Advantages Of Fuzzy Control Research Articles

Fully Automated RF/Microwave Filter Tuning by Extracting Human Experience Using Fuzzy Controllers

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The paper introduces modeling of human experience by linguistic if-then rules in terms of fuzzy logic controllers for tuning RF/Microwave filters. The approach could be used for any circuit or system tuning problem that involves human expert information provided that the expert information could be described in terms of linguistic if-then rules. The tuning approach is both theoretically and practically illustrated in this paper. The tuning is done in two stages both taking advantage of fuzzy controllers. The first stage uses the phase response of the filter, while the second stage uses the magnitude response of the filter for adjustment of the tuning screws. A fully automated experimental setup is implemented by high resolution motors with flexible leads to make the tuning possible. 3-pole and 7-pole Chebyshev waveguide filters are used to demonstrate the concept. The measured results prove the validity of the method. </para>

Hierarchical control of combined hybrid electric vehicle

This paper describes a novel strategy developed for optimising the energy flow in a combined hybrid electric vehicle (CHEV) structure. This method implemented an online energy management by a hierarchical hybrid controller between dual sources in this kind of hybrid systems. This structure included two energy sources, the battery and the stack of fuel cells, and its power train system is based on an electric motor (EM) and internal combustion engine (ICE) in a parallel combination. The proposed control method involves a supervisory controller which in the first layer captures all the possible operation modes. In the second layer, an advanced fuzzy hybrid controller has been developed for each of the defined modes. Finally in the third layer of controller, there are local controllers to regulate the set points of each subsystem to reach the best performance and acceptable operation indexes. The simulation results confirm the feasibility and encourage more research toward an actual application.

Intelligent power management strategy of hybrid distributed generation system

This paper describes a novel control strategy for active power flow in a hybrid fuel cell/battery distributed generation system. The method introduces an on-line power management by a hierarchical hybrid controller between dual energy sources that consist of a battery bank and a solid oxide fuel cell (SOFC). The proposed method includes an advance supervisory controller in the first layer which captures all of the possible operation modes. This layer has been developed by Stateflow toolbox and prepares a proper supervisory environment for this complex structure. In the second layer, an advanced fuzzy controller has been developed for power splitting between battery and fuel cell. With regards to the operation modes, the upper layer makes decision to choose the switching chain rules and corresponding controller in the second layer. Finally in the third layer, there are local controllers to regulate the set points of each subsystems to reach the best performance and acceptable operation indexes. Simulation results of a test system illustrate improvement in the operation efficiency of the hybrid system and the battery state of charge has been maintained at a reasonable level.

Comparing the energy performance of an electrochromic window under various control strategies

Electrochromic glazing can involve substantial energy consumption in the building sector with their optical properties driven either by various occupant needs or environmental conditions. This paper presents comparison of ten different control strategies developed for such a glazing system in terms of specific energy consumption of a PASSYS test cell where the glazing was installed. The control strategies include scheduled ON–OFF controllers, a PID and advanced fuzzy controllers which were developed using experimental data. We used energy simulation to analyse the annual heating, cooling and lighting demands investigating the influence of each control strategy to the thermal behaviour of the building.

An educational tool for fuzzy control

This paper presents an educational library to be used with the MATLAB/Simulink package from the Mathworks company for the design of fuzzy controllers. This free library, named FlouLib, has its foundations in a clear representation of the fuzzy interfaces (fuzzification, inference, defuzzification). First, Mamdani-type conventional fuzzy logic controllers are presented, including when rulebases are chained. Then, from the modal equivalence principle, advanced Takagi-Sugeno fuzzy controllers are introduced especially those relying on input-output linearization techniques. Examples, all available in FlouLib demos, are used to show the potentialities of FlouLib for control engineering curricula.

Comparison of two approaches to automated PI controller tuning for an industrial weigh belt feeder

In this paper, two advanced PI controller tuning methods, unfalsified control and fuzzy control, are applied to an industrial weigh belt feeder that has significant nonlinearities. Both methods do not require an explicit plant model. The advantage of the unfalsified PI control design method is that it is able to directly incorporate multiple performance criteria, while the advantage of fuzzy logic is that it is able to directly incorporate human reasoning in the design process. Experimental results exhibit the effectiveness of both control methods. A detailed comparison of the two approaches is given in the areas of allowed design specifications, process knowledge requirements, computational requirements, controller development effort, transient performance, and the ability to handle motor saturation.

