Modern vehicles are equipped with a complex suite of computing (cyber) and electromechanical (physical) systems. Holistic design, modeling, and optimization of such Cyber-Physical Systems (CPS) requires new techniques capable of integrated analysis across the full CPS. This dissertations introduces two methods for balancing cyber and physical resources in a step toward holistic co-design of CPS. First, an ordinary differential equation model abstraction of controller sampling rate is developed and added to the equations of motion of a physical system to form a holistic discrete-time-varying linear system representing the CPS controller.
Using feedback control, this cyber effector, sampling rate, is then co-regulated alongside physical effectors in response to physical system tracking error. This technique is applied to a spring-mass-damper, inverted pendulum, and finally to attitude control of a small satellite (CubeSat). Additionally, two new controllers for discrete-time-varying systems are introduced; a gain-scheduled discrete time linear regulator (DLQR) in which DLQR gains are scheduled over time-varying sampling rates, and a forward-propagation Riccati based (FPRB) controller. The FPRB CPS controller shows promise in balancing cyber and physical resources.