Adaptive Fuzzy Sliding Mode Research Articles

Adaptive Fuzzy Sliding Mode Control for a Class of Nonlinear System

For a class of nonlinear system with parameter perturbation and external disturbance, adaptive fuzzy control can be used to approach the system unknown functions to reduce the control input and the steady-state error. And an adaptive switch control gain whose adaptive law is decreasing function is designed to weaken the system chattering, the switch gain of estimate will increase on the basis of the original without decreasing with the elimination of interference. If system is interferenced many times. Against the shortcomings, this paper proposes an improved adaptive law that can weaken the system chattering effectively while maintaining the strong robustness. The simulation results by tests show that this method is correct and effective.

Adaptive Fuzzy Sliding Mode Controller for Attitude Coordinated Control in Spacecraft Formation

AbstractThe attitude coordinated control problem of a spacecraft formation in leader-follower approach is considered in this paper. An adaptive fuzzy sliding mode control scheme is designed to achieve tracking and synchronization in spacecraft formation in the presence of model uncertainties and external disturbances. The proposed control law consists of two parts: equivalent control and switching control. In order to attenuate high-frequency chattering caused by the switching control, the adaptive fuzzy control is utilized to approximate the sign function of the switching control. Moreover, fuzzy rules are employed to smooth the switching control based on the sliding surface. Lyapunov theory is applied to proof the stability of the closed-loop system. Finally, simulation results and comparative analysis are carried out to demonstrate the effectiveness of the proposed method.

Adaptive Fuzzy Sliding Mode Controller and Observer for a Dive Cell

AbstractWe present an adaptive fuzzy sliding mode control strategy in combination with a sliding mode observer for a dive cell. Numerical results demonstrate the outperformance of the presented controller compared to a conventional sliding mode approach. (© 2015 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Adaptive Type-2 Fuzzy Sliding Mode Control for Grid-Connected Wind Turbine Generator Using Very Sparse Matrix Converter

The strategy to improve both efficiency and power quality of grid-connected wind turbine generator systems (WTGs) are presented. WTGs efficiency is improved by developing a variable speed control to obtain maximum power at all wind speeds. Variable speed control based on Adaptive Type-2 Fuzzy Sliding Mode Control (AFSMOC) is proposed by employing Very Sparse Matrix Converter (VSMC). Type-2 fuzzy system is used to improve the robustness of sliding mode control. VSMC can provide low harmonics in line current, so the power quality problems can be minimized. The simulation results shows that the AFSMOC can regulate the generator speed at optimum Tip Speed Ratio (TSR) with maximum error 2.5 rpm, so that the maximum power can be obtained at all wind speeds. VSMC also provide good performance with Total Harmonic Distortion (THD) of voltage 0.35% and THD of current 6,82%

Adaptive sliding mode fuzzy control for unknown robots with arbitrarily-switched constraints

This article addresses the control problem of robots with unknown dynamics and arbitrarily-switched unknown constraints. Such kind of robots will be shown to be unknown hybrid systems with arbitrary switching and an Adaptive Sliding Mode Fuzzy Control (ASMFC) strategy is proposed that handles the unknown dynamics of the robot along with the unknown constraints arbitrary switching. The ASMFC is a synergy of finding a Common Lyapunov Function (CLF) between the resulted switched subsystems of the considered robots, employing the Fuzzy Logic Systems (FLS), and the use of the Sliding Mode Control (SMC). The CLF accommodates the constraints arbitrary switching, the SMC adds robustness against possible parameters drift, and the FLS approximates the unknown robot dynamics. All unknown parameters are adapted online and all closed loop signals are guaranteed to be bounded. The proposed strategy is validated by conducting an experiment on a KUKA Lightweight Robot (LWR) doing a typical force-guided peg-in-hole assembly task that falls in the category of robot systems under consideration. Excellent tracking performance is obtained when using the ASMFC strategy. Comparison is conducted with the performance of a PD controller that is widely used in commanding industrial robots and the superiority of the proposed strategy is shown.

