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Adaptive control of a chemical process system
Author(s) -
Ahlgren Theodore D.,
Stevens William F.
Publication year - 1971
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690170235
Subject(s) - control theory (sociology) , adaptive control , controller (irrigation) , process (computing) , pid controller , control engineering , process control , computer science , a priori and a posteriori , control system , adaptation (eye) , interval (graph theory) , stability (learning theory) , temperature control , engineering , control (management) , mathematics , artificial intelligence , philosophy , physics , electrical engineering , optics , epistemology , combinatorics , machine learning , agronomy , biology , operating system
Modification of parameters in the conventional controller equation usually is necessitated by uncontrollable process parameter drifts which occur during the operation of the large scale continuous processes typically found in the chemical industry. To this end, a normalized version of the model reference adaptive control system, including suitable procedures for adjusting the adaptive loop gains, was developed and demonstrated to provide excellent adaptive performance for a single concentration control loop for a simulated stirred‐tank chemical reactor. The three constants in a conventional PID controller were simultaneously adjusted to accomplish this adaptation. Equally excellent adaptive performance was achieved in an interacting control loop scheme simulated by control of both the concentration and the temperature in the same stirred‐tank reactor. In both cases adaptation was achieved in a time interval which was sufficiently short to make this method of adaptive control feasible for use in a real processing situation. Models needed for implementation of the model reference adaptive control scheme were easily developed. In a real application these models could be easily developed from studies which could take place during prestartup or early operations of the process; hence no a priori knowledge would be required. A wide range of adaptive loop gains was demonstrated to provide a stable overall control system. A high degree of stability was demonstrated for the overall system despite the initiation of large extraneous load upsets occurring during the operation of the adaptive control system. The method presented has not been rigorously proven to be applicable to every real control problem requiring adaptive control. However, the method was demonstrated to be highly effective over a wide range of required controller adjustments in cases similar to those encountered in large continuous processes. Thus the method merits serious consideration for possible implementation whenever adaptive control is required.