アドバンストファジィ制御 : ファジィモデルに基づく制御( 最新のファジィシステム技法特集号)

アドバンストファジィ制御 : ファジィモデルに基づく制御( 最新のファジィシステム技法特集号)

Fuzzy logic controlled shunt active power filter for power quality improvement

The simulation and experimental study of a fuzzy logic controlled, three-phase shunt active power filter to improve power quality by compensating harmonics and reactive power required by a nonlinear load. The advantage of fuzzy control is that it is based on a linguistic description and does not require a mathematical model of the system. The fuzzy control scheme is realised on an inexpensive dedicated micro-controller (INTEL 8031) based system. The compensation process is based on sensing line currents only, an approach different from conventional methods, which require harmonics or reactive volt-ampere requirement of the load. The performance of the fuzzy logic controller is compared with a conventional PI controller. The dynamic behavior of the fuzzy controller is found to be better than the conventional PI controller. PWM pattern generation is based on carrierless hysteresis based current control to obtain the switching signals. Various simulation and experimental results are presented under steady state and transient conditions.

FUZZY MODELING AND CONTROLLING OF A FAN-COIL

Fuzzy models and controllers are represented by if-then rules and thus can provide a user-friendly and understandable representation of combined quantitative and qualitative description. The qualitative rules result in a quantitative non-linear controller well suited to nonlinear systems controlling thermal comfort with vague defined objectives as fan-coils used in solar energy systems. The fuzzy models are achieved through identification by varying the inputs so that the fan-coil reaches the states encountered in normal operation. These models may be used for control or for simulation. On its domain of validity, the fuzzy controller behaves better then a classical controller. In fact, the main advantage of fuzzy controller is the easiness of introducing operating modes and poor defined objectives specific for solar energy systems such as freeze and over-temperature protection, or draining.

COMPARATIVE STUDY OF FUZZY CONTROL, PID CONTROL, AND ADVANCED FUZZY CONTROL FOR SIMULATING A NUCLEAR REACTOR OPERATION

Based on the background of fuzzy control applications to the first nuclear reactor in Belgium (BR1) at the Belgian Nuclear Research Centre (SCK˙CEN), we have made a real fuzzy logic control demo model. The demo model is suitable for us to test and compare some new algorithms of fuzzy control and intelligent systems, which is advantageous because it is always difficult and time-consuming, due to safety aspects, to do all experiments in a real nuclear environment. In this paper, we first report briefly on the construction of the demo model, and then introduce the results of a fuzzy control, a proportional-integral-derivative (PID) control and an advanced fuzzy control, in which the advanced fuzzy control is a fuzzy control with an adaptive function that can self-regulate the fuzzy control rules. Afterwards, we present a comparative study of those three methods. The results have shown that fuzzy control has more advantages in terms of flexibility, robustness, and easily updated facilities with respect to the PID control of the demo model, but that PID control has much higher regulation resolution due to its integration term. The adaptive fuzzy control can dynamically adjust the rule base, therefore it is more robust and suitable to those very uncertain occasions.

An advanced fuzzy controller

A methodology for the reduction of complexity of the fuzzy if-then rules for a robust controller system is presented. An analysis of the fuzzy if-then rules is performed by viewing the fuzzy sets in the rules as crisp sets. The knowledge of the analysis is used to reduce the number of variables and the number of fuzzy if-then rules. By applying fuzzy logic to the reduced linguistic if-then rules, a robust controller system based on fuzzy if-then rules is reconstructed. The simulation results show that the reconstructed controller is more efficient and performs as well as the original controller.

