Abstract
Intelligent machines are capable of recognizing their operational condition and take actions towards optimality through an autonomous processing of information. Considering the importance of rotating machines in modern industry, this concept of intelligent machines can be applied to achieve high availability, thus avoiding interruptions in the production flow. In this work, a self-identification algorithm is proposed for the autonomous decision and control of a flexible shaft rotating system with electromagnetic actuators. Based on the D-decomposition technique, the algorithm searches in the domain of controller gains the best ones for P and PD controllers to reduce maximum peak response of the shaft. For that, frequency response functions of the system are automatically identified experimentally by the algorithm. It is demonstrated that regions of stable gains can be easily plotted, and the most suitable gains can be found to minimize the resonant peak of the system in an autonomous way, without human intervention.
Highlights
According to [1], an intelligent machine is capable of recognizing its operational condition and takes actions towards optimality through an internal and autonomous processing of information
The controller is turned off and a subroutine starts the identification procedure, which consists in measuring the frequency response function (FRF) of the open-loop system
When subroutine FRF Measurement is called, the block diagram shown in Figure 12 is run through Real Time Workshop (RTW) and, after completion of the identification task, the input/output data becomes available at MatLab workspace, enabling the steps of the algorithm
Summary
According to [1], an intelligent machine is capable of recognizing its operational condition and takes actions towards optimality through an internal and autonomous processing of information. Actuators and sensors have been incorporated into rotating machines aiming at attenuating and controlling the vibration levels, especially those presented by the shaft [3,4,5,6] In such cases, the actuators can be used as exciters, and open-loop frequency response of the system can be identified. Such frequency response would contain information from the actuator system + rotating system/ bearings + sensor system that can be used to find the best gains for the controller If all this process (identification of plant FRFs and determination of optimum gains) is automatically managed by an algorithm, as proposed in the present work, one would achieve the definition of intelligent machines stated by [1]: a machine that can identify its characteristics (self-identification) and take actions towards optimality (search for optimum gains). The obtained results show the feasibility of the algorithm in finding the best gains for the control system in an autonomous way
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