Hybrid Fuzzy Controller Research Articles

ORTHOGONAL HYBRID-FUZZY CONTROLLERS

The main idea of this paper is to present a possibility of application of hybrid-fuzzy controllers in control systems theory. In this paper, we have described a new method оf using orthogonal functions in control of dynamical systems. These functions generate genarilzed quasi-orthogonal filter, which are used in the concluding phase of the fuzzy controllers. Proposed hybrid-fuzzy controllers of Takagi-Sugeno type has been applied to a DC servo drive system and performed experiments have verified efficiency and improvements of a new control method.

Hybrid fuzzy logic controller for boot converter operating in pv energy system

The demand for high efficiency DC/DC boost converters is increasing dramatically in many areas of industrial applications especially for PV system to produce high voltage to meet the needs of the load. Closed-loop systems are designed to automatically attain and keep the desired output condition by comparing it with the actual condition. In this paper, Hybrid Proportional-Integral Fuzzy Logic Controller (HPIFLC) is designed and implemented to control the duty cycle of DC/DC boost converter. This combination of Proportional-Integral (PI) and Fuzzy Logic (FL) is done to exploit the advantageous sides of both controllers to obtain better performance. The system under consideration consists of a PV module connected to the load through a controlled DC/DC boost converter. The mathematical model of the complete power system and the simulation has been done using MATLAB/SIMULINK. Performance comparison between PI, FL, and HPIFLC controllers have been carried out which emphasize that HPIFLC is superior to the other controllers as rise time, settling time, overshoot and steady state error are reduced.

Optimal Design of Wide Area Based on Fuzzy Controller and Intelligent Method

Recently, the controller using wide-area measurement systems (WAMS) signals has been proposed by researchers. But, an unavoidable delay before the wide-area signals exists which is received by the controller. Accordingly, a delay-independent robust control problem of large interconnected power systems is presented based on the hybrid fuzzy controller for wide area measurement. A fuzzy controller is a nonlinear controller and it is not so sensitive to system topology, parameter and operating condition changes as the conventional ones. According to wide area power system complexity and variation of the loads and network conditions, FPSS has been considered in this paper. Furthermore, the proposed controller has been improved by chaotic version of shark smell optimization algorithm (CSSO) as an optimization problem. Effectiveness of the proposed method has been applied over the 10 machine 39 bus New England power system. Finally, the effectiveness of the proposed controller design methodology is demonstrated through simulation example. Obtained results demonstrate the superiority of the proposed strategy.

Simulation Research on the Optimization of Servo System Based on Hybrid Fuzzy Control Algorithm

In servo system, aiming at the defects of the selection of parameters including scale factor and quantitative factor, which depend on experience seriously and lack standards, a parameter optimization method of servo system based on genetic algorithm and particle swarm algorithm is proposed. This method not only greatly reduces the maximum tracking error and optimizes static and dynamic characteristics, it can also effectively overcome the influence of nonlinear factors disturbances from ripple torque. This method makes the system basically satisfy the nonlinear and time-varying control requirements. Finally, the effectiveness and practicability of the proposed method are validated through simulation.

Optimum Design of Fractional-Order Hybrid Fuzzy Logic Controller for a Robotic Manipulator

The robotic manipulators are complex and coupled nonlinear systems. Therefore, the designing of an effective controller for these systems is quite complicated. The main hurdle in operating these systems is the inter-linkage between the links, and this can be removed by using any decoupling method. The decoupling between the links is not a good idea from the viewpoint of practical applications. In this paper, a fractional-order hybrid fuzzy logic controller (FOHFLC) scheme is developed for a two-degree-of-freedom rigid planar robotic manipulator with payload (2-DOF RPRMWP) plant for the trajectory tracking. The cuckoo search algorithm (CSA) is utilized for finding the optimal parameters of the proposed approach. For witnessing the effectiveness, the performance of proposed FOHFLC scheme is compared with integer-order hybrid FLC (IOHFLC) approach and conventional PID controller. The robustness testing is investigated for parameter variations and disturbance rejection for the proposed controller schemes.

