Control theory and engineering

Control engineering or control systems engineering is an engineering discipline that deals with control systems, applying control theory to design equipment and systems with desired behaviors in control environments. The discipline of controls overlaps and is usually taught along with electrical engineering and mechanical engineering at many institutions around the world. The practice uses sensors and detectors to measure the output performance of the process being controlled; these measurements are used to provide corrective feedback helping to achieve the desired performance. Systems designed to perform without requiring human input are called automatic control systems (such as cruise control for regulating the speed of a car). Multi-disciplinary in nature, control systems engineering activities focus on implementation of control systems mainly derived by mathematical modeling of a diverse range of systems. Modern day control engineering is a relatively new field of study that gained significant attention during the 20th century with the advancement of technology. It can be broadly defined or classified as practical application of control theory. Control engineering plays an essential role in a wide range of control systems, from simple household washing machines to high-performance fighter aircraft. It seeks to understand physical systems, using mathematical modelling, in terms of inputs, outputs and various components with different behaviors; to use control system design tools to develop controllers for those systems; and to implement controllers in physical systems employing available technology. A system can be mechanical, electrical, fluid, chemical, financial or biological, and its mathematical modelling, analysis and controller design uses control theory in one or many of the time, frequency and complex-s domains, depending on the nature of the design problem. Control engineering is the engineering discipline that focuses on the modeling of a diverse range of dynamic systems (e.g.

Control theory and engineering

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Data-driven LPV Disturbance Rejection Control with IQC-based Stability Guarantees for Rate-bounded Scheduling Parameter Variations

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Data-driven LPV Disturbance Rejection Control with IQC-based Stability Guarantees for Rate-bounded Scheduling Parameter Variations