Miroslaw Wlas

Artificial-neural-network-based sensorless nonlinear control of induction motors

In this paper, two architectures of artificial neural networks (ANNs) are developed and used to correct the performance of sensorless nonlinear control of induction motor systems. Feedforward multilayer perception, an Elman recurrent ANN, and a two-layer feedforward ANN is used in the control process. The method is based on the use of ANN to get an appropriate correction for improving the estimated speed. Simulation and experimental results were carried out for the proposed control system. An induction motor fed by voltage source inverter was used in the experimental system. A digital signal processor and field-programmable gate arrays were used to implement the control algorithm.

Neural-Network-Based Parameter Estimations of Induction Motors

The goal of this paper is to use artificial neural networks (ANNs) for online identification of induction-motor parameters. ANNs such as feedforward and recurrent networks will be used to develop an ANN as a memory for remembering the estimated parameters and for computing the parameters during transients. Simulations and experimental results will be presented for a nonlinear control system of induction motors. A digital signal processor will be used for the experimental investigation.

Properties of sensorless control systems based on multiscalar models of the induction motor

Purpose – To develop general forms of multiscalar models of the induction motor and to present properties of the sensorless control systems based on such models.Design/methodology/approach – Previously presented multiscalar model of the induction motor based on a stator current and rotor flux vector is generalized as a model of type 1. New model of type 2 is defined for stator current and the vector which is directly controlled by a voltage vector. The above models are applied in a sensorless control system with speed observer. Dynamical properties of the sensorless control systems are investigated by simulations and experiments.Findings – Application of the multiscalar model of type 2 results in higher exactness of sensorless control system than application of the multiscalar model of type 1. Controlled variables are more smooth in transients.Research limitations/implications – This is not an analytical proof of stability of the control systems.Practical implications – Provides very useful information fo...

Speed sensorless nonlinear control of induction motor in the field weakening region

In the paper it is presented speed sensorless nonlinear control system using multiscalar model based MMB operating in the lower field weakening speed region. Nonlinear control methods can improve the performance of induction motor drives in transients. The maximum available output torque, which guarantees satisfactory motor dynamics in field weakening region, is calculated using the steady state dependencies of induction motor model. Full dynamic reaction to commanded changes or to disturbances that occur during operation at the voltage limit is enabled by reducing the excitation level in a fastest possible way. Experimental results are presented to demonstrate reliability of proposed controller. In the experimental implementation a 22 kW induction motor is used. The whole control scheme (including multiscalar control, speed computation and space vector PWM) are implemented on a DSP and FPGA.

The Ethernet POWERLINK Protocol for smart grids elements integration

In this paper it is presented control system of distributed energy resources (DER) based on Ethernet POWERLINK Protocol. Authors develop a common method for communicating with The Inverter-Based Microgrid System. This paper presents the optimal storage sharing control method of grid connected generation system. This system consists of photovoltaic panels (PV), windmill with induction generator (WG), supercapacitors (SC), AGM battery, controllable load, power converters and electric power system. These components can be connected to make a micro-grid system controlled by Energy Management System based on DSP, ARM 9 processors and FPGA hardware. In a case study, it is analyzed how Ethernet POWERLINK Protocol can be used to build a communication channels between converters, load and management system. Simulation results are presented to demonstrate reliability of proposed control systems. The whole control scheme and communication protocol are implemented on a DSP and FPGA.

Dynamic performance of sensorless induction motor drives with two control systems based on multiscalar models

Application of the speed observer to two types of non-linear control systems of the induction motor is considered in the paper. The control systems are based on multiscalar models of the induction motor. Properties of the control systems are considered in dependence on two types of the multiscalar models of the induction motor pointed out in the paper. Simulations and experiments have confirmed the effectiveness of the proposed scheme

Microprocessor system for controlling the operation of renewable energy resources

This paper describes the management system to control, monitor and supervisory of renewable energy resources, energy storages and loads. System can also be implemented as management controller for local grid, which may cooperates with distribution networks. The system uses real-time Ethernet technology, which combined with a fast signal processor allows to perform a complex analysis of the network and to control local loads and distributed energy resources. Extensive communication protocols and low cycle time provide technical mean to control whole microgrid, Virtual Power Plant and communicate with distribution network operators.

PWM current source inverter with IGBT transistors and multiscalar model control system

A control system for the induction motor fed by a PWM CSI based on a multiscalar model is presented in the paper. The current source inverter topology and principle of PWM modulation are taken into account. The vector model of the induction motor fed by CSI with output capacitors of inverter is presented in the paper. Complete equations of three multiscalar models of the induction motor are presented. The first multiscalar model is based on the stator current and rotor flux vectors. The second model is based on the stator current and stator flux vectors. The third model is based on the stator current and main flux vectors. Properties of the new control systems are compared and results of simulations are presented

The laboratory model of wind power generator

Wind energy conversion system consists of: the wind turbine, the gear, mechanical energy conversion system: machine and converter and a control system. Optimal conver- sion of the wind power into the electrical power requires the variable speed generation systems. Many control strategies of the wind generator can be created. During the laboratory research the features of the wind power conversion system should be very carefully verified. In the real wind turbine system the experiments depend on the wind conditions and are expensive and not comfortable. To make the tests possible and independent on the weather a laboratory model of a 2kW wind power station based on wind emulator, has been built. In the paper description of the system and laboratory tests are pre- sented.