Fuzzy Logic Unit Research Articles

Hybrid harmony search algorithm & fuzzy logic for solving unit commitment problem with wind power uncertainty

This work spotlights on fuzzy logic and hybrid harmony search algorithm based framework for solving the unit commitment problem in any electric utility. Here, the selection of fuzzy logic is because of its qualitative representation ability with respect to input attributes, cost-effective operating agenda and all the calculations of feasible schedules. A three-unit system is assumed here, to compute the above-mentioned aspects. In recent days, the meta-heuristic optimization algorithms are constructed because of its zero utilization and storage for making the search procedureas effective. Hybrid harmony search algorithm searches whether the load demand is met or not. If it is not satisfied an error is developed. The error and change in error is fed input to fuzzy logic unit. The output of fuzzy logic unit is given to a breaker. The breaker will cut off the system is the power output is more and if the power output is less than the required value additional power is fed to the system. Constant ouput power is thus maintained. To test and prove that the proposed HHS-FLresults a superior optimization, performance by analyzing the wind speed in Coimbatore region. The experimental results demonstrated that the proposed model is efficient even if the windgets changed and all simulations was performed with MATLAB.

An intelligent visual servo control system for quadrotors

While quadrotors are becoming more popular, control of these unmanned air vehicles should be improved. In this study, a new intelligent image-based visual servo control system is proposed for the flight guidance control of quadrotors. Features are essential for visual servoing and the proposed system utilizes the features of a shape that provide a clear sight of the landing site instead of point features. Furthermore, the system focuses on three problems of visual servo control: finding an appropriate gain value under velocity limits, keeping the shape features in the field of view and tracking a moving target. As a solution to the first problem, a fuzzy logic unit that uses feature error and error derivative norms as inputs are deployed to assign the gain, adaptively. The second problem is solved by defining safe and risky regions in the image plane to take precautions before field of view missing. Another fuzzy logic unit is activated when the shape passes through a risky region to provide counter velocity in x or y direction and to drag the shape through the safe region. As the last stage, Kalman filtering with Potter’s square root update is added to the proposed system to increase the feature tracking performance. This update also promises divergence avoidance. To show the performance of the proposed system, simulation results for fixed and moving targets under feature disturbance are presented for a quadrotor. The results verify that the proposed system is capable of handling visual servoing problems.

Analysis of protection technologies radio fire alarm systems against unauthorized access

There is currently a growth of radio channel fire alarm. One of their main disadvantage is the vulnerability of the communication channel to the data being compromised. The authors, based on our analysis and fuzzy logic unit, identified the most tamper-proof wireless technology fire alarm to give a quantitative evaluation of the security level. The most secure technologies from complex threats (view, substitution, interception, jamming) include technologies based on spread-spectrum signals (based on the technology of random sequences and ultra-wideband signals) and are the least secure cryptographic techniques (simulation protection device). It's the necessity of further research aimed at improving the security of the radio fire alarm. A promising development is seen systems with technologies to protect the radio channel based on spread-spectrum signals (based on the technology of random sequences and ultra-wideband signals).

Adaptive robust fuzzy control for dual arm robot with unknown input deadzone nonlinearity

The control problem of the dual arm robot rigidly grasping an object with unknown nonsymmetric deadzone input is investigated in this paper. Due to the factor that the deadzone nonlinearity is widespread in the actuators, a smooth inverse adaptive deadzone is incorporated to minimize the effect of the deadzone nonlinearity in the dual arm robot system to guarantee a high accuracy tracking. Since these type of robots are usually applied in complex environments, a multi-input multi-output fuzzy logic unit is adopted to approximate the manipulator’s dynamics to achieve a accuracy tracking performances. Moreover, a decentralized robust fuzzy adaptive control scheme is constructed to make the motion and internal forces track a reference trajectories in the presence of parameters uncertainty and external disturbance. By using the Lyapunov method, the stability of the signals in the closed-loop system is proved. Simulation result demonstrates that the proposed controller is effective to the dual arm robot system with deadzone nonlinearity.

Stability Enhancement in Multi-Machine Power Systems by Fuzzy-based Coordinated AVR-PSS

This paper presents performance of intelligent fuzzy-based coordinated control for Automatic Voltage Regulator (AVR) and Power System Stabilizer (PSS), to prevent losing synchronism after major sudden faults and to achieve appropriate post-fault voltage level in multi-machine power systems. The AVR and PSS gains can adaptively change to guarantee the power system stability after faults. For change in AVR and PSS gains, at least one significant generator in each area of a multi-area power system is equipped with fuzzy logic unit. The fuzzy logic unit accepts normalized deviations of terminal voltage and phase difference of synchronous generators as inputs and generates the desirable gains for AVR and PSS. The construction of appropriate fuzzy membership functions and rules for best tuning of gains is described. The proposed fuzzy control methodology is applied to 11-bus 4-generator power system test case. Simulation results illustrate the effectiveness and robustness of the proposed fuzzy-based coordinated control strategy.

