An investigation on hybrid optimization controller design for auto respiration and vehicle suspension system

Abstract

The two main issues faced by the people are considered as a problem statement and the controller is designed to give a possible solution to reduce the effect. A few years ago, COVID-19 changed the lifestyle of the whole world. Unexpected virus attacks affect the respiration system of the people and many lose their lives. Even though there were medical facilities, as the virus affected a large number of people at a time doctors faced difficulty in addressing everyone on time. Artificial respiration systems will help with such issues in the future which was first problem statement. The second problem statement is to support people with spinal cord issues in traveling happily in the car without any disturbance. People with spinal cord issues will not prefer long travel as feel discomfort when the car encounters disturbances like bumps, pits, and turns on the road. Here the bumps are considered as disturbances and tried to give a solution for the problem. The Hybrid controllers are considered for controlling the airway pressure in the auto respiration system and vibration in the car suspension system. The hybrid controllers used here are Hybrid Model Predictive PID Controller, Hybrid Ant colony - Genetic Algorithm based Fractional Order PID, Fmincon-Pattern Search based PID, and Fminsearch - Simulated Annealing Algorithm based controllers. The model is designed for both the problem statements and the simulation work is done to verify the control action. newline