Fuzzy Integral Controller Research Articles

Design of an Integral Fuzzy Logic Controller for a Variable-Speed Wind Turbine Model

The demand for electricity is continuously growing around the world and thus the need for renewable and long-lasting sources of energy has become an essential challenge. Wind turbines are considered one of the major sources of renewable electricity generation. Therefore, there is a crucial demand for wind turbine model and control systems that are capable of precisely simulating the actual wind power systems. In this paper, an advanced fuzzy logic controller is proposed to control the speed of a wind turbine system. Initially, aero dynamical, mechanical and electrical models of two mass wind turbines models are derived. Analytical calculation of the power coefficient is adopted through a nonlinear function of six coefficients that mainly depends on pitch angle and tip speed ratio. The ultimate power output from the turbine can reach up to 50 % which is achieved at zero pitch angle with an approximately tip speed ratio of eight. This is then followed by designing a hybrid fuzzy-plus I pitch controller to regulate the speed of the wind turbine shaft. In general, fuzzy logic control strategy have the advantages over traditional control techniques especially when the system is highly non-linear and has to deal with strong disturbances such as wind turbulence. To evaluate the reliability and robustness of the controller, the response of the wind turbine system is tested under several types of disturbances including wind fluctuation, sudden disturbances on high and low speed shafts. Simulation findings reveals that the performance of fuzzy-integral control technique outweighs that of conventional fuzzy approach in terms of multiple performance evaluation indexes such as zero overshoot and steady state error, rise time and a settling time of (32.9 s) (44.7 s) respectively. The reliability and robustness of the controller is tested by applying speed and torque disturbances of 25% of their maximum ranges. Results have revealed that the controller was able to reject all disturbances efficiently with a change in pitch angle up to a maximum of 10 degrees in order to retain a constant rotor speed at 1000 rpm.

Event-triggered fuzzy integral control for a class of nonlinear singularly perturbed systems

A fuzzy integral controller with an event-triggered strategy for a class of nonlinear continuous singularly perturbed systems is proposed in this manuscript. Since the singularly perturbed systems are characterized by the parasitic parameter ɛ, which leads the systems to have multi-time-scale dynamics, a state feedback controller is proposed and designed for manipulating the effects of the parasitic parameter with the ɛ free functions by utilizing the Takagi–Sugeno fuzzy model, integral feedback, and event-triggered mechanism. As a result, we demonstrate that the proposed method maintain almost the same performance as the conventional controllers with less steady-state error while producing fewer events, which makes the communication channels between the plant system and the controller more available, through the examples of electrical engineering problems.

Power quality enhancement in islanded microgrids via closed-loop adaptive virtual impedance control

The high proportion of nonlinear and unbalanced loads results in power quality issues in islanded microgrids. This paper presents a novel control strategy for harmonic and unbalanced power allocation among distributed generators (DGs) in microgrids. Different from the existing sharing strategies that allocate the harmonic and unbalanced power according to the rated capacities of DGs, the proposed control strategy intends to shape the lowest output impedances of DGs to optimize the power quality of the microgrid. To achieve this goal, the feasible range of virtual impedance is analyzed in detail by eigenvalue analysis, and the findings suggest a simultaneous adjustment of real and imaginary parts of virtual impedance. Because virtual impedance is an open-loop control that imposes DG to the risk of overload, a new closed-loop structure is designed that uses residual capacity and absorbed power as feedback. Accordingly, virtual impedance can be safely adjusted in the feasible range until the power limit is reached. In addition, a fuzzy integral controller is adopted to improve the dynamics and convergence of the power distribution, and its performance is found to be superior to linear integral controllers. Finally, simulations and control hardware-in-the-loop experiments are conducted to verify the effectiveness and usefulness of the proposed control strategy.

Design and Fabrication of a Device for Reducing Hand Tremor in Parkinson Patients during Eating.

