Chromatographic Methods

Abstract

The time-varying state-feedback control of a constrained linear state-space system is addressed via Linear Matrix Inequality (LMI) based optimization methods. The constraints are specified as ellipsoidal or hyperplane constraints on the inputs and states, and the approach presented allows these to be specified without any conservativeness. The control action is specified in terms of both feedback and feedforward components. Uncertainty in the system is modeled by perturbations in a linear fractional transform (LFT) representation, and also by bounded disturbances. As a single-step design procedure the approach gives a time-varying controller capable of steering the state to a specified reference while satisfying the constraints. The method can be applied in a model predictive strategy to allow for higher performance as the state, and control input, move away from the constraint boundaries.