Adaptive PID Control for Industrial Turbines
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Solution Overview
Problem
Tuning PID controllers for industrial turbines is challenging due to demanding control requirements and unusual dynamic behavior, often exceeding the skills of turbine operations personnel, leading to suboptimal performance.
Innovation Solution
A method involving a process controller and a parameter controller that adjust proportional, integral, and derivative gain parameters based on turbine response values and a parameter adjustment algorithm, using equations like H(s)=P(1+I/s)(Ds+1), to optimize turbine control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual PID tuning is performed by turbine operations personnel, then the control system can be adjusted, but the tuning quality is suboptimal due to insufficient skills and training
Solution Approach 1:
The system performs self-tuning by automatically adjusting PID parameters based on observed turbine response to test inputs, eliminating the need for manual tuning by operations personnel and achieving optimal control without requiring specialized skills
Solution Approach 2:
A parameter controller acts as an intermediary between the process controller and the turbine, automatically determining optimal control parameters based on turbine response characteristics and providing them to the process controller
2Reliability
If trial-and-error tuning is used to achieve acceptable performance, then the system can be made to work, but the tuning process is time-consuming and requires repeated adjustments
Solution Approach 1:
The system performs preliminary testing by automatically applying test inputs to the turbine and observing responses before final deployment, allowing optimal parameters to be determined in advance through systematic experimentation rather than repeated trial-and-error adjustments
Solution Approach 2:
The system uses feedback from turbine response measurements to automatically adjust PID parameters, observing how the turbine responds to test inputs and using this information to determine optimal control settings without requiring manual intervention
3Ease of operation
If automated parameter adjustment is implemented, then tuning simplicity is improved, but the device complexity increases due to additional controllers and algorithms
Solution Approach 1:
The parameter controller serves multiple functions: it generates test inputs, observes turbine responses, determines optimal parameters using algorithms, and provides these parameters to the process controller, consolidating what would otherwise require multiple separate systems into a single multi-functional device
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 providing a process controller configured to perform a control algorithm based on at least one first control parameter, providing a parameter controller configured to perform a parameter adjustment algorithm, providing a turbine having an output sensor, providing to the process controller at least one first control parameter and a first input value, controlling the turbine based on the at least one first control parameter and the first input value, receiving a turbine response value provided by the turbine output sensor, determining at least one second control parameter based on the turbine response value and the parameter adjustment algorithm, providing, to the process controller from the parameter controller, the at least one second control parameter, and controlling the turbine based on the at the least one second control parameter and a second input value.