Multisatellite Formation Control for Remote Sensing Applications Using Artificial Potential Field and Adaptive Fuzzy Sliding Mode Control

The formation control of satellites for remote sensing applications has received considerable attention during the past decade. This work deals with the development of a formation control strategy for the circular formation of a group of satellites. In this paper, artificial potential field method is used for path planning, and sliding mode control (SMC) technique is used for designing a robust controller. A fuzzy inference mechanism is utilized to reduce the chattering phenomenon inherent in the conventional SMC. An adaptive tuning algorithm is also derived based on Lyapunov stability theory to tune the fuzzy parameter. The proposed fuzzy-SMC-based technique is intended to compensate for the modeling uncertainties existing in practical applications. The results of simulations done for a group of five satellites making a circular formation confirm the stability and robustness of the present scheme.

Performance Comparison of Three Different Controllers of Proton Exchange Membrane Fuel Cell

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and strong-coupling characteristics of PEMFCs. Based on the dynamic model of PEMFC, an adaptive fuzzy sliding mode controller is proposed for PEMFC to realize constant voltage output and reliability service. Three different controllers, including fuzzy controller, fuzzy sliding mode controller and adaptive fuzzy sliding mode controller, are designed and compared. Simulation results show that the proposed adaptive fuzzy sliding mode controller for PEMFC can get satisfactory controlling effects.

Adaptive Fuzzy Sliding Mode Control of MEMS Gyroscope Sensor Using Fuzzy Switching Approach

In this paper, an adaptive fuzzy sliding mode control strategy, which combines the merits of sliding mode control and adaptive fuzzy control, is proposed to control the MEMS gyroscope in the presence of model uncertainties and external disturbances. The adaptive fuzzy systems are employed to approximate both the equivalent control term and the sliding mode controller. Then the switching control becomes continuous and the chattering phenomena can be attenuated. The adaptation laws based on the Lyapunov analysis can adaptively adjust the fuzzy rules to guarantee the asymptotical stability of the adaptive fuzzy closed-loop control system. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control schemes.

A Novel Sensorless MPPT for Wind Turbine Generators Using Very Sparse Matrix Converter Based on Hybrid Intelligent Control

The maximum power of Wind Turbine Generators (WTGs) can be obtained by adjusting the rotor speed at the optimum Tip Speed Ratio (TSR), so that the Maximum Power Point Tracking (MPPT) algorithms is needed to obtain the reference speed. The conventional MPPT such as Pertubartion and Observation (PO), a reference speed is determined by a constant step. Choosing appropriate the step size is a problem, because it may cause problems in the response and the oscillations at the maximum point. To solve this problem, the flexible step size is proposed by using Least Squares-Support Vector Machine (LS-SVM). Then, the Adaptive Type-2 Fuzzy Sliding Mode Control (AFSMOC) is applied to control a rotor speed at a reference speed through Very Sparse Matrix Converter (VSMC). To replace a rotor speed sensors, the Model Reference Adaptive System (MRAS) observers is proposed. The simulation results shows that the MPPT based LS-SVM is remarkably faster and more efficient than the PO algorithm. LS-SVM can generate the flexible steps with the accuracy of classification 94.29 %. The AFSMOC can regulating the rotor speed at reference point, so that the maximum power can be achieved at all wind speeds.

Adaptive Fuzzy Sliding Mode Controller for Attitude Coordinated Control in Spacecraft Formation

Adaptive Fuzzy Sliding Mode Controller for Attitude Coordinated Control in Spacecraft Formation

Adaptive Fuzzy Sliding Mode Control for the Probe Soft Landing on the Asteroids with Weak Gravitational Field

For the trajectory control of the probe soft landing on the asteroids with weak gravitational field, this paper presents a combined integral sliding mode control with an adaptive fuzzy logic system, named adaptive fuzzy sliding mode control (AFSMC) scheme. Considering the uncertainty of the orbit dynamics model in the small body fixed coordinate system, and the polyhedron modeling uncertainty in the gravitational potential, a fuzzy logic system is adopted to approximate the upper bound of the uncertainties. In addition, a robust control item is introduced to compensate for the approximation error of fuzzy logic system. The designed adaptive law and robust item make the closed-loop control stable and the tracking errors are convergent to zero. The controller not only guarantees the rapidity and accuracy of the desired trajectory tracking, but also enhances the robustness of the control system, improving the dynamic tracking performance for the probe soft landing on asteroids. Finally, the contrastive simulation results are presented to show the feasibility and effectiveness of the proposed control scheme.

