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.

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-Based Design and Simulation of an Automatic Parking System

With the development of automatic driving and fuzzy theory, people pay more and more attention to the application of fuzzy logic in engineering technology. The automatic parking module in the automatic driving system has always been the focus of research. Automatic parking modules can greatly assist drivers in parking operations, greatly reduce parking difficulties and make people more convenient and fast parking. In this paper, an automatic parking system based on the fuzzy controller is proposed. The fuzzy controller of automatic parking system is constructed by using fuzzy theory, and the robustness of the whole system is examined by fuzzy logic. Firstly, the vehicle motion rules and trajectory changes are analyzed in detail, and the real parking lot model is simulated. Then, the input and output variables of the whole system are analyzed by fuzzy theory and the membership function is constructed. Based on the experience of human experts, the parking rules are tested and summarized, and a reasonable and practical rule base is established. Finally, MATLAB is used to code, build the visual interface of parking lot and vehicles, and draw the cyclic iterative function to detect the vehicle position and direction angle, so as to act as a sensor. The results show that using a fuzzy controller to construct an automatic parking system can effectively improve the parking level.

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.

Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design

An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. The results of function optimization show that the algorithm has good searching ability and high convergence speed. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due tσ multivariable inputs, a state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. The simulation results show that the designed controller can control the inverted pendulum successfully.

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.

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-

SOFC temperature evaluation based on an adaptive fuzzy controller

The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.

On-Chip Micro Temperature Controllers Based on Freestanding Thermoelectric Nano Films for Low-Power Electronics

Multidimensional integration and multifunctional com-ponent assembly have been greatly explored in recent years to extend Moore’s Law of modern microelectronics.However,this inevitably exac-erbates the inhomogeneity of temperature distribution in microsystems,making precise temperature control for electronic components extremely challenging.Herein,we report an on-chip micro temperature controller including a pair of thermoelectric legs with a total area of 50×50μm^(2),which are fabricated from dense and flat freestanding Bi2Te3-based ther-moelectric nano films deposited on a newly developed nano graphene oxide membrane substrate.Its tunable equivalent thermal resistance is controlled by electrical currents to achieve energy-efficient temperature control for low-power electronics.A large cooling temperature difference of 44.5 K at 380 K is achieved with a power consumption of only 445μW,resulting in an ultrahigh temperature control capability over 100 K mW^(-1).Moreover,an ultra-fast cooling rate exceeding 2000 K s^(-1) and excellent reliability of up to 1 million cycles are observed.Our proposed on-chip temperature controller is expected to enable further miniaturization and multifunctional integration on a single chip for microelectronics.

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.

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.

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.

Fuzzy Controller Based 3Phase 4Wire Shunt Active Filter for Mitigation of Current Harmonics with Combined p-q and Id-Iq Control Strategies

As more and more variable frequency drives (VFDs), electronic ballasts, battery chargers, and static Var compensators are installed in facilities, the problems related to harmonics are expected to get worse. As a result Active power filter (APF) gains much more attention due to excellent harmonic compensation. But still the performance of the active filter seems to be in contradictions with different control strategies. This paper presents detailed analysis to compare and elevate the performance of two control strategies for ex-tracting reference currents of shunt active filters under balanced, un-balanced and non-sinusoidal conditions by using Fuzzy controller. The well known methods, instantaneous real active and reactive power method (p-q) and active and reactive current method (id-iq) are two control methods which are extensively used in active filters. Extensive Simulations are carried out with fuzzy controller for both p-q and Id-Iq methods for different voltage conditions and adequate results were presented. Simulation results validate the superior per-formance of active and reactive current control strategy (id-iq) with fuzzy controller over active and reactive power control strategy (p-q) with fuzzy controller.

Stability of Nonlinear Systems Using Optimal Fuzzy Controllers and Its Simulation by Java Programming

In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.

An Adaptive Fuzzy Controller for Trajectory Tracking of Robot Manipulator

In this paper, an adaptive fuzzy control algorithm is proposed for trajectory tracking of an n-DOF robot manipulator subjected to parametric uncertainty and it is advantageous compared to the conventional nonlinear saturation controller. The asymptotic stability of the proposed controller has been derived based on Lyapunaov energy function. The design procedure is straightforward due to its simple fuzzy rules and control strategies. The simulation results show that the present control strategy effectively reduces the control effort with negligible chattering in control torque signals in comparison to the existing nonlinear saturation controller.

Study on Multi-variables Decoupled Fuzzy Controller for Confined Pig House in Northern China

In winter, the confined pig house of northern China is severe. The environment variables are nonlinear, time-varying and coupled, which seriously affect the health of pigs and the qualities of the meat. In order to solve the problem multi-variables coupling, a multi-variables decoupled fuzzy logic control method was proposed. Two fuzzy logic controllers were designed based on fuzzy logic theory. The fans, heaters and humidifiers were used to control temperature, humidity and ammonia. The reductions of temperature and humidity caused by ventilating were compensated by heaters and humidifiers respectively which realized the multivariables decoupling. The proposed methods were validated through theoretical, experimental and simulation analysis. The results suggested that the methods were able to regulate the confined pig house environment effectively. In addition, comparing to the manual regulation, the proposed methods could reduce 19% power consumption as well.

Design of Fuzzy Controller for Robot Manipulators Using Bacterial Foraging Optimization Algorithm

Trial and error method can be used to find a suitable design of a fuzzy controller. However, there are many options including fuzzy rules, Membership Functions (MFs) and scaling factors to achieve a desired performance. An optimiza-tion algorithm facilitates this process and finds an optimal design to provide a desired performance. This paper presents a novel application of the Bacterial Foraging Optimization algorithm (BFO) to design a fuzzy controller for tracking control of a robot manipulator driven by permanent magnet DC motors. We use efficiently the BFO algorithm to form the rule base and MFs. The BFO algorithm is compared with a Particle Swarm Optimization algorithm (PSO). Performance of the controller in the joint space and in the Cartesian space is evaluated. Simulation results show superiority of the BFO algorithm to the PSO algorithm.

Instantaneous Active and Reactive Power and Current Strategies for Current harmonics cancellation in 3-ph 4wire SHAF With both PI and Fuzzy Controllers

Control strategies for extracting the three-phase reference currents for shunt active power filters are compared, evaluating their performance under different source conditions with PI and Fuzzy Controllers in MATLAB/Simulink environment When the supply voltages are balanced and sinusoidal, the two control strategies are converge to the same compensation characteristics;However, the supply voltages are distorted and/or un-balanced sinusoidal, these control strategies result in different degrees of compensation in harmonics. The compensation capabilities are not equivalent, with p - q control strategy unable to yield an adequate solution when source voltages are not ideal. Extensive simulations are carried out with PI controller and also with Fuzzy controller for both p-q and Id-Iq control strategies under different main voltages. Extensive Simulations are carried out with PI as well as fuzzy controller for both p-q and Id - Iq control strategies by considering different voltage conditions and adequate results were presented. On owing Id - Iq method with fuzzy logic controller gives away an out-standing performance under any voltage conditions (balanced, un-balanced, balanced and non-sinusoidal).