Closed-Loop Transfer Function Measurement in Servo Mechatronics
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Solution Overview
Problem
Determining the transfer function of a servo-controlled mechatronic or electromechanical system is challenging due to the influence of internal and external disturbances, requiring system interruption and external equipment for measurement, which disrupts operation.
Innovation Solution
A device with an electronic control unit and software module uses sinusoidal excitation signals, Fresnel representation, and Kalman filtering to determine transfer functions without interrupting the servo control loop, employing a digital corrector and Kalman filter to model and filter response signals, enabling transfer function estimation through complex number division.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external equipment (analyzer or oscilloscope) is connected to determine the transfer function, then measurement capability is improved, but system operation is interrupted and operator intervention is required
Solution Approach 1:
The system uses its own internal resources (CPU, memory, software module) to perform transfer function measurements without requiring external measurement equipment. The electronic control unit itself generates excitation signals, acquires response signals, and processes the data to determine transfer functions, making the system self-sufficient for measurement purposes.
Solution Approach 2:
The electronic control unit is designed to perform multiple functions: both controlling the servo system and performing transfer function measurements. The software module can operate in different modes (normal control mode and measurement mode) without requiring separate dedicated hardware for measurement, thus eliminating the need to interrupt system operation for measurements.
2Measurement precision
If the feedback loop is opened to measure transfer function, then measurement accuracy is improved, but system stability is compromised and operator intervention is required
Solution Approach 1:
The system uses periodic sinusoidal excitation signals at different frequencies to stimulate the system during measurement. By applying periodic excitation and analyzing the periodic response, the software module can determine transfer functions while the system remains in its normal closed-loop stable operating state, avoiding the need to open the feedback loop.
Solution Approach 2:
The software module acts as an intermediary that processes signals within the existing feedback loop structure. Instead of opening the loop, the software module injects excitation signals, captures response signals, and processes them mathematically to extract transfer function information, thereby maintaining loop closure and system stability throughout the measurement process.
3Measurement precision
If complex signal processing is used to determine transfer function, then measurement accuracy is improved, but computational resources required increase
Solution Approach 1:
The software module uses parameter changes in the sinusoidal excitation signals (varying frequency and amplitude) to characterize the system's frequency response. By systematically changing these parameters and measuring the corresponding response, the system can determine transfer functions using relatively simple computational operations such as magnitude and phase calculations, avoiding the need for complex signal processing algorithms.
Data Source
AI summary
A device comprising at least one electromechanical system and an electronic control unit comprising both a servo control loop connecting together the input and the output of the electromechanical system, and also a digital corrector. The device includes a software module having an input and an output connected respectively to the output and to the input of the electromechanical system. For each frequency of a set of frequencies that are to be analyzed, the software module is programmed: to issue a sinusoidal excitation signal on its output and to recover a response signal on its input; to model the response signal by means of a Fresnel representation and to filter it about the excitation frequency by means of at least one Kalman filter in order to obtain a state vector of the filtered response signal; and to obtain at least one transfer function for the system from the model, from the excitation signal, and from the input signal.