Adaptive Plant Controller Reduces Steam Temperature Deviations
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Solution Overview
Problem
Current control systems for energy production plants, such as those using coal or other fuels, face challenges in accurately managing operational parameters like steam temperature and flue gas flow, leading to inefficiencies and deviations from desired set points, particularly during transient conditions or changes in power output or thermal load.
Innovation Solution
The implementation of an adaptive control system that includes a controller with a processor, memory, and transceiver, capable of estimating operational variable statuses, calculating uncertainty values, and generating control signals based on reference and measured values to adjust plant processes, thereby improving control precision and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional PID controllers are used for controlling plant operational parameters, then the control system is simple and easy to implement, but the control precision and transient performance deteriorate during changing conditions
Solution Approach 1:
The patent implements an adaptive control system that continuously monitors operational parameters and adjusts control signals based on real-time feedback. The controller compares measured values with target values and dynamically modifies control outputs to maintain optimal performance during transient conditions, resolving the contradiction by using intelligent feedback mechanisms rather than simple fixed-gain PID control.
Solution Approach 2:
The control system dynamically changes control parameters adaptively based on operating conditions. Instead of using fixed PID gains, the system adjusts controller parameters in real-time to match changing plant conditions, thereby maintaining high control precision without requiring overly complex fixed-structure controllers.
2Adaptability or versatility
If conventional control systems are used, then the system structure is simple, but the ability to adapt to changing conditions deteriorates
Solution Approach 1:
The patent implements a dynamic control system that adapts its behavior based on changing operating conditions. The controller continuously updates its control strategy in response to varying plant parameters, enabling it to handle transient conditions and load changes effectively. This dynamic adaptation resolves the contradiction by making the control system flexible rather than static.
Solution Approach 2:
The adaptive control system performs self-adjustment based on real-time measurements of plant conditions. The controller automatically modifies its own control parameters and signals without external intervention, enabling the system to adapt to changing conditions while maintaining a relatively simple overall structure through autonomous decision-making.
3Stability of the object's composition
If conventional control methods are used, then the control system is easy to operate, but the transient performance and stability deteriorate
Solution Approach 1:
The patent employs continuous feedback mechanisms where the controller monitors operational parameters and automatically adjusts control signals to maintain process stability during transient conditions. This closed-loop feedback ensures stability without requiring complex manual adjustments, as the system self-corrects based on real-time measurements.
Solution Approach 2:
The patent replaces manual control operations with automated adaptive control algorithms. The intelligent controller performs complex stability-maintaining operations automatically, substituting mechanical/manual control actions with computational processes that enhance stability while maintaining ease of operation through automation.
Data Source
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AI summary
A method for controlling at least one operational parameter of a plant (1) having a combustion unit (3) can include estimating a status of at least one operational variable of the plant to identify an estimated value for the operational variable. For each operational variable, the estimated value for the operational variable can be compared with a measured value of the operational variable to determine an uncertainty value based on a difference in value between the measured value and the estimated value for the operational variable. A control signal can be generated based on a reference signal, the measured value, and the deviation value for sending to at least one element of the plant (1) for controlling a process of the plant (1).