Integrated instrumentation and control design using finite signal-to-noise models

In this paper, new signal-to-noise models are used to characterize instrumentation design specifications and an integration of control and instrumentation design is achieved by simultaneously designing the feedback control law and the instrument signal-to-noise ratios to meet performance requirements for the closed loop system. Iterative algorithms are proposed to find locally optimal solutions. Assuming that the signal-to-noise ratio is directly related to the instrumentation cost, this integration provides a systematic procedure to design a low cost control system. More importantly, this procedure identifies the performance limiting component of a closed loop system.