Analysis of one dimensional and two dimensional fuzzy controllers

The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.

INDIRECT ACCELERATED ADAPTIVE FUZZY CONTROLLER

According to a type of normal nonlinear system, an indirect adaptive fuzzy （IAF） controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy （IAAF） controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system＇s global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process＇s shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.

The Optimized Disign of the Fuzzy Controller(Ⅰ)——The predigested disquisition of rules of fuzzy control

To improve the ability and precisions of the fuzzy control,this thesis points out the adjusted fuzzy control method,realizes the precision of the fuzzy quantity, and reduces the number of the fuzzy control rules,so that it can predigest the process of disigns and realize the methods without influencing the idiocratic control,which are on the base of the domain flexing.

Fuzzy Controller Used to Protect Collision

A FC-1B type fuzzy controller used to protect collision in automobile running has heen devel-oped by Computer Institute, North Technological University. This facility has been authenticatedby specialists. This is a sci-tech fruit which integrates the hardware and software from fuzzy con-trol and artificial intelligence. This technique adopts initiative r-ime ultrasonic range-findingprobe, rapid fuzzy control algorithm, fuzzy discern and fuzzy decision etc. This technique is adapt-

A practical fuzzy controllers scheme of overhead crane

This paper presents fuzzy-based design for the control of overhead crane. Instead of analyzing the complex nonlinear crane system, the proposed approach uses simple but effective way to control the crane. There are twin fuzzy controllers which deal with the feedback information, the position of trolley crane and the swing angle of load, to suppress the sway and accelerate the speed when the crane transports the heavy load. This approach simplifies the designing procedure of crane controller; besides, the twin controller method reduces the rule number when fulfilling the fuzzy system. Finally, experimental results through the crane model demonstrate the effectiveness of the scheme.

Adaptive fuzzy controller for a class of strict-feedback nonaffine nonlinear systems

A robust adaptive fuzzy control scheme is presented for a class of strict-feedback nonaffine nonlinear systems with modeling uncertainties and external disturbances by using a backstepping approach.Fuzzy logic systems are employed to approximate the unknown parts of the desired virtual controls,and the approximation errors of fuzzy systems are only required to be norm-bounded.The function tanh（·） is introduced to avoid problems associated with sgn（·）.The tracking error is guaranteed to be uniformly ultimately bounded with the aid of an additional adaptive compensation term.Chua＇s circuit system and R o¨ssler system are presented to illustrate the feasibility and effectiveness of the proposed control technique.

HYDRAULIC ACTIVE GUIDE ROLLER SYSTEM FOR HIGH-SPEED ELEVATOR BASED ON FUZZY CONTROLLER

Increase of elevator speed brings about amplified vibrations of high-speed elevator. In order to reduce the horizontal vibrations of high-speed elevator, a new type of hydraulic active guide roller system based on fuzzy logic controller is developed. First the working principle of the hydraulic guide system is introduced, then the dynamic model of the horizontal vibrations for elevator cage with active guide roller system and the mathematical model of the hydraulic system are given. A fuzzy logic controller for the hydraulic system is designed to control the hydraulic actuator. To improve the control performance, preview compensation for the controller is provided. Finally, simulation and experiments are executed to verify the hydraulic active guide roller system and the control strategy. Both the simulation and experimental results indicate that the hydraulic active guide roller system can reduce the horizontal vibrations of the elevator effectively and has better effects than the passive one, and the fuzzy logic controller with preview compensation can give superior control performance.

Robust decentralized adaptive output feedback fuzzy controller design and application to AHS

A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.

DESIGNING OF TWO NEW FUZZY CONTROLLERS WITH ERROR INTEGRAL AND THEIR APPLICATIONS IN FOLLOWING CONTROL OF WARSHIP-GUNS

Two new fuzzy controllers are designed, one's control rules are adjusted byerror integral, another are with feedforward of error integral. If only the control rules andparameters are selected felicitously, the static errors of the system will be eliminated. The testresults show that the controllers can assuredly improve static performances of the controlledsystem.

Design of Fuzzy Controller for Central Air Conditioner

A structure of central air conditioning system in building and its running pattern are proposed in order to perform optimum energy saving strategy. The design of room temperature controller is taken as an example to discuss the design of fuzzy controller using common microprogrammed control unit (MCU) in detail. Based on fuzzy theory the query control tables fixed in read only memory (ROM) of MCU are established to realize the energy saving in the room temperature controller and the reasoning procedure is analyzed. The diagram of hardware design and the flow chart of software of room temperature controller are presented. The results show that the proposed method is practical and effective to achieve the energy saving goal.