Control of Overhead Crane System Using Adaptive Model-Free and Adaptive Fuzzy Sliding Mode Controllers

In this study, a model-free adaptive controller (MFAC) using feedback linearization and an adaptive fuzzy sliding mode controller (AFSMC) using fuzzy approximation are employed to control an underactuated overhead crane system. Both controllers use trolley position and load swing angle information for controlling process. Innovation of the proposed MFAC is based on utilizing the appropriate control signal value of last level for determining the control signal value of new level which depends on position error in these levels. In AFSMC, sliding mode scheme is exploited adaptive Sugeno fuzzy algorithm to update estimation of unknown function and counteract the effect of unknown nonlinear terms of overhead crane’s dynamic model. External disturbances such as the wind and the hit are also considered to verify the efficiency of the proposed model-free methods.

Design of a Robust and Indirect Adaptive Fuzzy Sliding Mode Power System Stabilizer Using Particle Swarm Optimization

This work presents an indirect adaptive fuzzy sliding mode power system stabilizer that is used to damp out the low frequency oscillations in power systems. The proposed controller design is based on an adaptive fuzzy control combining a proportional integral control and sliding mode control. The fuzzy logic system is used to approximate the unknown system function and using the particle swarm optimization technique to optimize parameters proportional integral control to eliminate the chattering action in the sliding mode control. Using Lyapunov synthesis, adaptation laws are developed to make the controller adaptive to changes in operating conditions of the power system. The nonlinear simulation studies show the successful performance of the proposed stabilizer.

Design of an Adaptive Fuzzy Sliding Mode Control Using Supervisory Fuzzy Control for Micro-Electro-Mechanical Systems (MEMS) Z-Axis Gyroscope

This paper presents a novel robust adaptive control strategy for MEMS gyroscope, based on the coupling of the fuzzy logic control with sliding mode control (SMC) approach and adaptive laws. The drawbacks of the conventional SMC include chattering phenomenon and requirement of a priori knowledge of the bounds of uncertainties. In this paper, these problems are suitably attenuated by adopting an adaptive fuzzy sliding mode control (AFSMC) approach which uses two additional fuzzy self-tuning controllers as supervisory fuzzy systems to adaptively tune the output control gain, sliding gain of the AFSMC in order to speed up the convergence rates of the tracking errors and parameter estimations with a desired level of attenuation. Control system stability is proved by Lyapunov method. Numerical simulations using the MEMS gyroscope model with uncertainties demonstrate the effectiveness of this approach in high speed trajectory tracking problems and robustness in estimating the gyroscope parameters and the angular velocity. Numerical simulations show that the chattering is effectively attenuated by this method. Convergence rate of tracking errors and the gyroscope parameters is better than convergence rates in the literature.

Adaptive Fuzzy Sliding Mode Control for Hydraulic Servo System of Parallel Robot

The hydraulic servo control system, which is the important component of parallel robot, is a high order, nonlinear, dynamic asymmetry, parameter uncertain system, which seriously affect dynamic performance of robot, so it is very difficult to gain good performance with traditional control. Based on sliding mode variable structure control method combined with fuzzy control and adaptive control, an adaptive fuzzy sliding mode control algorithm was presented by taking the Stewart platform servo control system of parallel robot as the research object, and the uncertain term of the sliding mode controller was approximated with adaptive fuzzy control method. The simulation results showed that compared with the conventional PID control applied to the same hydraulic control system, the new controller has a strong robustness, good traceability with regard to model uncertainties, unknown external disturbances and changes in the operation conditions, as well as much better adaptive characteristics. The simulation results also showed that the adaptive fuzzy sliding mode control system can solve the dynamic asymmetrical performance and poor stability of parallel robot, and can greatly improve the robot control precision. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5087

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion