Fuzzy Logic Control Strategy Research Articles

Automobile Brake-by-Wire Control System Design and Analysis

The automobile brake-by-wire (BBW) system, which is also called the electromechanical brake system, has become a promising vehicle braking control scheme that enables many new driver interfaces and enhanced performances without a mechanical or hydraulic backup. In this paper, we survey BBW control systems with focuses on fault tolerance design and vehicle braking control schemes. At first, the system architecture of BBW systems is described. Fault tolerance design is then discussed to meet the high requirements of reliability and safety of BBW systems. A widely used braking model and several braking control schemes are investigated. Although previous work focused on antilock and antislip braking controls on a single wheel basis, we present a whole-vehicle control scheme to enhance vehicle stability and safety. Simulations based on the whole-vehicle braking model validate a proposed fuzzy logic control scheme in the lateral and yaw stability controls of vehicles.

Hybrid fuzzy logic control with genetic optimisation for a single-link flexible manipulator

To reduce the end-point vibration of a single-link flexible manipulator without sacrificing its speed of response is a very challenging problem since the faster the motion, the larger the level of vibration. A conventional controller can hardly meet these two conflicting objectives simultaneously. This paper presents a genetic algorithm (GA)-based hybrid fuzzy logic control strategy to achieve that goal. A proportional-derivative (PD) type fuzzy logic controller utilising hub-angle error and hub-velocity feedback is designed for input tracking of the system. GA is used to extract and optimise the rule base of the fuzzy logic controller. The GA fitness function is formed by taking the weighted sum of multiple objectives to trade off between system overshoot and rise time. Moreover, scaling factors of the fuzzy controller are tuned with GA to improve its performance. A GA-based multi-modal command shaper is then designed and augmented with the fuzzy logic controller to reduce the end-point vibration of the system. The performance of the hybrid control scheme is assessed in terms of its input-tracking capability and vibration suppression at the end point. A significant amount of vibration reduction has been achieved at the end point, especially at the first three resonance modes of the rig structure, with satisfactory level of overshoot, rise time, settling time, and steady-state error.

An Investigation Into the Application of Fuzzy Logic Control to Industrial Gas Turbines

This paper investigates the feasibility benefits of applying fuzzy logic control (FLC) strategies for use with industrial gas turbines. Our main objective is to investigate different designs methods, design implement an FLC strategy, plant simulation in a test environment optimize the FLC, conduct tests to compare the FLC with conventional controls in scenarios relevant to the application. We have designed, implemented, and tested our simulation to the exhaust temperature control problem of a gas turbine problem. The FLC, plant simulation, existing control configuration, and integrated test environment were developed in Java. Heuristic methods were used to optimize the FLC, which proved time consuming. The paper illustrates that while implementation of the FLC is feasible, it requires more effort than the conventional controls examined.

Simulation of a suspension system with adaptive fuzzy active force control

This paper presents the design of a new and novel control technique applied to an active suspension system of a quarter car model using adaptive fuzzy (AF) logic and active force control (AFC) strategies. The two main advantages of the proposed method are the simplicity of the control law and low computational burden. The overall control system essentially comprises three feedback control loops, namely the innermost PI control loop for the force tracking of the hydraulic actuator, intermediate AFC control loops for the compensation of the disturbances and outermost AF control loop for the computation of the optimum target/commanded force. AF algorithms were used to approximate the estimated mass of the hydraulic actuator in the AFC loop. The performance of the proposed control method was then simulated, evaluated and later compared to examine the effectiveness of the system in suppressing the undesirable effects of the suspension system. It was found that the active suspension system with Adaptive Fuzzy Active Force Control (AF-AFC) yields superior performance compared to the AF system without AFC and the passive counterparts.

Hybrid fuzzy logic control strategies for hot water district heating systems

Hybrid fuzzy logic control (FLC) strategies for hot water district heating (HWDH) systems are designed. A non-linear dynamic model of a HWDH system (heated floor area 90 000 m2) with 21 dynamic equations is developed. The dynamic model consists of a boiler, pipe network, heaters and buildings. Six different hybrid control strategies involving FL and PI control were designed to regulate fuel firing rate, water flow rate or water temperature in the system. Simulation results show that the control strategies, based on the use of return water temperature and indoor air temperature predictor (IATP), give good zone temperature control. Pumping costs were reduced by modulating water flow rate in the system. Results also showed that the proposed hybrid control strategies could save up to 17% energy in buildings.

