I. N. da Silva

Embedded DSP-Based Compact Fuzzy System and Its Application for Induction-Motor

This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.

V/f

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Speed Control

In past work, the authors have proposed a radial magnetic bearing architecture where the rotor was kept suspended only by means of magnetic forces produced by permanent magnets working in attraction mode and the rotor was actively controlled only in one degree of freedom (d.o.f.), i.e., its axial direction. Although the presented architecture is simpler than those bearings with active control in two or more d.o.f., it presented limitations mainly of low radial stiffness. So, in this context this paper discusses ways to enhance the radial stiffness in this kind of bearing and presents simplified analytical methods used to find magnets and actuator optimal dimensions that gives both ring magnets radial stiffness and actuator force/current ratio maximum intensities.

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

In past work, the authors have proposed a radial magnetic bearing architecture where the rotor was kept suspended only by means of magnetic forces produced by permanent magnets working in attraction mode and the rotor was actively controlled only in one degree of freedom (d.o.f.), i.e., its axial direction. Although the presented architecture is simpler than those bearings with active control in two or more d.o.f., it presented limitations mainly of low radial stiffness. So, in this context this paper discusses ways to enhance the radial stiffness in this kind of bearing and presents simplified analytical methods used to find magnets and actuator optimal dimensions that gives both ring magnets radial stiffness and actuator force/current ratio maximum intensities.

An attraction-type magnetic bearing with control in a single direction

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements The ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization The neural networks applied in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points The internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible equilibrium points. A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Design Considerations for Achieving High Radial Stiffness in an Attraction-Type Magnetic Bearing With Control in a Single Direction

A fuzzy control strategy for voltage regulation in electric power distribution systems is introduced in this article. This real-time controller would act on power transformers equipped with under-load tap changers. The fuzzy system was employed to turn the voltage-control relays into adaptive devices. The scope of the present study has been limited to the power distribution substation, and both the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage control strategies that satisfy both the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. A prototype based on the fuzzy control strategy proposed in this paper has also been implemented for validation purposes and its experimental results were highly satisfactory.

An efficient neural approach to economic load dispatch in power systems

A fuzzy approach to the navigation control of mobile robots is presented in this paper. The problem of driving a mobile robot to a goal in an unknown environment is formulated as a fuzzy logic control problem in which local information is used to make steering and velocity decisions while the robot is moving. The fuzzy logic maps the input fuzzy sets representing the mobile robot state space determined by sensor readings to the output fuzzy sets representing mobile robot action space. We propose a direct and effective method using sensory data in order to design the fuzzy logic controller. Simulation results show the performance of the approach proposed.

Fuzzy Control System for Voltage Regulation In Power Transformers

This paper evaluates the behavior related to the main variables that influence in the quantification of potential points for installation of fault indicators along electric power distribution feeders. Moreover, based on these behavioral characteristics, fuzzy inference systems are also used to estimate the best positions to allocate fault indicators, which take into account the distance in that a particular bus is in relation to more adjacent protection devices, load profile and short-circuit current levels of the downstream system to the respective points. Results with real data highlight the efficiency of the proposed methodology.

Navigation of mobile robots using fuzzy logic controllers

This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

Efficient fuzzy approach for allocating fault indicators in power distribution lines

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.