A novel optimized fractional order system for tuning biological parameters

In contemporary biological research and applications, control systems have become indispensable for understanding and managing the intricate dynamics of the human biological system. Given the critical role of components such as the pancreas structure, protein formation, insulin and glucose regulation, and the genetic regulatory network (GRN), any disturbances in these systems can lead to severe health issues. To overcome these issues, to introduced a novel hybrid controller called the fuzzy lion-based optimized fractional order system (FL-OFOS) for evaluating the performance of the system. This controller aims to efficiently govern and regulate key components of the human biological system, including insulin dynamics, protein synthesis, pancreas functionality, and GRN management. The controller is specifically tailored to regulate insulin, protein synthesis, pancreas function, and GRN dynamics within the human biological system. The optimization of biological parameter values is achieved through the incorporation of the fuzzy lion function. The results of this study highlight the efficacy of the FL-OFOS controller in optimizing and regulating various biological parameters. The system demonstrates minimal error rates, rapid response times, reduced overshoot, and high control precision and accuracy. The proposed controller achieves a minimal error rate of 0.98%, with only minor overshoot occurring in the outcomes. As a result, the FL-OFOS controller offers substantial gains and delivers optimal results in the realm of biological systems.