성능개선을 위한 룩업테이블 하이브리드 퍼지제어 시스템

성능개선을 위한 룩업테이블 하이브리드 퍼지제어 시스템

Optimal wide-area hybrid fuzzy controller to enhance the stability in power system

ABSTRACTTo stabilise power oscillation, power system stabilizer is often used as an effective device to enhance the damping of electromechanical oscillations in power systems. This device is working with small-signal stability, which is often applied as part of excitation control system. Different methods have been proposed to demonstrate the effectiveness of remote signals application in increasing damping of power system. In this paper, we used both local and remote signals control based on fuzzy controller and wide-area control, respectively. Accordingly, Takagi Sugeno controller based an intelligent algorithm and clustering algorithm is optimised. A global signal from the centralised controller is employed in wide-area control scheme to damp out the inter-area mode as well as local mode of oscillations. To demonstrate the capability of proposed strategy, three case studies have been used in this paper. The results obtained demonstrate the validity of the proposed model.

Designing robust model reference hybrid fuzzy controller based on LYAPUNOV for a class of nonlinear systems

Designing robust model reference hybrid fuzzy controller based on LYAPUNOV for a class of nonlinear systems

Passive Identification is Non Stationary Objects With Closed Loop Control

Typically chemical processes have significant nonlinear dynamics, but despite this, industry is conventionally still using PID-based regulatory control systems. Moreover, process units are interconnected, in terms of inlet and outlet material/energy flows, to other neighbouring units, thus their dynamic behaviour is strongly influenced by these connections and, as a consequence, conventional control systems performance often proves to be poor. However, there a hybrid fuzzy PID control logic, whose tuning parameters are provided in real time. The fuzzy controller tuning is made on the basis of Mamdani controller, also exploiting the results coming from an identification procedure that is carried on when an unmeasured step disturbance of any shape affects the process behaviour. This paper presents procedure for identifying technological object control in a closed loop, i. e. that operates the automated control system. The variation in the controlled variable, caused by the change of the nonmeasurable disturbance, is considered the initial signal for the identification procedure. The parameters of the control object are found by optimization method Levenberg-Marquardt.

Fuzzy Adaptive Control System of a Non-Stationary Plant

This paper proposes a hybrid fuzzy PID control logic, whose tuning parameters are provided in real time. The fuzzy controller tuning is made on the basis of Mamdani controller. In addition, this paper compares a fuzzy logic based PID with PID regulators whose tuning is performed by standard and well-known methods. In some cases the proposed tuning methodology ensures a control performance that is comparable to that guaranteed by simpler and more common tuning methods. However, in case of dynamic changes in the parameters of the controlled system, conventionally tuned PID controllers do not show to be robust enough, thus suggesting that fuzzy logic based PIDs are definitively more reliable and effective.

Some investigations on hybrid fuzzy IPD controllers for proportional and derivative kick suppression

Proportional and derivative kick i.e., a large change in control action of a proportional plus integral plus derivative (PID) controller due to a sudden change in reference set-point is generally undesired in process industry. Therefore, the structure of conventional parallel PID controller is modified to integral minus proportional derivative (I-PD) controller. In this paper, three hybrid fuzzy IPD controllers such as a fuzzy I-fuzzy PD (FI-FPD) controller and its hybrid combinations with its conventional counterpart such as fuzzy I-PD (FI-PD) and I-fuzzy PD (I-FPD) are presented in view of above industrial problem. These controllers are based upon the counterpart conventional I-PD controller and contains analytical formulae. Computer simulations are carried out to evaluate the performance of hybrid fuzzy controllers along with conventional I-PD and PID controllers for set-point tracking and disturbance rejection for an induction motor in closed loop using LabVIEW™ environment. The gains of conventional and hybrid fuzzy controllers are tuned using genetic algorithm (GA) for minimum overshoot and settling time. It has been observed that hybrid fuzzy controllers along with the conventional I-PD controller significantly remove the kick from the control action in reference set-point tracking. However, in disturbance rejection, I-PD and FI-PD controllers fail to eliminate the kick from the control signal. In contrast, FI-FPD and I-FPD controllers considerably reduced spikes from the control action in disturbance rejection. Among the conventional and hybrid fuzzy IPD controllers, FI-FPD demonstrates much better set-point tracking and disturbance rejection response with spike free control action.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.

