Integrating instrumentation and control design

Instrument precision is characterized by its signal-to-noise ratio, employi ng a new noise model. In this paper, this measure of precision of each inst rument is used to characterize instrumentation, and an integration is achie ved by jointly optimizing the feedback control law and the instrument signa l-to-noise ratios to meet control system performance requirements. Iterativ e 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 contr ol system. More importantly, this procedure identifies the performance-limi ting components of a control system, identifies where to spend money on a s ystem, and generates component design requirements from closed loop system performance criteria.