Model-Free Adaptive Control for Supercritical CFB Boiler Processes
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Solution Overview
Problem
Advanced power plants, particularly those with Once-Through Supercritical and Circulating Fluidized-Bed boilers, face challenges in controlling complex processes due to nonlinearities, time-varying conditions, and multi-variable interactions, leading to inefficiencies and emission issues, which conventional control methods struggle to address effectively.
Innovation Solution
A multivariable Model-Free Adaptive (MFA) control system is developed to manage 5-Input-5-Output combustion processes in Circulating Fluidized-Bed and Once-Through Supercritical Circulating Fluidized-Bed boilers, using a 7-input-7-output control system that integrates with Boiler-Turbine-Generator units, enabling adaptive and robust control without requiring precise process models or manual tuning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional PID control methods are used, then the control system is simple and easy to implement, but it cannot effectively handle nonlinearities, time-varying conditions, and multi-variable interactions in advanced power plants
Solution Approach 1:
The MFA control system performs self-tuning and self-adaptation automatically. The controller continuously monitors process behavior and adjusts its internal model without external intervention, enabling it to adapt to nonlinearities and time-varying conditions while maintaining manageable system complexity through automated operations
Solution Approach 2:
The control system dynamically adjusts its behavior based on real-time process conditions. The MFA controller modifies its control strategy adaptively in response to changing operating conditions, allowing it to handle time-varying processes effectively while maintaining responsiveness and effectiveness
2Measurement precision
If model-based advanced control methods are used, then control precision can be improved, but it requires precise process models, process identification, controller design, and complicated manual tuning
Solution Approach 1:
The MFA controller automatically identifies process characteristics and tunes itself without requiring manual intervention. It performs self-diagnosis and self-adjustment based on real-time process data, eliminating the need for complex manual tuning while maintaining high control precision through automated optimization
Solution Approach 2:
The control system continuously monitors process outcomes and uses this feedback to automatically adjust its control strategy. The MFA controller learns from actual process behavior and modifies its internal model accordingly, achieving precise control through iterative feedback-based adaptation rather than relying on pre-programmed models
3Productivity
If traditional control systems are used, then the system is easier to operate and maintain, but it cannot achieve superior performance in tracking setpoints and regulating variables in multivariable processes
Solution Approach 1:
The MFA control system automatically optimizes its own performance without requiring complex operational procedures. It self-adjusts to achieve superior setpoint tracking and variable regulation while maintaining ease of operation through automated control actions, eliminating the need for manual intervention in optimization processes
Data Source
AI summary
A novel 3-Input-3-Output (3×3) Fuel-Air Ratio Model-Free Adaptive (MFA) controller is introduced, which can effectively control key process variables including Bed Temperature, Excess O2, and Furnace Negative Pressure of combustion processes of advanced boilers. A novel 7-input-7-output (7×7) MFA control system is also described for controlling a combined 3-Input-3-Output (3×3) process of Boiler-Turbine-Generator (BTG) units and a 5×5 CFB combustion process of advanced boilers. Those boilers include Circulating Fluidized-Bed (CFB) Boilers and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.