Automated Closed Loop Controller Tuning via Frequency Response Analysis
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Solution Overview
Problem
Existing methods for selecting filters and loop proportional gain in closed loop systems are inefficient and lack automation, often requiring manual intervention and not optimizing both filter selection and gain simultaneously, which can result in suboptimal performance due to separate determination of filter and gain components.
Innovation Solution
A method and system that generates a Frequency Response Function (FRF) to determine resonant and anti-resonant frequencies, estimate total inertia, and iteratively select loop shaping filters and proportional gain using the golden section search algorithm to maximize gain while meeting stability margin criteria, allowing for automated servo tuning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of filters and proportional gain is performed, then expertise and control are maintained, but time consumption and efficiency increase
Solution Approach 1:
The system performs self-tuning by automatically selecting filter parameters and proportional gain values without requiring manual intervention. The computer executes algorithms that analyze system response characteristics and autonomously determine optimal controller parameters, eliminating the need for expert operators while maintaining tuning quality.
Solution Approach 2:
The patent replaces manual mechanical tuning processes with automated computational methods. Instead of technicians manually adjusting parameters based on experience, a computer system uses algorithms to calculate and optimize filter and gain parameters automatically, substituting human expertise with automated intelligent processing.
2Device complexity
If filters and proportional gain are determined separately, then the selection process is simplified, but overall system performance deteriorates
Solution Approach 1:
The patent combines the filter selection process and proportional gain determination into a unified automated procedure. The computer system simultaneously optimizes both parameters by analyzing their interconnected effects on system stability and performance, ensuring that filter characteristics and gain values are coordinated for optimal overall system behavior rather than being selected independently.
Solution Approach 2:
The system uses feedback from system response analysis to iteratively refine both filter parameters and proportional gain values. By monitoring how changes in one parameter affect overall system performance, the automated tuning process adjusts multiple parameters in coordination, using performance feedback to guide simultaneous optimization of filters and gain settings.
3Productivity
If automated tuning is implemented, then time efficiency and productivity improve, but automation extent and complexity increase
Solution Approach 1:
The automated tuning system is designed as a universal solution that can handle multiple types of control systems and parameter configurations through a single integrated platform. The computer executes general-purpose algorithms that adapt to different system characteristics, providing automated tuning capabilities across various applications without requiring separate specialized systems for each case.
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AI summary
The present invention is a novel device, system, and method for simultaneous selection of filters and loop proportional gain for a closed loop system. According to an exemplary embodiment of the present invention, a method provides an automated selection of the portion of the controller known as the speed loop compensator. The method may operate on a frequency response function that represents the dynamic response from an actuation force (e.g. motor torque) to the sensor used for feedback of speed control (e.g. motor encoder angle). The frequency response function may be represented as a series of complex numbers each with a corresponding frequency value. The tuning method determines the combination of filter parameters that allows the loop proportional loop gain (Kp) to be maximized while meeting a specified set of criteria for stability margins. Methods for selecting integral gain and reference model are also presented