Design and Development of Observer Based Control Strategies for Linear and Non Linear Systems and Its Remote Monitoring Through Iot

Abstract

Observer-based control approaches are critical for enhancing the stability and performance newlineof dynamic systems in a variety of domains such as engineering, exoskeleton newlinerobotics, and control theory. This abstract provides a thorough introduction to newlineobserver-based control methods, with applications to both linear and nonlinear processes. newlineThese methodologies enable accurate state estimates and efficient control law newlinesynthesis for a robust control approach. newlineObservers are key components in the field of linear dynamics that estimate the newlineunmeasured states of a system using available measurements. Active Disturbance newlineRejection Control (ADRC) is a new control approach that incorporates state estimate, newlinedisturbance estimation, and control in one framework. To assess the entire newlineinfluence of disturbances, uncertainties, and model errors, ADRC uses various forms newlineof extended state observer (ESO). The calculated disturbance is then eliminated in newlinethe control law, which permits robust tracking and disturbance rejection without the newlineneed for detailed system dynamics knowledge. ADRC has received a lot of attention newlinein recent years because of its effectiveness in dealing with uncertainties and disturbances newlinein linear systems. These methods find extensive use in fields like aerospace, newlinewhere accurate state estimation is crucial for stable and precise control. newlineThe ADRC framework s efficacy has been demonstrated by expanding its reach newlineto nonlinear systems. The concept of an extended state of the observer is especially newlineuseful for nonlinear systems since it permits the estimate of both state variables and newlinetotal disturbance. Nonlinear ADRC uses ESO and control law adaptation to control newlinethe impact of disturbances and uncertainties on system behavior. newlineBecause of the complexities of nonlinear dynamics, difficulties with state estimation newlineand control for nonlinear systems are increased. The combination of ADRC newlineand Sliding Mode Control (SMC) results in a powerful approach. Sliding Mode Convi newlinetrol produces a control signal that drives the system traject