Modeling Nonlinear Physical Systems in a Real-Time Operating System Environment for Control and Cyber Threat Mitigation

• Published in: Journal of Electrical Systems Vol. 20; no. 3s; pp. 1996 - 2003
• Main Authors: Deshkar, Prarthana A, Deshmukh, Maithili S, Puri, Nischal, Patil, Arvind R Bhagat, Thakare, Amit, Dahigaonkar, Dipak J
• Format: Journal Article
• Language: English
• Published: Paris Engineering and Scientific Research Groups 31.03.2024
• Subjects: Automation; Control systems; Cruise control; Cyber-physical systems; Embedded systems; Engineering schools; Equations of motion; Equilibrium; Genetic algorithms; Infrastructure; Network control; Nonlinear control; Nonlinear differential equations; Nonlinear systems; Nonlinearity; Potential energy; Predictive control; Real time; Robotics; Robots; Sensors; Series expansion; Simulation; State space models; Taylor series; Transfer functions; Yaw
• ISSN: 1112-5209
• DOI: 10.52783/jes.1791

Nonlinearity control and interconnection between physical systems are essential for many contemporary systems. Cyber Physical systems came about because of the growing number of security concerns with network control systems. Nonlinear physical systems are the primary subject of this study's investigation into control and cyber threat mitigation. Nonlinear physical systems are the focus of this study, which also delves into their control, modelling, and real-time implementation. Here, physical systems are defined as two kinds of benchmark nonlinear robotic systems: the Segway transporter and the cruise control system. Many see the Segway as an unstable and nonlinear physical system. By factoring in kinetic and potential energy, Lagrangian dynamics has allowed for the derivation of equations of motion. Next, a state-space model of the system is obtained by linearizing the nonlinear differential equations using Taylor series expansion of functions. This model is then transformed into two transfer functions, one for the tilt angle and one for the yaw angle. The Model Predictive Controller (MPC), GA Tuned PID, and PID are the building blocks of MATLAB's effective simulation study of nonlinear control.