Nonlinear and Intelligence Controllers for HCV Infection, HVAC System, and Electric Vehicles

Abstract

In the last five decades a remarkable improvement has been seen in the implementation of Nonlinear and Artificial intelligent controller for the complex dynamic systems. Nonlinear controllers are getting popular due to its performance and the availability of high processing micro-controllers to implement the complex control algorithms. Similar to nonlinear controllers, artificial intelligent neural networks have such internal architecture which can easily capture the complex dynamic behavior between input and output of any system. These sophisticated architectures of neural networks make them ideal for system identification and controller design for complex dynamic system. With the development of modern technology, a need of high precision and sophisticated controllers rise to achieve the desired response of complex dynamic systems. In this thesis, nonlinear controllers for Hepatitis C infection and HVAC system while artificial neural networks for vehicle dynamics control are proposed. Hepatitis C Virus (HCV) is the cause of Hepatitis C which is a liver disease. Hepatitis can cause serious health issues and may lead to liver cancer. A dynamic model defining the behavior of virions, uninfected hepatocytes and infected hepatocytes in human body under two drugs as control action is used to study the performance of Integral Sliding Mode Control (ISMC) , Double Integral Sliding Mode Control (DISMC), Integral Terminal Sliding Mode Control (ITSMC) and Fractional Order Terminal Sliding Mode Control (FOTSMC) to cater the HCV infection inside the human body. As tire blowout causes serious accidents on highways. Using breaking and actuation torque an Artificial Intelligent (AI) controller is designed. With automatic control signals the stability of a ground vehicle is enhanced when vehicle is subjected to tire blowout. AI based controller incorporates for the nonlinearities in tire and vehicle body. A detailed 7 DOF vehicle model incorporating longitudinal motion, lateral motion, steering angle and side slip angles have been used for the analysis of proposed controller design. Torques are included for stability in a distributive architecture. In healthcare critical units like operation theaters and intensive care units etc., both the patient and healthcare workers desire different temperature environment at different stages which depend upon the condition of patient and requirements of surgical procedures. Therefore, the need of dynamic set points zone temperature controller is required to achieve this objective. Two Sliding Mode Controller (SMC) based DISMC and ITSMC controllers are designed in the regard to achieve dynamic set point with minimum overshoots from the required set point and quick convergence to the desired zone temperature to provide better healthcare facilities to the patients as compared to other commercial and residential buildings. All the proposed controller are evaluated and the response have been presented with comparison to the other controller and best results are also highlighted.