Heuristic algorithm based identification and controller design for a class of unstable systems
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Abstract
newline Nonlinear process loops such as continuous stirred tank reactor,
newlineexothermic stirred reactors with back mixing, biochemical reactor, and
newlinepolymerization reactors are extensively used in chemical industry to convert
newlinethe raw materials into marketable products. To minimize the waste and to
newlinemaximize the production rate, these chemical loops require best possible
newlinecontrol actions. Optimizing the controller for these loops is a complex task
newlinesince, they exhibit multiple steady states based on operating regions. Process
newlinemodels with stable steady states are simple and conventional system
newlineidentification and controller design procedures are sufficient to obtain better
newlineresults. Design of controllers to stabilize chemical process loops and impart
newlineadequate disturbance rejection is critical particularly when these loops are
newlineoperating at unstable regions. System identification procedure is widely considered to develop
newlineapproximated reduced order model from experimental data. This model is
newlineemployed to design a controller. The conventional PID tuning methods
newlineexisting for unstable processes are purely model dependent and the model
newlinebased controller design procedure requires reduced order process models such
newlineas First Order Plus Time Delay (FOPTD) or Second Order Plus Time Delay
newline(SOPTD). The tuning procedure employed for one particular model may not provide a satisfactory response for other process models. For unstable system,
newlineno unique methodology exists to design the controllers.
newlineThe main objective of this research work is to implement heuristic
newlinealgorithm based system identification and controller design procedures for a
newlineclass of unstable process models. In this research work, heuristic algorithms
newlinesuch as Particle Swarm Optimization (PSO), Bacterial Foraging Optimization
newline(BFO), and hybrid algorithms are considered for system identification and
newlinecontroller design manoeuvre. An empirical procedure is also proposed to
newlineassign BFO parameters, to reduce the complexity in existing BFO algorithm.