MIMO PID Turbine Control with Automated Gain Tuning
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Solution Overview
Problem
Tuning of PID controllers for industrial turbines is challenging due to demanding control requirements and non-intuitive dynamic behavior, often requiring repeated trial-and-error adjustments by operators to achieve optimal performance.
Innovation Solution
A system for automated adjustment of proportional, integral, and derivative gain parameters of MIMO process controllers, utilizing a parameter controller to determine and adjust PID control parameters, including the Speed Derivative Ratio (SDR) parameter, to achieve predetermined operation of industrial turbines, including speed, pressure, load, and inlet/exhaust control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual trial-and-error tuning of PID controllers is used, then operators can adjust control parameters, but the tuning process becomes time-consuming and difficult to achieve optimal performance
Solution Approach 1:
The system performs self-diagnosis and self-tuning of PID controllers by automatically analyzing turbine response to excitation signals and adjusting control parameters without operator intervention, eliminating the need for manual trial-and-error tuning processes
Solution Approach 2:
The system pre-calculates optimal PID parameters by first introducing excitation signals to characterize turbine dynamics, then uses this pre-acquired information to automatically determine optimal control settings before actual operation begins
2Productivity
If automated PID tuning system is implemented, then tuning time is reduced and optimal performance is achieved, but system complexity increases
Solution Approach 1:
The control system performs multiple functions including normal turbine control, automatic excitation signal generation, response analysis, and PID parameter optimization using a single integrated controller, eliminating the need for separate dedicated tuning equipment
Solution Approach 2:
The system continuously monitors turbine response to excitation signals and uses this feedback information to automatically adjust PID parameters, creating a closed-loop self-tuning mechanism that adapts to actual turbine behavior
3Adaptability or versatility
If MIMO control is used for turbine, then multiple performance objectives are achieved, but control difficulty increases due to conflicting objectives
Solution Approach 1:
The MIMO control problem is segmented into multiple independent SISO PID controllers, each tuned separately using the automatic tuning method, which simplifies the overall control design while still achieving multiple performance objectives through coordinated operation
Data Source
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AI summary
The subject matter of this specification can be embodied in, among other things, a method that includes receiving, at a ratio controller, turbine response values based on first process output value based on a first control parameter and a first process input value, and a second process output value based on a second control parameter and a second process input value, providing the first process input value as a predetermined first constant set point value while varying the second process input value, receiving updated turbine response values, determining at least one third control parameter, providing the third control parameter as the second control parameter, providing the second process input value as a predetermined second constant set point value while varying the first process input value, receiving updated turbine response values, determining at least one fourth control parameter, and providing the fourth control parameter as the first control parameter.