Method and system for process control with complex inference mechanism using qualitative and quantitative reasoning
First Claim
1. A process control method for controlling a plurality of different types of control effectors individually or in a combination of the control effectors, comprising the steps of:
- generating, from combinations of current operation quantities for said plurality of control effectors, changeable combinations of operation quantities as operation candidates for a plurality of control effects;
arithmetically determining predicted values of a plurality of control objective items in a process after lapse of a predetermined time from the time when an operation is carried out with said generated changeable combinations of operation quantities;
arithmetically determining fitnesses of said arithmetically determined predicted values to membership functions predetermined with fuzzy quantities for the respective control objective items;
assigning predetermined weights to said fitnesses depending on said control objective items, respectively, to obtain weighted fitnesses and superposing said weighted fitnesses so as to arithmetically determine satisfaction grades for the respective control effector operation candidates;
outputting, as operation quantities, one of said control effector operation candidates having a maximum satisfaction grade as a result of said superposing operation; and
controlling each of said plurality of control effectors using said outputted one of said control effector operation candidates.
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Abstract
A process control system for controlling a process exhibiting both linear behavior and non-linear behavior with a plurality of control quantities has a knowledge base storing therein universal facts, production rules including expert'"'"'s empirical rules, meta rules describing flows of inferences, algorithm methods by mathematical expressions and membership functions referenced in fuzzy inference and a complex inference mechanism. The complex inference mechanism is composed of a complex fuzzy mechanism for inferring directly predicted values on a multi-dimensional space generated by a plurality of elements for evaluation and predicted control objectives evaluated previously with fuzzy quantities, a predicting fuzzy mechanism having the input supplied with the predicted values for determining arithmetically correlation to the membership functions determined previously with the fuzzy quantities and a satisfaction grade obtained by imparting weight to the correlation for each of the control objectives to thereby determine such a combination of the control quantities for control effectors to vary the operation states thereof from the current operation states that the satisfaction grade becomes maximum, and a main inference mechanism having the input supplied with process data to thereby compare selectively the process data with the knowledge stored in the knowledge base for thereby making decision of the process behavior through a forward fuzzy inference with the aid of the production rules based on the empirical knowledge and manage the whole process control system including the complex fuzzy inference mechanism, the predicting fuzzy inference mechanism and the knowledge base. The system can be advantageously employed for intra-tunnel ventilation control and other processes exhibiting both linear and non-linear behaviors.
48 Citations
1 Claim
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1. A process control method for controlling a plurality of different types of control effectors individually or in a combination of the control effectors, comprising the steps of:
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generating, from combinations of current operation quantities for said plurality of control effectors, changeable combinations of operation quantities as operation candidates for a plurality of control effects; arithmetically determining predicted values of a plurality of control objective items in a process after lapse of a predetermined time from the time when an operation is carried out with said generated changeable combinations of operation quantities; arithmetically determining fitnesses of said arithmetically determined predicted values to membership functions predetermined with fuzzy quantities for the respective control objective items; assigning predetermined weights to said fitnesses depending on said control objective items, respectively, to obtain weighted fitnesses and superposing said weighted fitnesses so as to arithmetically determine satisfaction grades for the respective control effector operation candidates; outputting, as operation quantities, one of said control effector operation candidates having a maximum satisfaction grade as a result of said superposing operation; and controlling each of said plurality of control effectors using said outputted one of said control effector operation candidates.
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Specification