Fuzzy Sliding Mode Research Articles

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

The Research Based on Fuzzy Sliding Mode Control for Linear Double Inverted Pendulum

This paper involves a linear double inverted pendulum system whose the state space model is established by Lagrange function. In order to solve the chattering problem of the conventional quasi-sliding mode variable structure control, this linear double inverted pendulum system applies the fuzzy control theory to adjust the parameterwhich is in the sliding mode variable structure control law. Then the fuzzy theory is utilized to design the sliding mode and deduce the fuzzy sliding mode reaching law. The significance of this method is that it diffuses the control signal, reduces or avoids the chattering phenomenon of sliding mode control. For the most, the simulation results show that the linear double inverted pendulum system based on fuzzy sliding mode variable structure control not only retains the strong robustness of sliding mode variable structure control, but also improves the dynamic quality of the system and weakens the buffeting of the system. Thus the method is proved to have certain research.

Improved Direct Power Control for Rectifier Based on Fuzzy Sliding Mode

An improved direct power control (DPC) is proposed for a three-phase voltage-source rectifier based on fuzzy sliding mode. It introduces the sliding mode controller (SMC) to enhance the disturbance rejection ability of the outer dc voltage loop. To ensure the stability of SMC, a fuzzy-based switching state controller is developed for the inner power loop, with which the switching states can be provided directly at the fixed time interval. This can contribute to the digitalization of controller and eliminate the drawbacks of the predefined switching table and the variable frequency that exists in the classical DPC. The effectiveness of the proposed DPC is verified by the simulation and experiment. Compared with the classical DPC, the current total harmonic distortion in the steady state is reduced by nearly half, and the transient setting time is shortened by at least 23%. The results indicate better performance of the proposed DPC in both the steady and transient states.

Sensorless Control for PMLSM Based on Fuzzy Sliding Mode Observer

In this paper, a new sensorless control method is proposed for a permanent magnet linear synchronous motor based on Fuzzy sliding mode observer, which combines the advantages of sliding mode observer and Fuzzy controller respectively. The difference between the current estimated value and the actual current value is regarded as sliding mode function; sliding mode function (current error) and variation of the error are used as the input of fuzzy controller, and the width of the boundary layer as the output, adjusting the width of the boundary layer dynamically in real time. The simulation results show that Fuzzy sliding mode observer is able to find a balance between soft chattering and steady-state error, keep the system robustness and control precision.

Fuzzy Sliding Mode Control for Parallel DC-DC Boost Converter

Nowadays, parallel DC-DC switched converters are commonly used in many applications such as distributed power supply systems and embedded systems to extend battery life. As a single switched mode DC-DC converter topology, a parallel converter must provide a regulated output voltage. For such case the regulation of the voltage must be performed in a closed loop control mode. In this paper, a Fuzzy Sliding Mode Control (FSMC) is developed and applied to a two parallel DC-DC converter. Fuzzy Sliding Mode Control is a robust control which combines the benefits of fuzzy logic control and sliding mode control. The proposed FSMC is implemented in real time using a dSPACE control board. The efficiency and the robustness of the proposed controller are tested by simulation and experimentally, with success, for different operating conditions

Design Intelligent PID like Fuzzy Sliding Mode Controller for Spherical Motor

The minimum rule base Proportional Integral Derivative (PID) Fuzzy Sliding Mode Controller (SMC) with application to spherical motor is presented in this research. The popularity of PID Fuzzy Sliding Mode Controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID Fuzzy Sliding Mode Controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing especially in nonlinear and uncertain systems. Proportional Integral Derivative methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions, we will need 343 rules. It is too much work to write 343 rules and have lots of problem to design embedded control system e.g., Field Programmable Gate Array (FPGA). In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a conventional PI controller to have the minimum rule base and good trajectory follow disturbance to control of spherical motor. However Sliding Mode Controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters for each direction of three degree of freedom spherical motor, this controller is work based on motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear spherical motor‟s dynamic equation which caused to challenge in uncertain system. This research is used to reduce or eliminate the Sliding Mode Controller problem based on minimum rule base fuzzy logic theory to control of three degrees of freedom spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator. Index Term—PID like fuzzy control, Sliding Mode Controller, PD like fuzzy control, conventional PI control, three degrees of freedom spherical motor.

