A modification of well-known controllability and observability tests using Lyapunov equations and Gramians yields a reliable tool for controllability and observability testing for linear continuous and discrete time systems, as well as an alternative procedure to determine controllable, observable and minimal system realizations.

 The most part of papers dealing with linear parameter varying systems (LPV) control assumes a perfect parameter knowledge. In this note the scheduling physical parameters are supposed to be inexactly measured. Continuous time polytopic LPV systems are considered and an observer based controller is proposed to guarantee internal stability and performance in terms of exact asymptotic output regulation at a desired set point, despite the presence external disturbances. An iterative LMI procedure is given for computing the maximum parametric uncertainty level that can be tolerated to maintain the exponential stability of the closed loop system. The controller is scheduled by the noisy parameter readings and a quadratic affinely parameter-dependent Lyapunov function is used. This results in a general approach encompassing constant controller gains and/or parameter independent Lyapunov functions.

 This work considers the stabilization of linear time invariant high order systems with two unstable poles plus time delay. For this, we will propose a simple observer based controller in order to stabilize the system. Numerical examples and an electronic implementation of the proposed scheme are presented in order to illustrate the performance of the closed loop system.

 This paper proposes a methodology for guaranteed state estimation of multivariable linear discrete time systems in the presence of bounded disturbances and noises. A zonotopic outer approximation of the state estimation domain is computed based on the minimization of the P-radius associated to the zonotope. The proposed method leads to an off-line Polynomial Matrix Inequality (PMI) optimization problem. A sub-optimal solution of this problem is obtained using relaxation techniques. An illustrative example is analyzed in order to highlight the performance of the proposed algorithm.

 This article focuses on the best achievable tracking performance of unstable tall plant models. The work is presented for discrete time, LTI systems, when an exponentially decaying signal is considered as reference. Closed form expressions for the best tracking performance for one and two degree of freedom control architectures are presented. As an application of those results, they are used in an example to compute the performance gains in the control of originally tall systems which have been squared-up by adding control input channels.