In this paper, the method of designing a noninvasive device for eliminating hand tremors in Parkinson's patients is presented. The designed device measures the tremors of the patient's hand and implements the tremor control accordingly. Since Parkinson's disease reduces patients' abilities to perform daily activities, this device is designed as an electronic spoon. The inertial measurement units are used to measure hand tremors. The signals got from motion sensors are passed through Butterworth's second order low pass filters to attenuate signals amplitude at frequencies higher than the human hand's natural frequency. The signals are sent to a proposed Proportional Integral (PI) fuzzy controller as a set point signal, and appropriate control signals are applied to two actuators installed orthogonal. Besides motion sensors, a microcontroller is installed inside the spoon handle that implements a PI fuzzy controller and provides control signals for two high speed servo motors installed perpendicularly. As such, the spoon can minimize the tremor effect. In this system, no damper or mass is added to the hand, and the patients are not required to wear an orthosis. The contribution of this paper is twofold. First, we use sensor data fusion to increase measurement accuracy. In this paper, we use accelerometer and gyroscope sensors. Second, we proposed a robust PI fuzzy controller to compensate for the uncertainties and reduce the tremor. The test results show that the hand tremor of Parkinson's patients during eating is reduced up to 75% using this method.

Summarisation, Simulation and Comparison of Nine Control Algorithms for an Active Control Mount with an Oscillating Coil Actuator

With the further development of the automotive industry, the traditional vibration isolation method is difficult to meet the requirements for wide frequency bands under multiple operating conditions, the active control mount (ACM) is gradually paid attentions, and the control algorithm plays a decisive role. In this paper, the ACM with oscillating coil actuator (OCA) is taken as the object, and the comparative study of the control algorithms is performed to select the optimal one for ACM. Through the modelling of ACM, the design of controller and the system simulations, the force transmission rate is used to compare the vibration isolation performance of the nine control algorithms, which are least mean square (LMS) adaptive feedforward control, recursive least square (RLS) adaptive feedforward control, filtered reference signal LMS (FxLMS) adaptive control, linear quadratic regulator (LQR) optimal control, H2 control, H∞ control, proportional integral derivative (PID) feedback control, fuzzy control and fuzzy PID control. In summary, the FxLMS adaptive control algorithm has the better performance and the advantage of easier hardware implementation, and it can apply in ACMs.

Extended Disturbance Observer-Based Integral Sliding Mode Control for Nonlinear System via T–S Fuzzy Model

In this paper, an extended disturbance observer-based integral sliding-mode control for a nonlinear system is proposed by the Takagi-Sugeno (T-S) fuzzy model approach. The proposed method focuses on two points: First, improving the design flexibility of integral fuzzy sliding-mode control (IFSMC) by transforming a conventional T-S fuzzy model structure into a novel form. Second, expanding a previous disturbance observer-based control (DOBC) concept by introducing a Fourier analysis to deal with the non-periodic form of disturbance. By using the modified form of the fuzzy model, a novel sliding surface combined with estimated disturbance through several fuzzy disturbance observers (FDOB) is suggested. Besides, a sufficient condition for guaranteeing asymptotic stability of the sliding dynamic with H ∞ control performance is proposed by applying a proper Lyapunov function with the linear matrix inequality (LMI) concept. Furthermore, a reachability problem of the proposed sliding surface is also handled by introducing another Lyapunov function. Finally, the effectiveness of the proposed method is demonstrated by comparing previous studies, which focused on robust control techniques, based on the simulation results of an inverted-pendulum system.

Performance comparison of PEMFC hydrogen reformer with different controllers

The renewable energy technology has become very popular due to major constraint in the existing electrical system such as high electricity demand, increased in fuel prices and concern of environmental pollution. The aims of this project are to develop a complete Proton Exchange Membrane Fuel Cell (PEMFC) model with hydrogen reformer by using MATLAB/ Simulink with three different controllers and comparison between the three controllers will be discussed. This project presents the development of methods to solve the problem of PEMFC output voltage by using different controllers which are Proportional Integral (PI), Proportional Integral Derivatives (PID) and Proportional Integral Fuzzy (PI-Fuzzy) controllers. The Ziegler Nicholas tuning method is used to tune PI and PID gains in a Simulink model. It helps the system to achieve a balance between performance and robustness for both controllers. The Mamdani type was used to develop the fuzzy controller in Simulink model. The transient performances that will be discussed are rise time, settling time, maximum overshoot, and percentage of overshoot. The results show that the proposed PI-Fuzzy is better than the conventionally used PI and PID controllers.