Robust Adaptive Fuzzy Sliding Mode Control Based on Fuzzy Compensation for Ammunition Auto-loading Robot

Aimed at the problems of low control accuracy and weak robustness influenced by external disturbance, friction, load changes, modeling errors and other issues in ammunition auto-loading robot control system, a new robust adaptive fuzzy sliding mode controller based on fuzzy compensation is proposed. The control architecture employs fuzzy systems to compensate adaptively for plant uncertainties to distinguish different disturbance compensation terms and approximate each of them respectively. The stability of the robust adaptive fuzzy sliding mode control (SMC) and the convergence of the tracking errors are ensured by using the Lyapunov theory. By analyzing and comparing the simulation results, it is obviously shown that the control system can lighten the effect on the control system caused by different disturbance factors and eliminate the system chattering instead of traditional SMC. As a result, the control system has great dynamic features and robust stability and meets the requirement that the actual motion of ammunition auto-loading robot quickly tracks the scheduled trajectory. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4342

Fuzzy Sliding Mode Control of a Multi-DOF Parallel Robot in Rehabilitation Environment

Multi-degrees of freedom (DOF) parallel robot, due to its compact structure and high operation accuracy, is a promising candidate for medical rehabilitation devices. However, its controllability relating to the nonlinear characteristics challenges its interaction with human subjects during the rehabilitation process. In this paper, we investigated the control of a parallel robot system using fuzzy sliding mode control (FSMC) for constructing a simple controller in practical rehabilitation, where a fuzzy logic system was used as the additional compensator to the sliding mode controller (SMC) for performance enhancement and chattering elimination. The system stability is guaranteed by the Lyapunov stability theorem. Experiments were conducted on a lower limb rehabilitation robot, which was built based on kinematics and dynamics analysis of the 6-DOF Stewart platform. The experimental results showed that the position tracking precision of the proposed FSMC is sufficient in practical applications, while the velocity chattering had been effectively reduced in comparison with the conventional FSMC with parameters tuned by fuzzy systems.

Adaptive Self-Organizing Fuzzy Sliding-Mode Radial Basis-Function Neural-Network Controller for Robotic Systems

A self-organizing fuzzy radial basis-function neural-network controller (SFRBNC) has been proposed to control robotic systems. The SFRBNC uses a radial basis-function neural-network (RBFN) to regulate the parameters of a self-organizing fuzzy controller (SOFC) to appropriate values in real time. This method solves the problem caused by the inappropriate selection of parameters in an SOFC. It also eliminates the dynamic coupling effects between degrees of freedom (DOFs) for robotic system control because the RBFN has coupling weighting regulation capabilities. However, its stability is difficult to demonstrate. To overcome the stability issue, this study developed an adaptive self-organizing fuzzy sliding-mode radial basis-function neural-network controller (ASFSRBNC) for robotic systems. The ASFSRBNC solves the problem of an SFRBNC implementation in determining the stability of the system control. It also applies an adaptive law to modify the fuzzy consequent parameter of a fuzzy logic controller to manipulate a robotic system to improve its control performance. The stability of the ASFSRBNC was proven using the Lyapunov stability theorem. From the experimental results of 6-DOF robotic control tests, the ASFSRBNC achieved better control performance than the SFRBNC as well as the SOFC.

Simulation to Implementation as Good Practices for Teaching Power Electronics to Undergraduate Students: Fuzzy Sliding Mode Control for DC Motors

How can students be given experience in the confused realities of engineering processes? How can undergraduate students be convinced that processes can be analyzed and improved? Computer simulations properly designed and applied could answer these challenges revolutionizing education in Power Electronics. In recent years, computer simulation has been commonly used in education to motivate students in their learning and help teachers to improve their teaching level. The present paper focuses on developing a speed controller for DC motors starting from theoretical aspects, passing through simulations, and finally reaching a control prototype. The control theory is based on a nonlinear technique known as Sliding Mode Control (SMC) involving artificial intelligence for optimization such as Fuzzy Logic (FL), Adaptive Neurofuzzy Inference Systems (ANFIS), and Genetic Algorithms (GAs).

Design a Novel SISO Off-line Tuning of Modified PID Fuzzy Sliding Mode Controller

The Proportional Integral Derivative (PID) Fuzzy Sliding Mode Controller (FSMC) is the most widely used control strategy in the Industry (control of robotic arm). The popularity of PID FSMC controllers can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID FSMC controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. Biologically inspired evolutionary strategies have gained importance over other strategies because of their consistent performance over wide range of process models and their flexibility. This paper analyses the modified PID FSMC controllers based on minimum rule base for flexible robot manipulator system and test the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

A robust and simple optimal type II fuzzy sliding mode control strategy for a class of nonlinear chaotic systems

