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).