A major difficulty encountered in the application
of linear parameter-varying (LPV) control is the complexity of
synthesis and implementation when the number of scheduling
parameters is large. Often heuristic solutions involve neglecting
individual scheduling parameters, such that standard LPV controller
synthesis methods become applicable. However, stability
and performance guarantees are rendered void, if controller
designs based on an approximate model are implemented on
the original plant. In this brief, a synthesis method for LPV
controllers that achieves reduced implementation complexity is
proposed. The method is comprised of first synthesizing an initial
controller based on a reduced parameter set. Then closed-loop
stability and performance guarantees are recovered with respect
to the original plant, which is considered to be accurately modeled.
Iteratively solving a nonconvex bilinear matrix inequality
may further improve performance. A two-degrees-of-freedom
(2-DOF) and three-degrees-of-freedom robotic manipulator is
considered as an illustrative example, for which experimental
results indicate a good performance for controllers of reduced
scheduling order. Furthermore, in the 2-DOF case, controller
performance has been significantly improved.