Gain-scheduled control via filtered scheduling parameters

Gain-scheduled control via LPV system models enjoys LMI-based synthesis methods and in particular parameter-dependent Lyapunov matrices have been employed to successfully reduce conservatism. Those controllers derived via parameter-dependent Lyapunov matrices, however, end up with depending on derivatives of scheduling parameters. Though this can be avoided by approximating derivatives or restricting Lyapunov matrices to be partly constant, the former loses guarantee of performance and stability and the latter can cause conservatism. This paper proposes a synthesis method of gain-scheduled controllers that depend on filtered scheduling parameters, instead of derivatives, with a concrete guarantee of a performance level. Moreover, it is shown that the performance level of conventional derivative-dependent gain-scheduled controllers is recovered with arbitrarily small errors.