DESIGN AND IMPLEMENTATION OF MODEL BASED CONTROLLERS FOR BIOLOGICAL SYSTEMS

Skin cancer is one of the most prevalent cancers worldwide, with millions of cases diagnosed each year. Malignant melanoma, an aggressive form of skin cancer, presents significant challenges in treatment. Early detection and targeted therapies improve survival outcomes. However, conventional drug delivery methods frequently harm healthy cells due to inaccurate dosing. To address these challenges, an electrical analog model of the skin is developed, representing layers such as the dermis, subcutaneous tissues, bones, and muscles. This biological system is formulated into a mathematical model using its electrical circuit equivalent. The objective is to control the drug flow rate to maximize absorption by cancerous cells while reducing diffusion to surrounding healthy tissue. Simulation studies assess drug absorption and diffusion rates across various skin layers. The electrical circuit model is designed using Proteus, while MATLAB analyzes absorption rates for individual and combined layers.

 

To enhance control, several advanced control strategies are implemented to regulate drug diffusion rates effectively. A conventional PID (Proportional-Integral-Derivative) controller is integrated to manage the system, and a comparative analysis is conducted between the traditional PID and its optimized version. The optimized PID controller is fine-tuned to minimize error and improve the precision of drug delivery. Furthermore, a Model Predictive Controller (MPC) is also incorporated to predict and adjust the drug delivery dynamically based on future states, optimizing drug absorption and diffusion. A similar comparison is performed between the standard MPC and the optimized MPC, where optimization techniques enhance performance and minimize undesirable diffusion. In addition, an Internal Model Control (IMC) approach is employed to improve the system's robustness and control. The optimized IMC controller is implemented to better handle the dynamics of drug absorption and minimize the effect on healthy tissues. A comparative analysis of PID, optimized PID, MPC, optimized MPC, and IMC controllers provides deeper insights into optimizing drug delivery systems for more effective and controlled skin cancer treatments.

 

KEYWORDS: Absorption Rate, Diffusion Rate, Drug Delivery, Electrical Analog, Mathematical Modeling, Skin Cancer, Proteus, PID Controller, Optimized PID, Model Predictive Controller (MPC), Optimized MPC, Internal Model Control (IMC), Optimized IMC.

Absorption Rate Diffusion Rate Drug Delivery Electrical Analog Mathematical Modeling Skin Cancer Proteus PID Controller Optimized PID Model Predictive Controller (MPC) Optimized MPC Internal Model Control (IMC) Optimized IMC.