Set-Membership Estimation for Industrial Processes with Uncertain Scheduling Parameters

The set-membership estimation problem is studied for a class of industrial processes, which is modelled by discrete linear parameter-varying (LPV) systems with uncertain scheduling parameters. Considering the unknown-but-bounded (UBB) process and measurement noise, a sufficient condition for the existence of the set-membership estimation is given with the norm-bounded uncertainty of the scheduling parameters. A convex optimization method for calculating the ellipsoidal feasible state set with guaranteed true states is proposed by solving a time-varying linear matrix inequality (LMI). Finally, a CSTR simulation shows the effectiveness of the proposed approach.