A%---+@i+T,s The main objective of this paper is to seek the simplest possible identification model that can simulate closely the dynamic behaviour of a synchronous generator. The successful development of such a model would be of help in devising efSicient on-line digital controllers. For this purpose, the recursive least-squares method of identification has been used. In this respect it has been found that both a third order and a second order identifier are successful in performing this job. The remarkablefinding here is the capability of such reduced models of simulating the dvnamics of synchronous generators under the effect of the sub-synchronous resonancephenomenon, where the order of the differential equations describing the system under study is extremely high. The validity of the presented analysis and the conclusions reached are checked experimentally.
This paper presents a modern approach of speed control for Permanent magnet Synchronous Motor (PMSM) using online artificial neural network (ANN). The overall system will be simulated under various operating conditions. The use of ANN as a controller makes the drive robust, with faster dynamic response higher accuracy and insensitive to load variation .On line training of the ANN is carried out and the results show fast convergence. After training the ANN the system is tested for a step change in load, the simulation results showing good dynamic response with fast recovery time.The DC motors have been widely used as precision control motors till mid 1970s. Recent developments in microprocessors, magnetic materials and semiconductors technology have offered an excellent opportunity to use AC motors in high performance drives systems. PMSM became at the top of ac motors in the medium range of power and it became very popular choice in drive technology over the last few years due to some of its inherent advantages [l].,These advantages include high torque to current ratio, large power to weight ratio, higher efficiency and robustnessThe speed controller used in drive system plays an important role to meet the other required criteria of the High Performance Drive. It should enable the drive to follow any reference speed tacking into account the effects of load impact, saturation and parameter variations. Conventional controllers such as P, PI and PID controllers need accurate mathematical models describing the dynamics of the system under control [2]. But these types of controllers are difficult to design if an accurate system model is not available. Moreover, unknown load dynamics and other factors such as noise, temperature, saturation, etc. affect their performance. Some adaptive control techniques, such as the variable structure and self -tuning don't need a model for system dynamics, the dynamic model is rather developed based on the on-line input/output response of the system. Unfortunately, these methods track only linear systems. But some investigator overcame this difficulty by updating these models every several sampling intervals [3-61.Although these adaptive controllers are proven to be effective, their hardware implementation is elaborate .ANN using parallel and distributed processing units can achieve the functions of system modeling and control for nonlinear systems [I]. Artificial neural networks have several key features that make their highly suitable for high performance drive applications. For example, ANN can cr 0-78034482-2104/$20.00 02004 IEEE. 143
The field oriented controlled Brushless dc (BLDC) motor resembles the dynamic characteristics of a fully compensated DC motor, The torque developed from such drives is directly proportional to the armature current and hence a super dynamic performance is achieved. This paper presents a new and simple technique of field orientation in BLDC motor drives. This technique relies upon adding an extra control loop to the ordinary voltage source inverter fed BLDC drives and allows the drive to develop maximum torque per ampere at any loading condition. The implementation of this control loop is quite simple and does not complicate the overall drive circuitry.speed range, and fi-equent maintenance requirements, particularly due to brushes and commutators. Need to find alternatives of using dc motors in the modern drive system has been advocated over many years. Recent developments in microprocessors, magnetic materials, and semiconductor technology have offered an excellent opportunity to use ac motors in high performance drive systems. Among the various types of ac motors, the permanent magnet synchronous motor is becomimz a verv uomdar choice in drive technolozv over the Keywords: Brushless DC motors, Permanent Magnet Synchronous last few y~~s &~0 some of its inherent advantageous u.Motor, Field oriented drives.
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