Modeling and Control of Non-Linear CSTH Process using Hybrid Optimized Technique

The highly non-linear Continuous Stirred Tank Heater process (CSTH) is modeled using appropriate process dynamics by considering multivariable factors in all chemical industries using Multi-Input Multi-Output (MIMO) system to prepare an extremely saturated solution with the required conditions. The model's transfer function and state space are created by applying the first principle method to successfully regulate the Level and Temperature of the CSTH process using specified time-domain parameters and a suitable conventional Proportional Integral Derivative (PID) controller. The Ziegler-Nichols method aims to estimate gain factor for controller. However, more effective and efficient control of the process is still required. Advanced optimization approaches such as Genetic Algorithm, Pattern Search, Fmin Search, and Hybrid Optimization Algorithm are more commonly used to fine-tune the controller's gain factor. Finally, a quantitative example is provided using a MATLAB simulation result to highlight the benefits and applicability of the proposed approach. The obtained result is validated by the experimental data from the real-time Process.