V/f PWM inverter with motor parameter identification and voltage auto-boost capabilities

2002 ◽  
Author(s):  
A. Gastli ◽  
N. Matsui
Keyword(s):  
Parameter Identification ◽  
Pwm Inverter ◽  
Motor Parameter

DC motor parameter identification using equation error method

2017 ◽  
Vol 100 (2) ◽  
pp. 415-423 ◽  
Author(s):  
Andrius Petrovas ◽  
Aurelijus Pitrėnas ◽  
Zita Savickienė
Keyword(s):  
Parameter Identification ◽  
Dc Motor ◽  
Equation Error ◽  
Motor Parameter ◽  
Error Method

Marine Asynchronous Propulsion Motor Parameter Identification Using Dynamic Particle Swarm Optimization

2013 ◽  
Vol 860-863 ◽  
pp. 2211-2217
Author(s):  
Si Yuan Liu ◽  
Yan Cheng Liu ◽  
Chuan Wang ◽  
Jun Jie Ren
Keyword(s):  
Particle Swarm Optimization ◽  
Parameter Identification ◽  
Electric Propulsion ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Identification System ◽  
Solution Quality ◽  
Swarm Optimization ◽  
Motor Parameter ◽  
Weight Learning

This paper proposes a new application of dynamic particle swarm optimization (PSO) algorithm for parameter identification of vector controlled asynchronous propulsion motor (APM) in electric propulsion ship. The dynamic PSO modifies the inertia weight, learning coefficients and two independent random sequences which affect the convergence capability and solution quality, in order to improve the performance of the standard PSO algorithm. The standard PSO and dynamic PSO algorithms use measurements of the mt-axis currents, voltages of APM as the inputs to parameter identification system. The experimental results obtained compare the identified parameters with the actual parameters. There is also a comparison of the solution quality between standard PSO and dynamic PSO algorithms. The results demonstrate that the dynamic PSO algorithm is better than standard PSO algorithm for APM parameter identification. Dynamic PSO algorithm can improve the performance of ship propulsion motor under abrupt load variation.

scholarly journals ROS-based Toolbox for Motor Parameter Identification of Robotic Manipulators

2021 ◽  
Author(s):  
Ulici Ioana-Anamaria ◽  
Codrean Alexandru ◽  
Tassos Natsakis
Keyword(s):  
Mathematical Model ◽  
Parameter Identification ◽  
Robotic Manipulators ◽  
Velocity Control ◽  
Precise Knowledge ◽  
Depth Study ◽  
Motor Parameter ◽  
The Mathematical Model ◽  
Stable Control ◽  
Individual Motor

For many applications, a precise knowledge of the model of the robot is necessary for accurate and stable control. However, it is not always feasible or desirable to perform from scratch an in-depth study of the robot model, especially if it is not an element of concern for the respective application. In this article we present a methodology for identifying motor parameters of a robotic manipulator. We discuss the mathematical model and introduce an extensible toolbox with velocity-control based methodology for a fast identification of individual motor parameters. The results show that we can identify individual parameters even for joints that are commercialised as of the same type.

Sign in / Sign up

Export Citation Format

Share Document