Disturbance observer‐based integral fuzzy sliding‐mode control and its application to wind turbine system

In this study, a disturbance observer-based integral fuzzy sliding-mode control methodology for a wind turbine system with a non-linear permanent magnet synchronous generator (PMSG) is proposed using the Takagi–Sugeno fuzzy model. To reduce the hardware cost of the fuzzy controller membership function, an imperfect premise matching condition is considered. Considering the matched disturbance, and an external disturbance acting on the system, a novel integral fuzzy sliding surface is proposed based on a fuzzy disturbance observer (FDOB). Therefore, various forms of external disturbances can be estimated using the FDOB. In addition, a sufficient condition for guaranteeing the asymptotic stability of the sliding motion with performance is proposed using a Lyapunov function and derived using a linear matrix inequality format. Furthermore, a reachability problem of the system states over the proposed sliding surface is derived through an appropriate Lyapunov function. Finally, the simulations for a wind turbine system using a PMSG are implemented to verify the effectiveness of the proposed method as compared with previous studies.

Active-Disturbance-Rejection-Control for Temperature Control of the HVAC System

Heating, ventilation, and air conditioning (HVAC) system is significant to the energy efficiency in buildings. In this paper, temperature control of HVAC system is studied in winter operation season. The physical model of the zone, the fan, the heating coil and sensor are built. HVAC is a non-linear, strong disturbance and coupling system. Linear active-rejection-disturbance-control is an appreciate control algorithm which can adapt to less information, strong-disturbance influence, and has relative-fixed structure and simple tuning process of the controller parameters. Active-rejection-disturbance-control of the HVAC system is proposed. Simulation in Matlab/Simulink was done. Simulation results show that linear active-rejection-disturbance-control was prior to PID and integral-fuzzy controllers in rising time, overshoot and response time of step disturbance. The study can provide fundamental basis for the control of the air-condition system with strong-disturbance and high-precision needed.

Performance analysis of LCLC resonant converter with PI and fuzzy gain scheduled PI controllers

Purpose The purpose of this paper is to analyze the performance of LCLC resonant converter (RC) with proportional integral controller and fuzzy gain scheduled proportional integral controller. Design/methodology/approach The drawbacks of series RC and parallel resonant converter (PRC) are explained using relevant references in Section 1 of this paper. The necessity of RCs and the merits of zero voltage and zero current switching are given in the Section 2. In Section 3, the modeling of LCLC RC using state space technique is done. In Section 4, the open loop analysis and performance evaluation of proportional integral controller, fuzzy gain scheduled proportional controller using MATLAB Simulink is obtained. The hardware specification is given and experimental results are taken for LCLC RC. In Section 5, conclusion of study is given. Findings The LCLC RC overcomes the drawbacks of series and PRC. The fuzzy gain scheduled proportional integral controller is suitable for load variations in RC. Originality/value The output of the converter is not affected with the load variations since the controller suggested in the paper works for load changes and can be a solution for load parameter deviation applications. Also performance of the RC is improved by the fast response of the proposed controller.

New techniques to improve the power control in the double-fed induction generator wind turbine

The great interest shown today in the double-fed induction generator in wind chain prompted us to analyze the performance of the separate control of active and reactive power generated by the stator of double-fed induction generator connected to the grid. The objective of the separate control of active and reactive stator powers is to provide constant power to the power grid whatever the variation of the wind speed, and to provide reactive power to correct the power factor. In this article, we present the modeling and an integrated vector control in a double-fed induction generator wind chain, which aims to independently control the active and reactive power generated by the double-fed induction generator. Knowing that the direct control of active and reactive power delivered to the grid with conventional proportional integral controllers provides good performance in permanent diet but a variable speed wind, the measured powers hardly follow the set values. To remedy this problem, we replace the conventional proportional integral controllers with proportional integral–fuzzy controllers to ensure good performance and robustness of the control of separate powers. To justify this choice, it is necessary to evaluate and compare the separate control loop for active and reactive power with conventional proportional integral controllers than with proportional integral–fuzzy controllers under the same constraint variable speed wind. The second part treated in this article is to reduce the harmonic pollution caused by the supply of the double-fed induction generator–based inverters and controlled rectifiers, which strongly infect current line. This phenomenon can have an adverse effect on the loads connected to the grid and equipment of proximity. The insertion of a filter system in the chain is needed, except that the strain of the volume and the reflection require a high cost for a more advanced and more optimal solution. Our contribution to this part is to replace the supply of the double-fed induction generator rotor side by a matrix converter controlled by the modulation technique of the difference errors between the measured values and the desired output values (least mean square errors).

