Coupled Cyber–Physical System Modeling and Coregulation of a CubeSat

Abstract

We propose the application of state-space techniques to develop a novel coupled cyber-physical system (CPS) model and use feedback control to dynamically adjust CPS resource use and performance. We investigate the use of a gain scheduled discrete linear quadratic regulator controller and a forward-propagation Riccati-based controller to handle the discrete-time-varying system. We demonstrate the value of our approach by conducting a disturbance-rejection case study for a small satellite (CubeSat) application in which resources required for attitude control are adjusted in real-time to maximize availability for other computational tasks. We evaluate CPS performance through a set of metrics quantifying physical system error and control effort as well as cyber resource utilization and compare these with traditional fixedrate optimal control strategies. Results indicate that our proposed coupled CPS model and controller can provide physical system performance similar to fixed-rate optimal control strategies but with less control effort and much less computational utilization.

Optimization and Control of Cyber-Physical Vehicle Systems

“…Finally, our recent co-regulation work is similar to feedback scheduling and time-varying sampling and control. We propose a linear model relating sampling rate to controller performance, which is then added to the linear time-invariant (LTI) model of the physical system [ 67 , 108 , 109 , 127 ]. Assuming a physical system modeled as: where is the physical state vector, the system matrix, the control matrix and the physical control input, we seek a system of the form: where components with subscript c are the cyber system analogs to the physical model components.…”

“…In [ 67 , 127 ], using feedback control techniques, we design two discrete-time varying controllers for the physical system. The first utilizes gain-scheduling, where controller gains are “scheduled” (Note that this is not the same as RTS task scheduling, but rather controller gains are selected at each time step for the system linearized over various operating points.)…”

“…These metrics capture a portion of RTS utilization, the error of the system trajectory with respect to its reference value and the control effort of the physical actuators. We used these metrics in a CubeSat CPVS co-regulation application to provide a domain-inspired characterization of potential savings in control effort and to make cyber utilization realizable [ 127 ].…”

Co-Regulated Consensus of Cyber-Physical Resources in Multi-Agent Unmanned Aircraft Systems

“…For example, controllers are typically designed to handle worst-case conditions or maneuvers while providing good margins of stability and robustness [3,4]. Selection of sampling rate, or period of execution of the control law often becomes a software or real-time system implementation issue [5]. However, even if co-designed, cyber and physical resources should be co-regulated at run-time, in conjunction with holistic (i.e., both physical and cyber)…”

Complete Models of Transmission-connected Photovoltaic Plant Using Modularity Principle for Power System Small Signal Stability Study

“…The electric cyber-physical system is helpful to build a smart grid by using cyber-system-based intelligence to maintain correct, and to detect and react to faults and attacks (7) (8) . Under this circumstance, some control signals may come from the cyber system.…”