Identification of a Permanent Magnet Direct Current Motor from One Experiment

En este artículo se presenta un procedimiento simple para estimar los parámetros de las funciones de transferencia, basándose en la respuesta al escalón, de un sistema conformado por un driver de velocidad y un motor de corriente directa de imanes permanentes. El proceso de identificación consiste en la selección de los modelos, la adquisición y pre-procesamiento de los datos, la estimación de parámetros y su validación. Los resultados muestran que es posible estimar los parámetros del sistema a partir de la respuesta al escalón, logrando valores de la suma normalizada de los errores cuadráticos menores al 0,5 %.A simple procedure to estimate the transfer function parameters, based on the step response, of a system composed by a speed driver and a permanent magnet direct current motor is presented in this paper. The identification process is composed by the model selection, the acquisition and pre-processing of data, the parameter estimation and its validation. The results show that it is possible to estimate the system parameters from the step response achieving values of the normalized sum of squared errors less than 0.5 %

High-frequency issues using rotating voltage injections intended for position self-sensing

The rotor position is required in many control schemes in electrical drives. Replacing position sensors by machine self-sensing estimators increases reliability and reduces cost. Solutions based on tracking magnetic anisotropies through the monitoring of the incremental inductance variations are efficient at low-speed and standstill operations. This inductance can be estimated by measuring the response to the injection of high-frequency signals. In general however, the selection of the optimal frequency is not addressed thoroughly. In this paper, we propose discrete-time operations based on a rotating voltage injection at frequencies up to one third of the sampling frequency used by the digital controller. The impact on the rotation-drive, the computational requirement, the robustness and the effect of the resistance on the position estimation are analyzed regarding the signal frequency

Theoretical analysis and experimental validation of a simplified fractional order controller for a magnetic levitation system

Fractional order (FO) controllers are among the emerging solutions for increasing closed-loop performance and robustness. However, they have been applied mostly to stable processes. When applied to unstable systems, the tuning technique uses the well-known frequency-domain procedures or complex genetic algorithms. This brief proposes a special type of an FO controller, as well as a novel tuning procedure, which is simple and does not involve any optimization routines. The controller parameters may be determined directly using overshoot requirements and the study of the stability of FO systems. The tuning procedure is given for the general case of a class of unstable systems with pole multiplicity. The advantage of the proposed FO controller consists in the simplicity of the tuning approach. The case study considered in this brief consists in a magnetic levitation system. The experimental results provided show that the designed controller can indeed stabilize the magnetic levitation system, as well as provide robustness to modeling uncertainties and supplementary loading conditions. For comparison purposes, a simple PID controller is also designed to point out the advantages of using the proposed FO controller

Magnetic Modelling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks

The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques. Among the candidates, pure reluctance and anisotropic permanent magnet motors are gaining popularity, despite their complex structure. The availability of accurate mathematical models that describe these motors is essential to the design of any model-based advanced control. This paper focuses on the relations between currents and flux linkages, which are obtained through innovative radial basis function neural networks. These special drive-oriented neural networks take as inputs the motor voltages and currents, returning as output the motor flux linkages, inclusive of any nonlinearity and cross-coupling effect. The theoretical foundations of the radial basis function networks, the design hints, and a commented series of experimental results on a real laboratory prototype are included in this paper. The simple structure of the neural network fits for implementation on standard drives. The online training and tracking will be the next steps in field programmable gate array based control systems

Initial rotor position estimation and sensorless direct torque control of surface-mounted permanent magnet synchronous motors considering saturation saliency

For a practical direct torque-controlled (DTC) permanent magnet synchronous motor (PMSM) drive system, the information of the initial rotor position, which is usually obtained by a mechanical position sensor, is essential for starting under the full load. To avoid the disadvantages of using mechanical position sensors, great efforts have been made on the development of sensorless control schemes. An initial rotor position estimation strategy is presented for a DTC PMSM drive based on a nonlinear model of PMSM incorporating both structural and saturation saliencies. In the new scheme, specially designed high-voltage pulses are applied to amplify the saturation saliencies. The peak currents corresponding to the voltage pulses are used, in combination with the inductance patterns, to determine the d-axis position and the polarity of the rotor. The presented initial rotor position identification strategy has been implemented in a sensorless DTC drive for a surface-mounted PMSM. Experiments are conducted to confirm the effectiveness of the method and the performance of the drive system. © The Institution of Engineering and Technology 2008

Linear motor motion control using a learning feedforward controller

The design and realization of an online learning motion controller for a linear motor is presented, and its usefulness is evaluated. The controller consists of two components: (1) a model-based feedback component, and (2) a learning feedforward component. The feedback component is designed on the basis of a simple second-order linear model, which is known to have structural errors. In the design, an emphasis is placed on robustness. The learning feedforward component is a neural-network-based controller, comprised of a one-hidden-layer structure with second-order B-spline basis functions. Simulations and experimental evaluations show that, with little effort, a high-performance motion system can be obtained with this approach

Adaptive Torque Estimation for an IPMSM with Cross-Coupling and Parameter Variations

This paper presents a new adaptive torque estimation algorithm for an interior permanent magnet synchronous motor (IPMSM) with parameter variations and cross-coupling between d- and q-axis dynamics. All cross-coupled, time-varying, or uncertain terms that are not part of the nominal flux equations are included in two equivalent mutual inductances, which are described using the equivalent d- and q-axis back electromotive forces (EMFs). The proposed algorithm estimates the equivalent d- and q-axis back EMFs in a recursive and stability-guaranteed manner, in order to compute the equivalent mutual inductances between the d- and q-axes. Then, it provides a more accurate and adaptive torque equation by adding the correction terms obtained from the computed equivalent mutual inductances. Simulations and experiments demonstrate that torque estimation errors are remarkably reduced by capturing and compensating for the inherent cross-coupling effects and parameter variations adaptively, using the proposed algorithm.111Ysciescopu

Description of the Spacecraft Control Laboratory Experiment (SCOLE) facility

A laboratory facility for the study of control laws for large flexible spacecraft is described. The facility fulfills the requirements of the Spacecraft Control Laboratory Experiment (SCOLE) design challenge for a laboratory experiment, which will allow slew maneuvers and pointing operations. The structural apparatus is described in detail sufficient for modelling purposes. The sensor and actuator types and characteristics are described so that identification and control algorithms may be designed. The control implementation computer and real-time subroutines are also described