Intelligent control of a nonlinear tank reactor based on Lyapunov direct method

In this paper, intelligent control of the outlet flow concentration of a non-thermic catalytic continuous stirred tank reactor (CSTR) is addressed. Control command is the sum of two control commands: steady state and transient commands. A fuzzy controller generates transient control command pushing the system towards the reference (desired situation). Steady state control command is generated to maintain steady state situation (based on the concept of ´control equilibrium point´). This research is performed in simulation environment; however, the mathematical model of the system is not used during stability analysis to keep the methodology useful in case of considerable uncertainties; instead, some obvious facts about the system in the form of fuzzy rules are used for stability analysis, namely ´fuzzy rough model´. Using this technique, Lyapunov asymptotic stability of control system is proved. For comparison, the case study is also controlled by neuro-predictive algorithm. The studied CSTR is known as a very good example of neuro-predictive control application; however, the newly offered hybrid intelligent method leads much better reference tracking performance as well as less change in control command (which is very important in implementation).