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This paper presents the use of fuzzy logic control (FLC) of a variable speed induction machine wind generation system. The generation system uses three fuzzy logic controllers (FLC's), first fuzzy logic controller tracks the generator speed with wind velocity to extract maximum power. Second fuzzy logic controller programs the machine flux for light load efficiency improvement. Third fuzzy logic controller...
This paper presents the stability analysis of a class of nonlinear time-varying delay systems with parameter uncertainty, through extended Takagi-Sugeno fuzzy modeling. The delay-dependent stability and robust stability criterions are presented using delay decomposition approach, in terms of linear matrix inequalities (LMIs). The time-varying delay is assumed to be bounded and continuous need not...
One of the current challenges in the development of robot control systems is making them capable of intelligent and suitable responses to changing environments. But, the control of the robot's behavior in uncertain and dynamic environments is very challenging when the problem is how to guarantee the robot's safety by minimizing the interaction with other actors. The most popular methods are based...
Tuning of a pH process is a challenging problem due to the strong on-line non-linearity and extreme sensitivity to disturbances of the process. Hence, a nonlinear control strategy based on sliding mode, which is a standard approach to tackle the parametric and modeling uncertainties of a nonlinear system, is chosen for tuning a pH process. Fuzzy Sliding Mode Control (FSMC) as a robust and intelligent...
This paper presents a modified particle swarm optimization (MPSO) algorithm to design an optimal multi input multi out (MIMO) fuzzy logic controller for a cement mill process. The membership function, rule base and the scaling factor of the multi input multi output FLC is tuned for optimal control performance using MPSO by minimizing the Integral absolute error for minimum and maximum operating setpoints...
This paper develops a ANFIS controller design method for temperature control in plastic extrusion system. The plastic extrusion process control system uses first order transfer function. Plastic extrusion system is generally nonlinear and the temperature of the plastic extrusion system may vary over a wide range subjected to various disturbances. The plastic extrusion system compresses of couple effects,...
This paper presents a comparative study of the PSO-technique and the Fuzzy based controller for the improvement of transient stability of Static Synchronous Series Compensator (SSSC). New and efficient configuration of adaptive SSSC controller based on the Fuzzy control is presented. Further, the performance of the Fuzzy based controller is compared with the PSO-technique results. Simulation results...
In this paper, Adaptive Neuro-Fuzzy Inference System (ANFIS) method based on the Artificial Neural Network (ANN) is applied to design a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design objective is to improve both rotor angle stability and system voltage profile. The proposed ANFIS controller combines the advantages of fuzzy controller...
In order to solve the problem that the membership functions of traditional fuzzy control are difficult to be determined, a new method (fuzzy network) of fuzzy control is proposed. Fuzzy network adopted the network structure in which the membership functions, control rules, fuzzy reasoning and defuzzification process are included. Compared with the fuzzy neural network, fuzzy network don't need learning...
The aims of this paper, are to obtain for an electro-hydrostatic servo-actuator, good performances, (time response and frequency characteristics), making it usable on aircraft, and a more simple configuration of the regulator, with a short computing time and a more simple program, in order to obtain a cheaper and more simple implementation. The strategy is to reduce the membership functions number...
In this paper a study of the fuzzy logic controller for ZCS Boost converter is presented. The fuzzy logic controller provides an adaptive control for better system performance and it is used for controlling the non-linear processes. FLC is designed to regulate the output voltage of the converter. The converter is modeled and analyzed using Matlab/Simulink software and it was designed in an closed-loop...
Self-optimisation will enable future wireless networks to manage themselves in a continuous and independent way. By dynamically adjusting relevant radio parameters during network operation a system that adapts to environmental changes can be created. This paper presents a novel self-optimisation algorithm based on Fuzzy Logic Controlling. Taking into consideration measurements gathered from the network,...
Currently, a large number of clustering algorithms are available for data mining. But it will be difficult for people who to a large extent know little about data mining to select an appropriate clustering algorithm. In order to solve this problem, in this paper, we first comprehensively analyze a number of clustering algorithms, then summarize their evaluation criteria and apply the so-called fuzzy...
In this paper, a neuro-fuzzy control-based approach is used for networked control systems to overcome the negative effects of the network-induced delays. This approach can timely modify the weights of the adaptive controller to improve control performance. Finally, by modeling networked control system with Matlab truetime toolbox, and the simulation results show that networked control systems based...
Although simple genetic algorithm (SGA) can, to some extent, improve the back propagation neural network (BP), it is prone to prematurity and losing the optimal solutions. Niche technology and fuzzy control theory are introduced to improve SGA and the improved one is used to optimize BP. The improved genetic algorithm is used to optimize BP neural network. In addition, due to the increasingly voltage...
The fuzzy control theory is applied on reactive voltage control. With voltage and reactive power deviation as its input, and the transformer tap and capacitor switching as its output, MATLAB Fuzzy Logic Toolbox are used to form the fuzzy inference system. NanYi substation in JiangXi is an example. In the TH2100 software simulation, the results show that the control system is stable and reliable, the...
The gyro stabilized platform control is required to isolate the line of sight (LOS) from the disturbance and vibration of carrier and ensure pointing and tracking for target in electro-optical tracking system. A compound adaptive fuzzy PID control with hysteresis-band switching is developed for this servo system with nonlinear property and some uncertainties. Here, in the adaptive fuzzy controller,...
In this paper, because the induction machines (IM) are described as the plants of highly nonlinear and parameters time-varying, to obtain excellent control performances of IM and overcome the shortcomings of the fast modified variable metric optimal learning algorithm (MDFP) and back propagation (BP) learning algorithm of neural network, such as requiring derivation in the process of learning and...
Currently, in the MAC protocol of wireless sensor network, the sender mote sends data with or without receiving acknowledgements (ACK). Although in some applications, people enable the ACK function, they just use the fixed repeat times. In such scenarios, the sender mote does not care about the quality of the channel when they have to send the data. However, in the real world, the channel may not...
In this paper, an adaptive interval type-2 fuzzy neural network (FNN) controller is presented to synchronize multivariable chaotic systems with training data corrupted by noise or rule uncertainties. Adaptive interval type-2 FNN control scheme and sliding mode approach are incorporated to deal with the synchronization of two non-identical chaotic systems. In the meantime, based on the adaptive fuzzy...
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