A fuzzy logic‐controlled SMES for damping shaft torsional oscillations of synchronous generator

AbstractThis paper presents a fuzzy logic control scheme for the superconducting magnetic energy storage (SMES) based on a PWM voltage source converter and a two‐quadrant chopper using an insulated‐gate‐bipolar‐transistor (IGBT) to dampen turbine‐generator shaft torsional oscillations. Simulation results of balanced faults in a single machine connected to an infinite bus system show that the proposed fuzzy logic‐controlled SMES is effective in damping shaft torsional oscillations of synchronous generators (GENs). © 2006 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

A PI-fuzzy logic controller for the regulation of blood glucose level in diabetic patients

This manuscript investigates different fuzzy logic controllers for the regulation of blood glucose level in diabetic patients. While fuzzy logic control is still intuitive and at a very early stage, it has already been implemented in many industrial plants and reported results are very promising. A fuzzy logic control (FLC) scheme was recently proposed for maintaining blood glucose level in diabetics within acceptable limits, and was shown to be more effective with better transient characteristics than conventional techniques. In fact, FLC is based on human expertise and on desired output characteristics, and hence does not require precise mathematical models. This observation makes fuzzy rule-based technique very suitable for biomedical systems where models are, in general, either very complicated or over-simplistic. Another attractive feature of fuzzy techniques is their insensitivity to system parameter variations, as numerical values of physiological parameters are often not precise and usually vary from patient to another. PI and PID controllers are very popular and are efficiently used in many industrial plants. Fuzzy PI and PID controllers behave in a similar fashion to those classical controllers with the obvious advantage that the controller parameters are time dependant on the range of the control variables and consequently, result in a better performance. In this manuscript, a fuzzy PI controller is designed using a simplified design scheme and then subjected to simulations of the two common diabetes disturbances—sudden glucose meal and system parameter variations. The performance of the proposed fuzzy PI controller is compared to that of the conventional PID and optimal techniques and is shown to be superior. Moreover, the proposed fuzzy PI controller is shown to be more effective than the previously proposed FLC, especially with respect to the overshoot and settling time.

Fuzzy logic controller applied to a variable geometry turbine turbocharger

This paper provides an adaptive technique for the control of a variable geometry turbine (VGT) in a turbocharged compression ignition engine. The adaptive control is based on a fuzzy logic control scheme and a least-squares parameter estimator algorithm. In order to test the performance of the proposed control technique, a numerical model of the engine has been used, which employs a thermodynamic (zero-dimensional) approach. The paper will show that the fuzzy logic control technique is able to take into account the non-linearity of the controlled system and to reject white noise affecting the measurement chain.

Comparative Study on Vibration Control of a Scaled Bridge Using Fail-Safe Magneto-Rheological Fluid Dampers

This work presents vibration control of a scaled bridge using fail-safe magneto-rheological fluid (MRF) dampers. A fail-safe MRF damper refers to a device that retains a minimum required damping capacity in the event of a power or electronic system failure. Energy minimization, Lyapunov, fuzzy logic, and variable structure system (VSS) fuzzy logic control strategies are employed to study the performance of this system under a random base excitation. To better understand the overall system behavior, a theoretical frequency response analysis is also presented. It is experimentally demonstrated that semiactive control systems utilizing MRF dampers can reduce the relative deck displacement while the absolute deck acceleration is relatively unaffected. In addition, it is shown that the fuzzy logic and VSS fuzzy logic methods are simple to implement, effective and require far less input energy than other control cases.

Adaptive Fuzzy-Logic SVC Damping Controller Using Strategy of Oscillation Energy Descent

A novel concept called the bus power oscillation energy function is introduced in this paper. On this basis, a control strategy, the oscillation energy function descent approach, is proposed for developing an efficient static VAR compensator (SVC) supplementary damping controller. Using the strategy, a fuzzy-logic adaptive SVC control scheme is developed. To enhance the performance of the damping controller, an additional fuzzy-logic control unit is introduced to adaptively adjust the control gain factor in real time according to the magnitude of system oscillations at each moment. The adaptive approach overcomes the drawback of fuzzy-logic control schemes with constant gain factor. Simulation results with and without the adaptive control unit on the 10-generator New England systems are reported to show the effect of the adaptive control techniques. The satisfactory performance of the controller validates that the oscillation energy decent control strategy is useful to design FACTS supplementary damping controllers.

