Optimizing Stability and Performance in Fluid Catalytic Cracking Unit Using a Brown-Bear Optimization Algorithm for Adaptive Neuro Sliding Mode Control

Stiff delayed systems seek to improve the stability and performance of complicated systems with large time lags and uncertainty. In the context of a fluid catalytic cracking unit, this technique aimsto increase operational efficiency and reliability by resolving system delays and variabilities, resulting in consistent output and optimal performance. The challenge is to improve the stability and efficiency of a fluid catalytic cracking unit by rigorously improving its performance underlarge time delays and system uncertainty. In this manuscript,the proposed Optimizing Stability and Performance in Fluid Catalytic Cracking Unit Using a Brown-Bear Optimization Algorithm for Adaptive Neuro Sliding Mode Control(OSP-FCC-BBOA) proposes a strong steady state Brown-bear Optimization Algorithm (BBOA) technique. The BBOA approach is utilizedto maximize the gain parameters of the Adaptive Neuro Sliding Mode Control (ANSMC) controller. The objective of the manuscript is to improve the stability and performance of a Fluid Catalytic Cracking (FCC) unit. Delays are caused by catalyst hold-ups in the standpipes that link the riser and regenerator. Demonstrate that delays and stiffness can be handled by the proposed BBOA technique. Furthermore, the proposedapproach has the ability to adjust controller parameters and optimize process parameters at the same time. The proposed technique is implemented on MATLAB. The simulation results display that the proposed framework can effectively handle the delay and stiffness properties of the FCC process and improve the closed-loop control performance. Comparative analysis shows that the proposed method obtains the minimum error rate of 0.10%, mean error rate of 0.14%, which is better than the optimization of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey wolf optimizer (GWO) and Harris Hawks Optimization (HHO) methods. The results show the effectiveness of BBOA in improving the stability, disturbance rejection ability and controller tuning performance of stiff delayed FCC systems.