Using fuzzy logic to reduce ping-pong handover effects in LTE networks

Recently, mobile communications have been widely used in people's everyday lives. Their handover process facilitates people to transfer an ongoing call or a data session from one service area to another without conducting any communication interruption. However, in mobile communications, the ping-pong effect is a serious problem since it may cause unnecessary handover and lead to data loss and high computation cost. This is the case when a user equipment (UE) moves between two or among more evolved Node Bases (eNBs), due to signal strength reason, the UE in a very short time period alternatively switches among the eNBs. Consequently, the eNBs bounce the communication link the UE connected to them back and forth. Although several previous researches have been made to mitigate the ping-pong effect, what seems to be lacking is effectively eliminating unnecessary handover. Therefore, in this paper, we propose a fast and simple fuzzy-logic-based handover decision system, named Fuzzy based Low Ping-Pong Effect Handover System (FPEHS for short), to reduce the ping-pong effect in an LTE network. In the FPEHS, five parameters, including current signal-to-noise ratio (SNR), detected SNR, bandwidth of serving eNB, bandwidth of target eNB, and remaining energy of the underlying user's device, are inputted to the fuzzy logic unit to make handover decision. Our simulation results show that the FPEHS can effectively decrease the ping-pong effect about 92.94 % in average compared with that of the standard LTE's handover mechanism.

Multi Output Optimization of CNC High Speed Hard Turning of AISI 52100 Bearing Steel using Taguchi Method and Fuzzy Logic Unit

In this paper the combination of Taguchi method with logical fuzzy reasoning was implemented for multi output optimization of high speed CNC turning of AISI 52100 steel alloy. The machining parameters (cutting speed, feed rate, depth of cut) are optimized with considerations of the multiple performance measures (surface roughness, material removal rate, machining time, tool wear). Taguchi's concepts of orthogonal arrays, signal to noise (S/N) ratio, ANOVA etc are used and the S/N ratios have been fuzzified to optimize the high speed CNC turning process parameters through a single comprehensive output measure (COM).

Control of vehicle active suspensions by using PD+PI type fuzzy logic with sliding surface

A PD+PI type fuzzy logic controller with sliding surface is presented in this study. This controller consists of two parts which are PD type and PI type fuzzy logic units. Inputs to those fuzzy logic units are the sliding surface functions and their derivatives. The integrated controller is applied to two degrees of freedom vehicle active suspension model. Both time and frequency domain analysis are evaluated. Numerical results demonstrate that the proposed controller improves the vibration isolation of the vehicle body, without causing a suspension degeneration problem and without degrading road holding very much.

Type-2 hierarchical fuzzy system for high-dimensional data-based modeling with uncertainties

A type-2 hierarchical fuzzy system (T2HFS) is presented for the high-dimensional data-based modeling with uncertainties. Type-2 fuzzy logic system (T2FLS) is a powerful tool to handle uncertainties in complex processes. However, the operation of type-reduction has greatly increased the computational burden of T2FLSs. By integrating the T2FLS with hierarchical structure, a systematic design methodology of T2HFS is proposed to avoid the rule explosion and to simplify the computation complexity. The design methodology has included several procedures to establish the T2HFS. Firstly, the PCA-based method is developed to capture the prominent component from training data, and to determine the hierarchical structure of T2HFS. Furthermore, a novel clustering method is proposed to design the basic type-2 fuzzy logic unit (T2FLU) in uncertain environments. Finally, a hybrid-learning method is presented to fine-tune the parameters for the global optimization where the statistical and deterministic optimization methods are developed for the nominal and auxiliary performance, respectively. Simulation results have shown that the proposed T2HFS is very effective for the high-dimensional data-based modeling and control in uncertain environment.

Stereo Vision System Using Low-cost Cameras for Robot Following Control

This article describes a robot following system, which uses a fuzzy logic unit to generate control sequence. A stereo vision system using low-cost pinhole cameras is proposed for distance and position feedback in the fuzzy logic unit. The proposed robot control system is built on Tamiya Little Trucks. Experimental results are reported in comparison with a previous work using single camera. The results indicate that our proposed approach provides tighter control performances for the robots to follow predefined courses. VDO clips are available at http://www.youtube.com/watch?v= qAL1uYclvGY and http://www.youtube.com/watch?v=yTWgs1NLWVQ. The article presents some promising patents on Stereo Vision System. Keywords: Fuzzy logic, mobile robot, object tracking, robot following control, Stereo vision, Stereo Vision System, Low-cost Cameras, STEREO VISION PRINCIPLE, Fuzzy membership functions, Stereoscopic image

MIMO fuzzy sliding mode controlled dual arm robot in load transportation

The control problem of the cooperative motion of a two-link dual arm robot during handling and transportation of an object was studied in this paper. Since these types of robots are frequently preferred for hazardous applications such as transportation of radioactive materials and disposal of explosives, a robust non-chattering sliding mode controller (SMC) improved by a multiple-input multiple-output (MIMO) fuzzy logic unit was applied to the robot to track the desired trajectory with high accuracy and transport the load safely. In order to assess the performance of the proposed MIMO fuzzy sliding mode controller (MIMO-FSMC) in presence of parameter variations and external disturbances, a sudden load variation and noise were introduced to the robot system. If compared with classical SMC, tracking errors with smaller magnitudes and faster convergence to zero were obtained by using the proposed MIMO-FSMC. Numerical results suggest that this type of control method may safely be used for cooperative motion control of dual arm robots in load handling and transport applications in hazardous environments with high accuracy.