Optimization of Adaptive Fuzzy Controller for Maximum Power Point Tracking Using Whale Algorithm

The advantage of fuzzy controllers in working with inaccurate and nonlinear inputs is that there is no need for an accurate mathematical model and fast convergence and minimal fluctuations in the maximum power point detector.The capability of online fuzzy tracking systems is maximum power,resistance to radiation and temperature changes,and no need for external sensors to measure radiation intensity and temperature.However,the most important issue is the constant changes in the amount of sunlight that cause the maximum power point to be constantly changing.The controller used in the maximum power point tracking(MPPT)circuit must be able to adapt to the new radiation conditions.Therefore,in this paper,to more accurately track the maximumpower point of the solar system and receive more electrical power at its output,an adaptive fuzzy control was proposed,the parameters of which are optimized by the whale algorithm.The studies have repeated under different irradiation conditions and the proposed controller performance has been compared with perturb and observe algorithm(P&O)method,which is a practical and high-performance method.To evaluate the performance of the proposed algorithm,the particle swarm algorithm optimized the adaptive fuzzy controller.The simulation results show that the adaptive fuzzy control system performs better than the P&O tracking system.Higher accuracy and consequently more production power at the output of the solar panel is one of the salient features of the proposed control method,which distinguishes it from other methods.On the other hand,the adaptive fuzzy controller optimized by the whale algorithm has been able to perform relatively better than the controller designed by the particle swarm algorithm,which confirms the higher accuracy of the proposed algorithm.

The Optimized Design of The Fuzzy Controller(Ⅱ)——the disquisition of optimized triangle subjection function

The subjection function of the fuzzy quantity is bell like,which is on the base of the theory;but during the course of the control,each fuzzy grade should be predigested into a triangle of W=4.

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.

A New Fully Differential Adaptive CMOS Line Driver Using Fuzzy Controller Suitable for ADSL Modems

In this paper, a new principle for an adaptive line driver using Fuzzy logic is presented. This type of line driver can adapt its output impedance and gain, automatically to the applied load using a fuzzy logic controller (FLC). This results in automatically corrected output impedance for different cables with terminations. Also, the line driver output impedance and gain become insensitive to process and line variations. As an example, a line driver for ADSL application has been designed. The circuit operates from a 3.3 v in a 0.35 um standard CMOS technology. The power consumption of FLC is about 1 mW. The circuit dissipates 106 mW and exhibits a -62 dB THD for a 3.2-Vpp signal at 5 MHz across a 75 ohms Load. It has a relatively high -3 dB bandwidth (240 MHz) with good phase margin of about 67 degrees in a 10 pF load capacitor.

A Novel Asymmetric Three-Phase Cascaded 21 Level Inverter Fed Induction Motor Using Multicarrier PWM with PI and Fuzzy Controller

Multilevel inverters are gaining popularity in high power applications. This paper proposes a new ladder type structure of cascaded three-phase multilevel inverter with reduced number of power semiconductor devices which is used to drive the induction motor. The ultimate aim of the paper is to produce multiple output levels with minimum number of semiconductor devices. This paper uses only 11 switches along with 3 diodes and 4 asymmetrical sources to produce an output voltage of 21 levels. The modulation technique plays a major role in commutation of the switches. Here we implement the multicarrier level shifting pulse width modulation technique to produce the commutation signals for the inverter. The proposed multilevel inverter is used to drive the three-phase induction motor. The mathematical modeling of three-phase induction motor is done using Simulink. Furthermore the PI and fuzzy logic controllers are also used to produce the reference waveform of the level shifting technique which in turn produces the commutation signals of the proposed multilevel converter. The controllers are used to control the speed of the induction motor. The effectiveness of the proposed system is proved with the help of simulation. The simulation is performed in MATLAB/Simulink. From the simulation results, it shows that the proposed multilevel inverter works properly to generate the multilevel output waveform with minimum number of semiconductor devices. The PI and fuzzy logic controller performances are evaluated using the results which indicate that with the help of controllers the harmonics has been reduced and the speed control of induction motor is achieved under different loading conditions.

Enhancing the efficiency of cabin heaters in emergency shelters after earthquakes through an optimized fuzzy controller

In just one and half minutes,more than fifty thousand died due to the 7.7 and 7.6 magnitude earthquakes that struck Turkey’s southeast on February 6,2023;thousands of families who barely escaped struggled to survive in the freezing weather.A warm shelter was the most basic requirement of these families.Container buildings are a rapid and easy solution to this issue.However,there is a need for a more effective and safe heating option than a wood fire for these buildings.In this study,cabin heaters,which allow truck drivers to warm up when they park their vehicles to sleep,are specially optimized for emergency shelters after an earthquake.An optimized fuzzy controller was developed to use in such buildings,which allows an air–fuel ratio in the combustion chamber of the cabin heater to be controlled adaptively based on system dynamics to get lower carbon emissions and fuel consumption.The TRNSYS software was used to establish the transient simulation model of a cabin heater with a capacity of 4 kW for a typical 21 m^(2) shelter building in Turkey’s cold regions.The developed fuzzy controller carried out the heating process of this shelter from the 15th of November to the 15th of March.Instead of using expert knowledge,the Gray Wolf Optimization(GWO)method was applied to optimize the fuzzy controller parameters developed for the cabin heater.With the optimized fuzzy controller,the fuel consumption at the end of the heating season was reduced by an average of 0.2 L/h,and the cabin heater’s efficiency increased by more than 13%.Our simulation results show that the intelligent controller we developed could improve diesel fuel combustion efficiency by up to 85%.