A hybrid control strategy to control active filter and improve the PQ of non-linear load

Nowadays, the power quality (PQ)-related issues are more absorbed in power electronic devices. For compensating PQ disturbances, various types of power devices are used. The shunt active power filter (SAPF) is one of the power electronics devices that are used for enhancing the PQ. To reduce the PQ disturbances, the performance of SAPF must be improved. In this paper, a hybrid controller is proposed for improving the performance of SAPF and compensating the PQ. The hybrid technique is the combination of cuckoo search algorithm and radial basis function neural network technique which is used for extracting the reference current for compensating the SAPF and reducing the PQ problem. The SAPF is used for reducing the harmonic disturbances. The DC-link voltage is regulated by utilizing the proposed hybrid controller technique. Subsequently, the Fast Fourier Transform analysis is used for measuring total harmonic distortion values of the proposed system. The proposed method is implemented in MATLAB/Simulink platform and its performance is evaluated. The performance of the proposed method is evaluated and compared with the proportional–integral controller and fuzzy controller.

A Combined Methodology of H∞ Fuzzy Tracking Control and Virtual Reference Model for a PMSM

The aim of this paper is to present a new fuzzy tracking strategy for a permanent magnet synchronous machine (PMSM) by using Takagi-Sugeno models (T-S). A feedback-based fuzzy control with h-infinity tracking performance and a concept of virtual reference model are combined to develop a fuzzy tracking controller capable to track a reference signal and ensure a minimum effect of disturbance on the PMSM system. First, a T-S fuzzy model is used to represent the PMSM nonlinear system with disturbance. Next, an integral fuzzy tracking control based on the concept of virtual desired variables (VDVs) is formulated to simplify the design of the virtual reference model and the control law. Finally, based on this concept, a two-stage design procedure is developed: i) determine the VDVs from the nonlinear system output equation and generalized kinematics constraints ii) calculate the feedback controller gains by solving a set of linear matrix inequalities (LMIs). Simulation results are provided to demonstrate the validity and the effectiveness of the proposed method.

Simple Integral Fuzzy Control for Converters with Highly Nonlinear Dynamics

A simple integral Takagi-Sugeno (T-S) fuzzy control scheme suitable for many types of converters is proposed in this paper. A converter with highly nonlinear characteristics, called active high power factor correction (AHPFC), is taken as an example to show the control scheme. Indeed, we can derive a linear controller to achieve zero output regulation error for the AHPFC converter. First, we include an integral error signal to form an augmented system. After translating the coordinate to the regulated point, we obtain the stabilization model. The model-based fuzzy approach is then used to handle the nonlinear system. The system stability is proven by Lyapunov theorem. The feedback gains are obtained by solving linear matrix inequalities (LMIs). A surprised property is that the gains are identical for every fuzzy control rule. This result greatly simplifies the controller to be a linear state feedback one. Finally, the simulation and experimental results show the satisfactory performance, which is better than the converter using a proportional integral (PI) controller.

Internet Congestion Control Using Fuzzy Integral Controller

Until now, internet congestion problem cannot be completely resolved. The main cause of the internet congestion is the control mechanism for dividing network capacity does not work effectively. Thus, the amount of data through the network can exceed the network capacity. Various studies based on the control system theory have been done to overcome this problem. This paper specifically examines congestion control system based on fuzzy logic mechanism. The proposed controller is fuzzy integral controller in the router and control signal processing that resides on the user side, which is modelled by first order system. This control technique is a congestion control with explicit feedback. The control calculation result, i.e. the divided capacity of the router, which is distributed fairly among all users, is explicitly given to the user. There are three simulation scenarios to show the performance of the proposed congestion control system. From the simulation results can be concluded that the congestion control system using fuzzy integral controller has succeeded in fairly allocating capacity routers and able to prevent internet congestion by keeping the aggregate data flow through the router does not exceed the service rate of the router.

Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers

This paper proposes a novel Adaptive Charged System Search (ACSS) algorithm for the optimal tuning of Takagi–Sugeno proportional–integral fuzzy controllers (T–S PI-FCs). The five stages of this algorithm, namely the engagement, exploration, explanation, elaboration and evaluation, involve the adaptation of the acceleration, velocity, and separation distance parameters to the iteration index, and the substitution of the worst charged particles’ fitness function values and positions with the best performing particle data. The ACSS algorithm solves the optimization problems aiming to minimize the objective functions expressed as the sum of absolute control error plus squared output sensitivity function, resulting in optimal fuzzy control systems with reduced parametric sensitivity. The ACSS-based tuning of T–S PI-FCs is applied to second-order servo systems with an integral component. The ACSS algorithm is validated by an experimental case study dealing with the optimal tuning of a T–S PI-FC for the position control of a nonlinear servo system.

Adaptive Current Control with PI-Fuzzy Compound Controller for Shunt Active Power Filter

An adaptive control technology and PI-fuzzy compound control technology are proposed to control an active power filter (APF). AC side current compensation and DC capacitor voltage tracking control strategy are discussed and analyzed. Model reference adaptive controller for the AC side current compensation is derived and established based on Lyapunov stability theory; proportional and integral (PI) fuzzy compound controller is designed for the DC side capacitor voltage control. The adaptive current controller based on PI-fuzzy compound system is compared with the conventional PI controller for active power filter. Simulation results demonstrate the feasibility and satisfactory performance of the proposed control strategies. It is shown that the proposed control method has an excellent dynamic performance such as small current tracking error, reduced total harmonic distortion (THD), and strong robustness in the presence of parameters variation and nonlinear load.

A Choquet Fuzzy Integral Controller for Stabilization and Tracking Application

The stabilization, tracking and pointing systems are essential features of modern fire control and surveillance systems. The criteria for precision stabilization may vary from a few hundred micro-radians to few nano-radians for achieving jitter free image depending upon the application scenario. The Line of sight (LOS) is stabilized by mounting the optical payload on a gimbal platform and designing the control system around them. The paper describes a choquet fuzzy integral based control algorithm developed for LOS controlling and stabilizing application. In this approach, q-measure is estimated to simplify the computation of λ-measure that aggregates the information from the weighted inputs. The output of fuzzy rules, which are formulated by defining the product of weighted inputs are required to compute the fuzzy measure in the form of Choquet fuzzy integral.

Simple Realization of Integral Fuzzy Control for Isolated AHPFC Converters

This paper proposes an integral Takagi-Sugeno (T/S) fuzzy controller to achieve the output voltage regulation for an AC-DC isolated active high power factor correction (AHPFC) converter. The converter can avoid high voltage stresses and decrease harmonic distortions under discontinuous conduction mode (DCM). The dynamics of the converter are derived by the AM-TTS-DS method. To ensure zero steady-state error, we add an extra integral error signal to the dynamics. Translating coordinate to the DC operating points, the converter's stabilization model can be determined. Both feedback gains and system stability are inferred simultaneously. The control gains can be obtained by solving linear matrix inequalities (LMIs) via Matlab's toolbox. A surprising property is that the obtained feedback gains are identical for every fuzzy control rule. This condition greatly simplifies the realization using analog circuits. The simulations and experimental results exhibit the satisfactory performance of the converter with the designed integral T/S fuzzy regulator.

Optimal linear PI fuzzy controller design of a heat exchanger

This study aims at improving the control of a heat exchanger, described by a partial differential equation, by optimizing a linear proportional–integral fuzzy controller. The design of the controller is based on the use of a finite-dimensional approximate model, of high order, derived by spatially lumping the infinite-dimensional model of the heat exchanger. The design procedure consists to optimize the scaling factors of the linear fuzzy controller, by solving an unconstrained optimization problem issued from the simplification of a formulated constrained optimization where the objective function is an integral error measure, and the constraints are the relationships between fuzzy and conventional PID gains. The formulated unconstrained optimization problem is then solved using jointly the Matlab Optimization Toolbox and Simulink. Through simulation, the performances of the heat exchanger are evaluated, and the obtained results show that the fuzzy controller produces improved control performance with respect to the conventional controller.