Romain Delpoux

Parameter estimation of permanent magnet stepper motors without position or velocity sensors

The paper presents a new sensorless parameter identification method for permanent magnet stepper motors. Current sensors are assumed available, but position and velocity sensors are not. Data is obtained with open-loop voltage commands at multiple speeds. A new reference frame is proposed that presents advantages similar to the standard d-q frame, but without the need for a position sensor. The method exploits carefully derived linear parameterizations and a least-squares algorithm. In one case, overparameterization is resolved using elimination theory. Overall, the parameters identified using the new procedure are found to be very close to those obtained with position sensors. The approach is potentially applicable to other types of synchronous motors as well.

High-order sliding mode control for sensorless trajectory tracking of a PMSM

The paper presents a new sensorless approach for permanent magnet synchronous motor. Current sensors are assumed available, but position and velocity sensors are not. Based on the electrical equations, sliding mode observers are designed to estimate the back-electro motive force (EMF) of the motor. These estimations are used to reconstruct the position and the velocity. From this estimation, a robust sliding mode control is developed which ensures the position tracking of the motor. A new reference frame is used that presents advantages similar to the standard (d − q) frame, but without the need for a position sensor. The efficiency of the algorithm is shown through experimental results. The approach is potentially applicable to other types of synchronous motors as well.

On-line parameter estimation of a magnetic bearing

This article presents a parameter estimation algorithm for a magnetic bearing. Such process are inherently unstable systems with strongly nonlinear dynamics. Here, a simplified model of the magnetic bearing is developed. This enables to obtain a linear expression with respect to the unknown parameters. These parameters are measurable with difficulties, and may slightly vary over time. The expression of the estimates is written as a function of integrals of the inputs and outputs of the system. The simulations and the experiments show a fast and robust on-line identification.

Permanent Magnet Synchronous Motor control via Parameter Dependent Relay control

The article presents a novel control strategy for the control of Permanent Magnet Synchronous Motor (PMSM). The approach is motivated by the fact that PMSM are usually controlled by relays and thus only a finite set of control inputs is available. However in classical control design the use of Pulse-Width Modulation (PWM) ignores the relay nature of the actuators. Here we propose a direct relay control. As PMSM may be modeled as Linear Parameter Varying (LPV) systems, we propose a Parameter Dependent Relay (PDR) control. A design based on Linear Matrix Inequalities (LMI) allows to derive the switching surfaces, which depend on the motor position. The theory described is illustrated by simulations results.

Derivative based control for LPV system with unknown parameters: An application on a Permanent Magnet Synchronous Motors

This paper deals with the robust stabilization of a class of Linear Parameter Varying (LPV) systems in the continuous time case. Instead of using a state observer or searching for a dynamic output feedback, the controller is based on output derivative estimation. This allows the stabilization of the plant with very large parameter variation and uncertainties. The proof of stability is based on the polytopic representation of the closed loop, Lyapunov conditions and system transformations. The result is a control structure with only few parameters which are tuned via very simple conditions. This paper illustrates the usefulness on real application: Permanent Magnet Synchronous Motors (PMSM) position control.

Toward on-line robot vibratory modes estimation

This paper is concerned with preliminary results on robot vibratory modes on-line estimation. The dominating oscillatory mode of the robot arm is isolated by comparing the robot position given by the motors encoders and an external measure at the tool-tip of the robot arm. In this article the external measurement is provided by a laser tracker. The isolation of the oscillation permits to identify the vibratory mode, i.e. the natural frequency and the damping ratio of the undesired phenomena. Here we propose a comparison between the algebraic method and the sliding modes for the parameter identification. This comparison is motivated by the fact that both methods provide finite time convergence. Experimental identifications are proposed on a 6 degrees of freedom (DOF) manipulator robot, Stäubli RX-170B.

Joint Identification of Stepper Motor Parameters and of Initial Encoder Offset

Abstract The paper presents a new procedure to identify at the same time the electrical parameters of a permanent magnet stepper motor (PMSM) and the initial offset of an incremental encoder. The model considers effects due to the permanent magnet and to variable reluctance, and the resulting theory is applicable to cases where both or only one of these terms is present. The standard DQ model of PMSMs assumes that the permanent magnet is lined up with a winding when the position is zero. When an incremental encoder is used, an initialization procedure is required to zero the initial offset. In contrast, this paper computes a transformed model that accounts for the initial offset. then develops a least-squares identification algorithm that estimates the machines electrical parameters together with the offset angle. Experiments show that the estimation procedure and a closed-control method using the estimated offset perform similarly compared to when the offset is reset to zero using an initilization procedure.