis approach to guarantee the system asymptotic stability. Several comparisons under different levels of complex parametric and structural uncertainties have been done. The simulation results validate the performance of the proposed controller with robustness and effectiveness.

Active Fault Tolerant Control Based on Interval Type-2 Fuzzy Sliding Mode Controller and Non Linear Adaptive Observer for 3-DOF Laboratory Helicopter

Active Fault Tolerant Control Based on Interval Type-2 Fuzzy Sliding Mode Controller and Non Linear Adaptive Observer for 3-DOF Laboratory Helicopter

Backstepping-Based Recurrent Type-2 Fuzzy Sliding Mode Control for MIMO Systems (MEMS Triaxial Gyroscope Case Study)

This paper presents a novel type-2 fuzzy sliding mode control with nonlinear consequent part in fuzzy rules for control of Micro-Electro-Mechanical Systems (MEMS) gyroscope. The MEMS gyroscope consists of the basic mechanical structure, an electronic transducer to excite the system as well as an electronic sensor to detect the change in the mechanical structures modal shape. A nonlinear consequent part recurrent type-2 fuzzy system is used to approximate the conventional sliding mode control (SMC) law. A supervisory compensator is introduced to eliminate the effect of the approximation error. The adaptive adjustment algorithms for type-2 fuzzy parameters are derived in the sense of projection algorithm and Lyapunov stability theorem. The proposed type-2 fuzzy system has simple structure with six layers. Recurrent feedbacks at the fifth layer uses delayed outputs for improve the performance of type-2 fuzzy system. Finally the proposed type-2 fuzzy sliding mode control system is used to tracking control design with regard to uncertainty in MEMS gyroscope system. Combination of backstepping method and sliding mode control helps to compensate the control signal and get a better performance. The backstepping method is used to improve the global ultimate asymptotic stability and applying the sliding mode control to obtain high response and invariability to uncertainties. Simulation results show the proposed type-2 fuzzy system has better performance than ANFIS-based sliding mode control.