Fuzzy logic control of fuel cell for stand-alone and grid connection

Fuel cells have become one of the major areas of research in the academia and the industry with the numerous advantages they provide over the batteries and especially over the other small-scale sources of electricity including the photovoltaic and solar cells. Fuel cells generate electricity from hydrogen by a chemical process and are environmentally safe and efficient. Fuel cells have numerous stand-alone and grid-connected applications. The aim of the paper is to achieve the control of the fuel cell for stand-alone and grid connection. This is achieved by designing a suitable power conditioning unit. The power conditioning unit is needed for processing of the raw power output of the fuel cell in order to make it usable. The power conditioning unit might have only dc/dc converter or the two stages of dc/dc converter and dc/ac inverter. For the stand-alone part, the concentration is on the controlled direct current (dc) power, thus, only a boost converter (dc/dc) stage is used. For the grid interface of the fuel cell, controlled alternating current (ac) power is needed at the interface point of the fuel cell and the utility grid; thus, both stages, boost converter as well as the inverter (dc/ac), are needed. A power conditioning unit is designed for the solid oxide fuel cell, which can be used for other fuel cells with converter and the inverter of different ratings, but the control strategy will remain the same. The fuzzy logic control strategy is used for designing the controllers for both the stages.

Controlling torque distribution for Parallel Hybrid Vehicle based on Hierarchical Structure Fuzzy Logic

The Hierarchical Structure Fuzzy Logic Control (HSFLC) strategies of torque distribute for Parallel Hybrid Electric Vehicle (PHEV) in the mode of operation of the vehicle i. e. , acceleration, cruise, deceleration etc. have been studied. Using secondly developed the hybrid vehicle simulation tool ADVISOR, the dynamic model of PHEV has been set up by MATLAB/SIMULINK. The engine, motor as well as the battery characteristics have been studied. Simulation results show that the proposed hierarchical structured fuzzy logic control strategy is effective over the entire operating range of the vehicle in terms of fuel economy. Based on the analyses of the simulation results and driver’s experiences, a fuzzy controller is designed and developed to control the torque distribution. The controller is evaluated via hardware-in-the-loop simulator (HILS). The results show that controller verify its value.

Fuzzy logic control schemes for static VAR compensator to control system damping using global signal

This paper presents a simple way of achieving damping of phase angle oscillations and improving transient stability of an interconnected power system network using fuzzy logic. The output of the fuzzy logic controller is fed to an already existing Static VAR compensator (SVC). Different input measurements and their combinations are tested and the effectiveness of the fuzzy controller for achieving stability has been demonstrated on a four-generator, two-area system using simulation studies. The inputs tested are line power, angular speed, machine angle, frequency and combination of these. The paper also compares the damping effectiveness of the fuzzy controlled SVC (FCS) and a conventional power system stabilizer (CPSS).

Residential fuel cell energy systems performance optimization using “soft computing” techniques

Stationary residential and commercial fuel cell cogeneration systems have received increasing attention by the general public due to their great potential to supply both thermal and electrical loads to the dwellings. The reported number of field demonstration trials with grid connected and off-grid applications are under way and valuable and unique data are collected to describe the system’s performance. While the single electricity mode of operation is relatively easy to introduce, it is characterized with relatively low efficiency performance (20–35%). The combined heat and power generation mode is more attractive due to higher efficiency +60%, better resources and fuel utilization, and the advantage of using a compact one box/single fuel approach for supplying all energy needs of the dwellings. While commercial fuel cell cogeneration applications are easy to adopt in combined mode of operation, due to the relatively stable base power/heat load throughout the day, the residential fuel cell cogeneration systems face a different environment with uneven load, usually two peaks in the morning and in the evening and the fact that the triple load: space, water and power occur at almost the same time. In most of the cases, the fuel cell system is not able to satisfy the triple demand and additional back up heater/burner is used. The developed ‘’soft computing” control strategy for FC integrated systems would be able to optimize the combined system operation while satisfying combination of demands. The simulation results showed that by employing a generic fuzzy logic control strategy the management of the power supply and thermal loads could be done appropriately in an optimal way, satisfying homeowners’ power and comfort needs.