カバリングマシンの自動糸交換装置の開発 （第６報）ファジィ手法を用いた自律式作業台車の走行制御

Doffing operation for the covering machine has been already automated by the auto drawing-in apparatus loaded on the autonomous vehicle. The vehicle repeats moving and stop while measuring its position and attitude with a pair of laser displacement sensors. In this report, control methods for this autonomous vehicle are investigated to approach the initial operating position rapidly, to break away at the end of the covering machine, and to turn around it.Fuzzy control was applied to the path tracking that the autonomous vehicle approaches the initial operating position of the covering machine. It obtains much rapider response than the method in which the front wheel takes on the reference path.Using this advantage of fuzzy control, it enables the vehicle to turn back over the side of the covering machine with stability. By means of this, the autonomous vehicle can directly use the machine frame as a guide way without any additions extraordinary to the covering machine.

Design of a static reactive power compensator using fuzzy sliding mode control

This paper demonstrates a fuzzy sliding mode control (FSMC) scheme for a static reactive power compensator (static VAR compensator or SVC) to improve the damping of a synchronous generator. A robust sliding regime is derived to guarantee the stability of the proposed FSMC under parameter uncertainties. Two types of FSMC, the fuzzy switching gain compensation and the fuzzy control signal compensation, are recommended to regulate the reactive power of the SVC. A synchronous generator system with the proposed FSMC-SVC has been studied and its dynamic responses are simulated. The results show that the suggested FSMC scheme possesses the advantages of fuzzy control and sliding mode control, e.g. insensitivity to parameter variations and load disturbances. Note that the dynamic performance of the synchronous machine system can be improved dramatically over a wide range of operating conditions. Furthermore, for simplification of practical implementation, the reducing switches (or local feedback) control is adopted.

Special Issue on Fuzzy Control

This special issue is devoted to the study of Fuzzy Control applied to robotics and mechatronics. In particular, it contains a collection of fuzzy-neural network approaches, together with the conventional fuzzy reasoning or new approaches. Since the first pioneering work on fuzzy sets and fuzzy logic reported in 1965 by Zadeh, many control application papers have been published with the fundamental fuzzy controllers based on the so-called Mamdani's min-max centroidal method, the TakagiSugeno's functional reasoning, and the simplified reasoning. However, it is recognized that much trial and error is necessary in the design of the conventional fuzzy controller, because the fuzzy reasoning methods mentioned above are not fundamentally related to any control or system theory. In addition, it should be noted that the total number of control rules grows exponentially as the number of input variables to the conventional fuzzy reasoning increases. Thus, in order to improve the conventional approach and develop the new approach for large-scale systems, most current work on fuzzy control is concerned with an effective design, construction, or analysis of the fuzzy controller by invoking the neural network theory, genetic algorithm, and other control or system theories. Although the literature, both in Japanese and in English, on fuzzy control and applications is now very rich, I believe that this special issue provides an important impact on the advanced fuzzy control. This issue would not have been possible without the enthusiastic support of the contributors. I am indebted to all of them for their up-to-date contributions and to the editorial staff for care throughout the editorial and printing process.

Application of fuzzy control to an inserting operation

Abstract Because of the difficulty of dynamic equations for the inserting operation and the advantage of fuzzy control for easy execution without knowledge of the mathematical models. We used the force feedback signal measured by a force sensor and a fuzzy controller to regulate the position of the peg. The control strategies include two control loops; in one a PID position controller move the peg vague position near to the hole, and in the other the fuzzy controller regulates the final position according to contact force. Between the two control loops we use an index to activate a switch. To verify the proposed control strategy, we performed experiments with a Cartesian manipulator system driven by AC servo-motors. The experimental results reveal that we can insert a peg into a hole with a fitting clearance less than 0.01 mm.

An advanced fuzzy controller for traffic lights

In the paper a realistic approarh to fuzzy control of urban road traffic lights is described. Fuzzy application is encouraging since the design procedure of vehicle actuated traffic light systems is very transparently, and an adaptation to changing situations of traffic is easily to accomplish. The paper presents simulation results obtained for an intersection with 12 main direction traffic flows. The fuzzy controller proposed switches to a two-state, a three-state or a four-state control. The results with respect to the average loss of traveltime are very promising in comparison with other controllers applied to the same simulation example.