This paper suggests a new hybrid control strategy, called Optimal Type II Fuzzy Sliding Mode (OT2FSM) control scheme, to realize the control of general uncertain chaotic systems. The proposed controller not only guaranties the stability and robustness against the lumped uncertainties caused by unmodeled dynamics and external disturbances, but also can significantly reduce the control chattering inherent in conventional sliding mode control. In the proposed controller, a novel heuristic algorithm namely particle swarm optimization with random inertia weight (RNW–PSO) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input and output membership functions are optimized simultaneously by RNW–PSO. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the performance of the proposed controller, the results are compared with those obtained by Optimal H-infinity Adaptive PID (OHAPID) controller and an optimal Type-2 fuzzy proportional integral derivative (OT2FPID), which are the latest researches in the problem in hand. Simulation results show the effectiveness of the OT2FSM controller.

Two-Dimensional Fuzzy Sliding Mode Control of a Field-Sensed Magnetic Suspension System

This paper presents the two-dimensional fuzzy sliding mode control of a field-sensed magnetic suspension system. The fuzzy rules include both the sliding manifold and its derivative. The fuzzy sliding mode control has advantages of the sliding mode control and the fuzzy control rules are minimized. Magnetic suspension systems are nonlinear and inherently unstable systems. The two-dimensional fuzzy sliding mode control can stabilize the nonlinear systems globally and attenuate chatter effectively. It is adequate to be applied to magnetic suspension systems. New design circuits of magnetic suspension systems are proposed in this paper. ARM Cortex-M3 microcontroller is utilized as a digital controller. The implemented driver, sensor, and control circuits are simpler, more inexpensive, and effective. This apparatus is satisfactory for engineering education. In the hands-on experiments, the proposed control scheme markedly improves performances of the field-sensed magnetic suspension system.

An Adaptive Fuzzy Sliding Mode Control Design for a Class of Uncertain Horizontal Platform Systems

This paper presents an adaptive fuzzy sliding mode control design for a class of uncertain horizontal platform systems (HPSs). Firstly, a nonsingular terminal sliding surface is proposed for HPSs. Then, a fuzzy logic system is introduced to estimate the system uncertainties. The adaptive fuzzy sliding mode controller can guarantee the stability of the closed-loop system. The corresponding numerical simulations are demonstrated to verify the effectiveness of the proposed method.

Hybrid Fuzzy Sliding Mode Control of a DFIG Integrated into the Network

This paper presents the study of a variable speed wind energy conversion system using a Doubly Fed Induction Generator (DFIG) based on a Fuzzy sliding mode control (FSMC) applied to achieve control of active and reactive powers exchanged between the stator of the DFIG and the grid to ensure a Maximum Power Point Tracking (MPPT) of a wind energy conversion system. However the principal drawback of the sliding mode, is the chattering effect which characterized by torque ripple, this phenomena is undesirable and harmful for the machines, it generates noises and additional forces of torsion on the machine shaft. In order to reduce the chattering effect, the Sign function of sliding mode controller’s discontinuous part is replaced by a fuzzy logic; we will have the fuzzy sliding mode controller (FSMC). The FSMC makes it possible to combine the performances of the two types of controllers (SMC and FLC) and eliminates the chattering effect. The proposed control algorithm is applied to a DFIG where the stator is directly connected to the grid and the rotor is connected to a three-level converter structure NPC to suppress low level harmonics, higher frequencies will be filtered out by the machine. Second goal of this paper is to extract a maximum of power; the rotor side converter is controlled by using a stator flux-oriented strategy. The decoupling created by the control between active and reactive stator power allows keeping the power factor close to unity. Simulation results show that the wind turbine can operate at its optimum energy for a wide range of wind speed. Both simulation and validation results show effectiveness of the proposed control strategy is in terms of power regulation. Moreover, the fuzzy sliding mode approach is arranged so as to reduce the chattering produced in the generated power that could lead to increased mechanical stress because of strong torque variations. DOI: http://dx.doi.org/10.11591/ijpeds.v3i4.4072

Stabilization Controller Design for a class of Inverted Pendulums via Adaptive Fuzzy Sliding Mode Control

X–Z inverted pendulum is a new kind of inverted pendulum and it can move with the combination of the vertical and horizontal forces. This paper addresses the control problem of X-Z inverted pendulum in the presents of system uncertainties and external disturbances, and an adaptive fuzzy sliding mode control approach is proposed. The fuzzy system is used to approximate the system uncertainties and the complicated intermediate control functions in the backstepping control design. To update the parameters of the fuzzy system, a proper proportional-integral adaptation law is introduced. Finally, simulation studies are done to show the stabilization of the X-Z inverted pendulum under the proposed method. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.2985