The computation of H_∞ and LQG optimal controllers is considered for process control applications. There are many process control problems where significant uncertanties exist in the system models which therefore require robust control designs. A simple solution for the optimal H_∞ robust design problem is considered and the relationship to super-optimal solutions is discussed. For special types of weighted plant model the main H_∞ equations to be solved are shown to be decoupled so that the calculations are similar to the scalar case. This situation is shown to arise when a mixed-sensitivity cost-function is selected and the plant has an interaction structure typical of many hot or cold rolling mill gauge control applications. A simplified design procedure is also introduced which further simplifies the calculations of the optimal controller and enables standard eigenvector/eigenvalue algorithms to be employed in solving the equations. The procedures are illustrated using a multivariable metal processing control design example.

Inspec keywords: gauges; process control; linear quadratic Gaussian control; metallurgical industries; robust control; eigenvalues and eigenfunctions; multivariable control systems; H∞ control; rolling mills

Other keywords: weighted plant model; eigenvector algorithm; multivariable metal processing control design; rolling mill gauge control application; interaction structure; superoptimal solution; mixed sensitivity cost function; process control application; LQG optimal control design; H_∞ multivariable robust controller design

Subjects: Control applications in metallurgical industries