Power system damping control through fuzzy static VAR compensator design including crisp optimum theory

Static VAR compensators (SVC) are known to improve voltage and reactive power flow in a power system. Properly controlled SVCs can also provide damping to power system oscillations. This article presents a fuzzy logic SVC controller design for damping control considering different input signals. A fuzzy logic control strategy has been developed that uses crisp optimum control theory to obtain the best combination of speed deviation and acceleration signals so as to stabilize the system in minimum time. The proposed fuzzy controller requires much less fuzzy variables, and is computationally very efficient. Simulation results show that the crisp optimum control based fuzzy logic controller provides excellent damping to the power system compared to the general fuzzy strategies.

Brief communication: Uniform ultimate boundedness of a fuzzy logic controlled industrial robot

AbstractThis article addresses the proof of uniform ultimate boundedness of a fuzzy logic controller plus a computed torque control scheme applied to trajectory tracking control of robotic manipulators. Further improvement of the performance of this fuzzy logic control scheme is achieved through automatic tuning of a weight parameter α leading to a self‐tuning fuzzy logic compensator. Experimental results demonstrate the effectiveness of the computed torque and fuzzy compensation scheme, as well as the self‐tuning fuzzy logic controller, applied to an industrial CRS Robotics Corporation A460 robot during a trajectory tracking task. © 2001 John Wiley & Sons, Inc.

Application of Fuzzy Logic Control to Tea Rolling Process

This paper presents real-time fuzzy logic control for press cap roller used in tlle rolling process. The system is installed at tea processing facilities in Tea Research Institute, Gambung, Indonesia. Fuzzy logic control methodology is applied to achieve the desired temperature in press cap roller machineused in black tea rolling process. Mamdani-type fuzzy logic control strategy is implemented in software running on PC

Comparison of an adaptive stabilizer and a fuzzy logic stabilizer for superconducting generator governor control

Abstract This paper describes the development and application of two different control schemes for stability enhancement of a superconducting generator (SCG). The findings of study of the system performance with an adaptive scheme and a fuzzy logic control scheme are presented and compared. In the first scheme, the stabilizing signal is based on the minimization of a modified version of a quadratic performance index, which includes an additional weighted derivative term. In the second scheme, the stabilizing signal is based on the instantaneous speed deviation and acceleration of the SCG using two fuzzy membership functions and a few simple control rules. A new tuning parameter is introduced to increase the efficiency of the fuzzy logic stabilizer. A genetic algorifimi is used to search for optimal settings of each stabilizer parameters. Simulation results show that both stabilizers are suitable for and effective in damping oscillations and enhancing system stability over a range of operating conditions.

Fuzzy logic control of a nitrogen laser

Traditionally, the stability of the output of a laser is controlled through scientific means or by a simple feedback loop. For multiinput multioutput control and for medium- to high-power lasers, however, these control schemes may break down. We report on the use of a fuzzy logic control scheme to improve the stability of a pulsed nitrogen laser. Specifically, the nitrogen laser is modeled as a two-input two-output system. The two input parameters are the discharge voltage (V) and nitrogen pressure (P), and the two output parameters are the pulse energy (E) and pulse width (PW). The performance of the fuzzy logic controller is compared with a decoupled two-channel PID (proportional + integral + derivative) controller. In our experiment, the long-term stabilities of the open-loop system are 1.82% root mean square (rms) for pulse energy and 4.58% rms for pulse width. The PID controller achieves better performance with long-term stabilities of 1.46% rms for pulse energy and 4.46% rms for pulse width. The fuzzy logic controller performs the best with long-term stabilities of 1.02% rms for pulse energy and 4.24% rms for pulse width, respectively.

Direct and Fuzzy Control of a Two-Link Flexible Robot Manipulator

A direct proportional derivative (PD) control scheme is used to obtain a square trajectory 12.6 m × 12.6 m tracked by a two-link flexible robot manipulator incorporating nonlinear dynamics equations. An alternative approach uses a fuzzy logic control (FLC) scheme to track the trajectory by substituting the nonlinear dynamics equations with two fuzzy controllers, each dedicated to a link of the manipulator. The links are coupled by feeding acceleration output from the FLC for Link 1 into the FLC for Link 2 to simulate interactions between links across the elbow joint.