Present the main aspects of the measures and technologies to build modern control systems based on transductors, data extraction and data processing.
To present, in particular, processing of sensory data, estimation techniques for auto and cross-correlation, test signal generation, FFT based harmonic response estimation, as well as the techniques and components at the basis of the actuators of electric engines.
To present, in particular, processing of sensory data, estimation techniques for auto and cross-correlation, test signal generation, FFT based harmonic response estimation, as well as the techniques and components at the basis of the actuators of electric engines.
teacher profile teaching materials
Self and mutual correlation functions, amplitude and power spectra. Time windows. Noise generators.
Non-parametric identification: estimate of the harmonic response with the periodogram method for open and closed loop systems; estimation of the impulse response with deconvolution methods.
Characteristics of electric drives with particular reference to brushless motors.
Laboratory activities
Practice with common instruments.
Connection of simple didactic systems to acquisition cards. Acquisition, treatment and visualization through Matlab of the resulting signals.
Identification of simple didactic systems by implementing some of the techniques described and / or using dedicated software packages.
Programme
MKSA. Static and dynamic characteristics of the sensors. Calibration. Measurement chains. Sensors for kinematic quantities (position, speed, acceleration), notes on other sensors (load cells, temperature sensors, pressure sensors). Installation problems on the system. Electrical connection of sensors and measuring, shielding and insulation equipment. Interfacing with computers. Acquisition cards. An example of language for acquisition and processing of sensory data. Pretreatment (filtering, removal of the mean value). Measurement of the harmonic response.Self and mutual correlation functions, amplitude and power spectra. Time windows. Noise generators.
Non-parametric identification: estimate of the harmonic response with the periodogram method for open and closed loop systems; estimation of the impulse response with deconvolution methods.
Characteristics of electric drives with particular reference to brushless motors.
Laboratory activities
Practice with common instruments.
Connection of simple didactic systems to acquisition cards. Acquisition, treatment and visualization through Matlab of the resulting signals.
Identification of simple didactic systems by implementing some of the techniques described and / or using dedicated software packages.
Core Documentation
Teacher's notesType of delivery of the course
Theory is exposed in the classroom and practice in the labType of evaluation
A short thesis plus a question on the theory