Energy conservation for refrigeration systems by means of hybrid fuzzy adaptive control techniques

Most vapour compression refrigeration systems still operate under on–off control, although it is well known that the application of any other control method could result in improved COP. For that purpose, the present paper experimentally studies the use of adaptive fuzzy hybrid control and design of experiments techniques, as well as the application of the response surface methodology, in a 5-ton vapour compression system with a variable speed compressor and an electronic expansion valve. Evaporation temperature and evaporator overall conductance were found to be the most relevant input parameters to the fuzzy hybrid control system, where the optimal trajectory was sought without taking into account the elapsed time. Results have shown that the knowledge of the most relevant parameter of the system allowed for the control system to seek high COP zones. It has been found that this type of technique does not jeopardize the control performance, which remains robust.

A hybrid fuzzy sliding-mode control for a three-phase shunt active power filter

Power quality has become an important issue in recent years due to the increasing use of solid-state switching devices and other nonlinear loads. These non-linear loads generate undesirable harmonics causing distortions in the current and voltage waveforms.Shunt active power filters have proven very effective to mitigate harmonics. This paper describes a hybrid fuzzy sliding-mode controller (HFSMC) for a three phase shunt active filter to enhance the power quality and improve the reactive power profile in the distribution grid.The proposed method attenuates the effect of both uncertainties and external disturbances, and eliminates the chattering phenomenon induced by classical sliding-mode control. Simulation are presented to demonstrate the effectiveness of the proposed control strategy. The results show that the proposed HFSMC control scheme is able to mitigate harmonic distortions, and provide reactive power compensation and power quality improvement.

Hybrid Fuzzy Controller Based Frequency Regulation in Restructured Power System

This paper discusses the implementation of Load Frequency Control (LFC) in restructured power system using Hybrid Fuzzy controller. The formulation of LFC in open energy market is much more challenging; hence it needs an intelligent controller to adapt the changes imposed by the dynamics of restructured bilateral contracts. Fuzzy Logic Control deals well with uncertainty and indistinctness while Particle Swarm Optimization (PSO) is a well-known optimization tool. Abovementioned techniques are combined and called as Hybrid Fuzzy to improve the dynamic performance of the system. Frequency control of restructured system has been achieved by automatic Membership Function (MF) tuned fuzzy logic controller. The parameters defining membership function has been tuned and updated from time to time using Particle Swarm Optimization (PSO). The robustness of the proposed hybrid fuzzy controller has been compared with conventional fuzzy logic controller using performance measures like overshoot and settling time following a step load perturbation. The motivation for using membership function tuning using PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes is tested on a two-area restructured power system.

Hybrid Control Using Adaptive Fuzzy Sliding Mode for Diagnosis of Stator Fault in PMSM

In nonlinear control systems when we have a non-constant parameters, conventional control laws may be insufficient because they are not robust especially when the requirement on accuracy and other characteristics dynamic systems are strict. We must use control laws insensitive against to parameter variations, disturbance and nonlinearities. For this purpose, several tools are proposed in the literature, which is quoted a hybrid fuzzy logic and variable structure control (Fl_VSC). This per presents an application of the fuzzy logic scheme to control the speed of PMSM by taking account of the presence of interturn short circuit fault. We were interested in the sliding mode control (SMC) of the PMSM using controller’s fuzzy logic controller (FLC) and Adaptive fuzzy logic controller (AFLC). The combination of these two theories has given great performance with fast dynamic response without overshoot. As it has a very robust control, insensitive against to parameters variation and external disturbances. Simulation results confirm the choice of hybrid controllers compared with the conventional controllers and grants a robust performance and precise response to the reference model regardless of load disturbance, stator faults and PMSM parameter uncertainties.