A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system

When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely manner.This study proposes a maximum power reference signal search method based on fuzzy control,which is an improvement to the climbing search method.A neural network-based parameter regulator is proposed to address external wind speed fluctuations,where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed conditions.Finally,the effectiveness of this method is verified via Simulink simulation.

An Adaptive Neuro-Fuzzy Inference System to Improve Fractional Order Controller Performance

The design and analysis of a fractional order proportional integral deri-vate(FOPID)controller integrated with an adaptive neuro-fuzzy inference system(ANFIS)is proposed in this study.Afirst order plus delay time plant model has been used to validate the ANFIS combined FOPID control scheme.In the pro-posed adaptive control structure,the intelligent ANFIS was designed such that it will dynamically adjust the fractional order factors(λandµ)of the FOPID(also known as PIλDµ)controller to achieve better control performance.When the plant experiences uncertainties like external load disturbances or sudden changes in the input parameters,the stability and robustness of the system can be achieved effec-tively with the proposed control scheme.Also,a modified structure of the FOPID controller has been used in the present system to enhance the dynamic perfor-mance of the controller.An extensive MATLAB software simulation study was made to verify the usefulness of the proposed control scheme.The study has been carried out under different operating conditions such as external disturbances and sudden changes in input parameters.The results obtained using the ANFIS-FOPID control scheme are also compared to the classical fractional order PIλDµand conventional PID control schemes to validate the advantages of the control-lers.The simulation results confirm the effectiveness of the ANFIS combined FOPID controller for the chosen plant model.Also,the proposed control scheme outperformed traditional control methods in various performance metrics such as rise time,settling time and error criteria.

Dual degree branched type-2 fuzzy controller optimized with a hybrid algorithm for frequency regulation in a triple-area power system integrated with renewable sources

The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sources such as solar and wind necessitate the use of an efficient load frequency control(LFC)technique.Therefore,a hybrid version of two metaheuristic algorithms(arithmetic optimization and African vulture’s optimization algorithm)is developed.It is called the‘arithmetic optimized African vulture’s optimization algorithm(AOAVOA)’.This algorithm is used to tune a novel type-2 fuzzy-based proportional–derivative branched with dual degree-of-freedom proportional–integral–derivative controller for the LFC of a three-area hybrid deregulated power system.Thermal,electric vehicle(EV),and DRG sources(including a solar panel and a wind turbine system)are con-nected in area-1.Area-2 involves thermal and gas-generating units(GUs),while thermal and geothermal units are linked in area-3.Practical restrictions such as thermo-boiler dynamics,thermal-governor dead-band,and genera-tion rate constraints are also considered.The proposed LFC method is compared to other controllers and optimizers to demonstrate its superiority in rejecting step and random load disturbances.By functioning as energy storage ele-ments,EVs and DRG units can enhance dynamic responses during peak demand.As a result,the effect of the afore-mentioned units on dynamic reactions is also investigated.To validate its effectiveness,the closed-loop system is subjected to robust stability analysis and is compared to various existing control schemes from the literature.It is determined that the suggested AOAVOA improves fitness by 40.20%over the arithmetic optimizer(AO),while fre-quency regulation is improved by 4.55%over an AO-tuned type-2 fuzzy-based branched controller.

Fuzzy Proportional Integral Derivative control of a voice coil actuator system for adaptive deformable mirrors

Research on adaptive deformable mirror technology for voice coil actuators(VCAs)is an important trend in the development of large ground-based telescopes.A voice coil adaptive deformable mirror contains a large number of actuators,and there are problems with structural coupling and large temperature increases in their internal coils.Additionally,parameters of the traditional proportional integral derivative(PID)control cannot be adjusted in real-time to adapt to system changes.These problems can be addressed by introducing fuzzy control methods.A table lookup method is adopted to replace real-time calculations of the regular fuzzy controller during the control process,and a prototype platform has been established to verify the effectiveness and robustness of this process.Experimental tests compare the control performance of traditional and fuzzy proportional integral derivative(Fuzzy-PID)controllers,showing that,in system step response tests,the fuzzy control system reduces rise time by 20.25%,decreases overshoot by 78.24%,and shortens settling time by 67.59%.In disturbance rejection experiments,fuzzy control achieves a 46.09%reduction in the maximum deviation,indicating stronger robustness.The Fuzzy-PID controller,based on table lookup,outperforms the standard controller significantly,showing excellent potential for enhancing the dynamic performance and disturbance rejection capability of the voice coil motor actuator system.