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Research on the Unit Plant CCS Based on Multiple Model Adaptive Control

Author: LiNa
Tutor: LvLiXia；MaYongGuang
School: North China Electric Power University
Course: Control Theory and Control Engineering
Keywords: Multiple model adaptive control Coordinated control Self-tuning PID
CLC: TM621.6
Type: Master's thesis
Year: 2011
Downloads: 41
Quote: 0
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Abstract


The large unit coordinated control system is to improve the the plant economic benefits, an important part of the power grid dispatching automation. Coordinated control system is a complex multi-variable control system, there is not of deterministic interference and nonlinear characteristics boiler side there is a lot of lag and strong coupling characteristics and the boiler side and turbine side, so its control the design of the device there is a certain degree of difficulty. Robust control is a common and effective way of dealing with uncertainty. But when the system external environment or system parameter is changed greatly, the quality control of the system will be affected; traditional adaptive controller design is based on a fixed or slow time-varying parameters system model for complex systems, the The controller performance is also poor. In this context, the proposed multi-model adaptive control, the core idea is to use multiple models to approximate the dynamic characteristics of the system, the design of the corresponding sub-controller for each sub-model, and based on the best model designed controller switch performance optimization or weighted combination mapped to this controller, this controller can achieve better control precision for complex systems, tracking speed and stability. In this paper, the thermal power plants coordinated control system in the presence of parameter uncertainty, nonlinear, large inertia and large delay problem, multiple model adaptive control algorithm is applied to coordination control. First of all, the object of coordinated control system for processing. Drum boiler under the premise of a reasonable simplification, will coordinate simplify system objects into a dual-input, dual-output object. Feedforward compensation decoupling algorithm to lift the coupling between the control circuit or system variables; reduced-order for the high-level features of the object model, using the optimal model reduction algorithm. Then, the design of multi-model adaptive controller. This article select two fixed operating conditions equivalent model as a model of centralized sub-model, as far as possible approximation to the dynamic characteristics of the whole system, and then select an adaptive model to ensure identification error tends to zero. Sub-model-based design of self-tuning PID sub-controllers, and then weighting algorithm based on the performance indicators, the weighting of each sub-controller output and output value of the global controller to control the actual system. Finally, the application of the algorithm to a coordinated control by simulation to verify the validity of multi-model adaptive control algorithm for multi-model adaptive control algorithm in the nonlinear system to pave the way, and pointed out the direction of future research .

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CLC: > Industrial Technology > Electrotechnical > Power generation, power plants > Power plant > Thermal power plants, thermal power stations > Control equipment
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