Attitude synchronous tracking control of double shaking tables based on hybrid fuzzy logic cross-coupled controller and adaptive inverse controller

The purpose of shaking tables is to replicate the desired motion to specimen, which needs to ensure not only the synchronization precision of two tables, but the tracking precision for the desired signal. Due to the nonlinearity of system and eccentric of load masses, both tracking and synchronous accuracy are poor. To solve this problem, this article proposes a novel hybrid controller combined a hybrid fuzzy PD cross-coupled controller (CCC) with an adaptive inverse controller (AIC). Based on state variable error optimal control idea, a 2-stage parallel hybrid fuzzy logic controller (FLC) composed of fuzzy PD and accelerated fuzzy PD is proposed to CCC to reduce synchronization error. In order to improve the tracking accuracy, an AIC based on recursive extended least square (RELS) algorithm is used to estimate the close-loop inverse transfer functions of double shaking tables to adaptively tune the drive signals. The combination of hybrid fuzzy PD CCC and AIC has the advantage of integrating a superiority of the two control techniques for better control performance. The procedure of the proposed control scheme is programmed, and tests are carried out in various conditions. The test results demonstrated the viability of the proposed hybrid control scheme.

Fractional-order Proportional-integral-derivative-based Automatic Generation Control in Deregulated Power Systems

—In this article, implementation of a fractional-order proportional-integral-derivative controller is proposed as supplementary automatic generation control of interconnected multi-area deregulated power systems that operates under the effects of bilateral contracts on the dynamics. The tuning of the fractional-order proportional-integral-derivative controller parameters is formulated as an optimization problem and solved by employing a genetic algorithm. The traditional automatic generation control loop incorporated with the concept of the distribution company participation matrix and fractional-order proportional-integral-derivative supplementary controller is simulated for different operating cases; a comparison among the conventional integral controller, hybrid fuzzy proportional-integral controller, genetic algorithm-tuned proportional-integral controller, and genetic algorithm-tuned proportional-integral-derivative controllers is presented. The simulation results show that the system employing a genetic algorithm-tuned fractional-order proportional-integral-derivative controller has better performance than the integer-order hybrid fuzzy proportional-integral, genetic algorithm-tuned proportional-integral, and genetic algorithm-tuned proportional-integral-derivative controllers in terms of settling time and overshoot.

Transient Stability Enhancement Using Matrix Converter Based UPFC with Intelligent Controlling Techniques

This paper presents a matrix converter based UPFC for enhancing the transient stability. Conventional methods use a two step based UPFC (DC-AC-DC). In the proposed model the conventional UPFC is replaced by a Matrix Converter which is controlled with two different controllers which include fuzzy logic controller and the other with an added integrator which is referred to be a HYBRID fuzzy logic controller. In this paper, the working of matrix converter based UPFC with the two controller techniques under certain disturbances is observed using the MATLAB software and the results are verified.

Load frequency control of power system under deregulated environment using optimal firefly algorithm

Abstract In this paper, a novel Firefly Algorithm (FA) optimized hybrid fuzzy PID controller with derivative Filter (PIDF) is proposed for Load Frequency Control (LFC) of multi area multi source system under deregulated environment by considering the physical constraints such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB) nonlinearity. As the effectiveness of FA depends on algorithm control parameters such as randomization, attractiveness, absorption coefficient and number of fireflies are systematically investigated, the control parameters of FA are tuned by carrying out multiple runs of algorithm for each control parameter variation then the best FA control parameters are suggested. Additionally, the superiority of the FA is demonstrated by comparing the results with tuned Genetic Algorithm (GA). To investigate the effectiveness of the proposed approach, time domain simulations are carried out considering different contracted scenarios and the comparative results are presented. Further, sensitivity analysis is performed by varying the system parameters and operating load conditions. It is observed from the simulation results that the designed controllers are robust and the optimum gains of proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Finally, the effectiveness of the proposed control scheme is evaluated under random step load disturbance.