Prosthetic Hand Finger Control Using Fuzzy Sliding Modes

In order to improve the life quality of amputees, providing approximate manipulation ability of a human hand to that of a prosthetic hand is considered by many researchers. In this study, a biomechanical model of the index finger of the human hand is developed based on the human anatomy. Since the activation of finger bones are carried out by tendons, a tendon configuration of the index finger is introduced and used in the model to imitate the human hand characteristics and functionality. Then, fuzzy sliding mode control where the slope of the sliding surface is tuned by a fuzzy logic unit is proposed and applied to have the finger model to follow a certain trajectory. The trajectory of the finger model, which mimics the motion characteristics of the human hand, is pre-determined from the camera images of a real hand during closing and opening motion. Also, in order to check the robust behaviour of the controller, an unexpected joint friction is induced on the prosthetic finger on its way. Finally, the resultant prosthetic finger motion and the tendon forces produced are given and results are discussed.

퍼지 시스템의 2계층 퍼지 시스템으로의 변환 방법

To solve the rule explosion problem in multi input fuzzy logic system, a method of converting a given fuzzy system to 2 layered hierarchical fuzzy system is presented where the collection of the THEN-parts of the fuzzy rules of given fuzzy system is considered as vectors of fuzzy rule. At the 1 st layer, linearly independent fuzzy rule vectors generated from the given fuzzy logic system are used and, at the 2nd layer, linear combinations of these independent fuzzy rule vectors are used for fuzzy logic units at each layer. The resultant 2 layered hierarchical fuzzy system has not only equivalent approximation capability, but less number of fuzzy rules compared with the conventional fuzzy logic system.

Fuzzy Greenhouse Climate Control System based on a Field Programmable Gate Array

Fuzzy control is a practical alternative for the design of a great variety of control applications. It provides an advisable method for the design of non-linear controllers using heuristic information. This article presents the development of a greenhouse intelligent climate control system that uses a fuzzy controller, based on a field programmable gate array (FPGA). The FPGA has a great potential for use in agricultural technology development due to its characteristics to produce fast prototypes of complex hardware designs with an effective production cost. A low-cost intelligent system designed in a single chip with the task to carry out the complete functionality for the greenhouse climate control was developed. The system proposed here is a good option to unload the low-level tasks (monitoring of climate variables and operation of actuators, such as heaters and windows to control the greenhouse inside temperature) from the main control system, in order to leave to the main controller the high-level tasks as plant monitoring, control of vegetative development, production planning, irrigation system control, which need a high computational power. The system developed in this work consists of: a signal conditioning sub-system, a data-acquisition sub-system, digital/analogue conversion sub-system and a FPGA sub-system. The FPGA sub-system has three units: the synchronisation unit, the personal computer interface unit and the fuzzy logic unit, all implemented within a FPGA-integrated circuit, conforming to a system-on-a-chip (SoC). The design, compilation and simulation of the FPGA sub-system were carried out in the Active-HDL environment using the hardware description language VHDL. The Co-simulation Active-HDL/Simulink and experiments that show the performance of the complete system are presented.

Fuzzy based coordinated controller for power system stability and voltage regulation

This paper deals with the design of a fuzzy based coordinated controller to prevent an electric power system losing synchronism after a large sudden fault and to achieve good post-fault voltage level. The developed controller has a fuzzy logic unit (FLU) which, accepts change in terminal voltage and speed deviation as its inputs and generates the required weightage for the transient controller and voltage controller. The performance of the proposed controller is compared with those existing control switching coordinate controller. The simulation study is carried out for the configuration of a single machine infinite bus power system.

Combined channel estimation and data decoding based on fuzzy logic

A simple method that detects the data sequence and at the same time estimates the channel condition is proposed using the Viterbi algorithm and fuzzy logic for the convolutional code. After a fixed number of decoding steps, the fuzzy logic unit reads the branch metric value of the survivor and the difference between maximum and minimum survivor path metric values at the Viterbi decoder and estimates the channel condition with the signal-to-noise ratio. The proposed method enables the channel estimation regardless of what kinds of modulator and demodulator are used. In the experiment, constraint length 7 and code rate 1/2 convolutional code that is standardized by the European Space Agency (ESA) is used. The effective movement range of the proposed channel estimation method is from 0.0 dB to 25 dB.