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Development of a Real-Time Model-Prediction-Based Framework for Reset Controller Design
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DOI：10.1021/ie5027869.png)
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Abstract
En 中文
This paper addresses a real-time reset controller design based on the model prediction strategy for process control. Reset control design consists of two main steps: (1) base-system controller design and (2) reset law determination. The base system controller is designed according to the base (no reset) plant dynamics and the reset law is determined by an algebraic condition, which is checked throughout the time for controller state resetting. In this paper, based on the model prediction approach, a linear matrix inequalities (LMI)-based formulation is derived for designing the reset controller. When the reset condition is satisfied, the reset law is computed by solving an LMI optimization problem, and then base-system parameters and current controller states are suddenly changed to new values. This result is used in two examples; numerical simulations verify the efficiency of the proposed approach.
Keywords:
PERFORMANCE ANALYSIS
CONTROL-SYSTEMS
STABILITY
PLANT
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