Supervisory Control Computer
Functions
Supervisory control has three fundamental functions
- Calculation of the present state of the process in terms of key process parameters such as yield, severity, and efficiency.
- Calculation of critical process constraints, such as compressor capacity, column flooding limits, explosion limits, vacuum condenser capacity, and raw material.
- Calculation of new process conditions, in terms of set points, which will meet the requirements of the objective function. The objective function can be one of a number of goals such as maximizing throughput, yield, and profit or minimizing deviation.
Tasks
The supervisory control computer requires
- A process model
- Cost functions
- Optimization algorithms
- Constraints and limits
The supervisory computer typically performs the following types of tasks
- Determines the process operating constraints, such as a column flooding condition in distillation or a surge condition of a compressor. Basic material balance, energy balance, or heat transfer calculations are utilized in creating the required process models. Because of the complex nature of the process itself, the computation of the model is a difficult task and might require iterative computation to satisfy convergent criteria.
- Determines the present operating state of the process based on the online, real-time information based on temperatures, pressures, and feed characteristics to obtain reactor yields or determines the desired state according to the constraints and optimization criteria.
- Determines the optimum control strategy based on the online, real-time information to achieve the control command by adjusting the manipulated variables or set points at the DCS level. Once such an algorithm is used in the supervisory computer, the response of the process to control strategy commands will gradually move this process from an initial state to a final desired state, avoiding the process constraints and following the optimum path such that one of the following objective functions is obtained minimum cost, minimum energy, maximum yield, or maximum profit.
- Predicts impending alarms based on rigorous mathematical models using present and past history, process data, and control commands. Anticipating alarm conditions in advance of the process reaching these conditions is a vital function of supervisory control. Proper grouping of the pertinent process variables in a preclassified manner allows the severity of the alarms to be identified and allows actions to be pinpointed that can then be initiated quickly by operators.
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