Analytic design of adaptive sampling control law in sampled-data systems

Abstract

A unified analytic approach is presented for the design of adaptive sampling control law in sampled-data systems. This is accomplished by introducing an objective function which measures the performance of the sampler over each sampling interval, and then minimize it to obtain the sampling control law. A total of six different control laws, which are functions of the sampled function, are derived from the generalized objective function by selecting different weighting coefficients. More than half of these control laws are identical to existing results. Similar control laws as functions of the system output can be derived as well. Also included are some experimental results on the performances of four representative control laws in a second-order system subject to step disturbance.