Tadeusz Kaczorek (Białystok Technical University, Faculty of Electrical Engineering, Białystok, Poland)
The notion of output-reachability is extended for positive linear discrete-time systems with delays described by the state equations, by the transfer matrices and by the impulse matrices. Necessary and sufficient conditions for the output-reachability are established. The classical Cayley-Hamilton theorem is extended for coefficient matrices of the system impulse matrix. The considerations are illustrated by numerical examples.
keywords: linear, discrete-time, system, delay, output-reachability, positive system
Michael M. Tchaikovsky, Alexander P. Kurdyukov (Institute of Control Sciences, RAS, Moscow, Russia)
The anisotropic norm of a linear discrete-time-invariant system is a measure of system output sensitivity to stationary Gaussian input disturbances with mean anisotropy bounded by some nonnegative parameter. The mean anisotropy characterizes the predictability (or coloredness) degree of stochastic signal. The anisotropic norm of a system is an induced norm, which limiting cases are H2- and H∞- norms as α → 0 and α → ∞ respectively. In literature a method for numerical computation of the anisotropic norm was proposed. This method involves linked Riccati and Lyapunov equations and associated special type equation. This paper develops a method for computing the anisotropic norm that reduces to finding a strongly rank-minimizing solution of linear matrix inequality and a solution of special type nonlinear algebraic equation.
keywords: differential entropy, anisotropy, induced norm, linear matrix inequality
Ewa Snitkowska, Włodzimierz Kasprzak (Warsaw University of Technology, Institute of Control and Computation Engineering, Warsaw, Poland)
An important source for information about digital image content is the texture of image regions. This paper presents a feature extraction approach that is based on independent component analysis (ICA). In ICA a transformation of measured vectored time series is discovered via blind signal processing that gives statistically independent source signals. In our approach every textured region is considered as a mixture of (initially unknown) statistically independent source regions, scanned to 1-D time series. After these sources, called independent components, are extracted by ICA, optimally for given image type, the mixing coefficients of particular region constitute its feature vector. The quality of such features is experimentally verified and compared to other common feature schemas. The comparison procedure explores the Fisher information criterion and classification results for feature evaluation. Our application field is the analysis of angiography images. It is difficult for medical doctors properly to classify such images, hence an automatic tool could provide support in this matter. We demonstrate the usefulness of ICA-based features for automatic evaluation of angiography images.
Mostafa Rachik, Abdessamad Tridane, Mustapha Lhous, Zakia Tridane (Département de Mathématiques et Informatique, Faculté des Sciences Ben M'Sik, Casablanca-Morocco)
Consider the discrete perturbed controlled nonlinear system given by
and the output function , where is a disturbance which perturb the system. The disturbance e is said to be -admissible if , where is the output signal corresponding to the uninfected system. The set of all - admissible disturbances is the admissible set . The characterization of is investigated and practical algorithms with numerical simulation are given. The admissible set for discrete delayed systems is also considered.
Peter Hippe (Lehrstuhl für Regelungstechnik, Universität Erlangen-Nürnberg, Erlangen, Germany)
The purpose of this contribution is to show, that by inserting an appropriate nonlinear dynamic model at the output of the compensator, basically all known techniques for windup prevention developed for amplitude restrictions are also applicable in the presence of actuators with joint amplitude and rate saturation.
Zdzisław Gosiewski, Arkadiusz Mystkowski (Technical University of Białystok, Mechanical Department, Białystok, Poland)
The paper presents a robust control of the motion of a shaft supported by magnetic bearings. The dynamics of magnetic suspension systems are characterized by their instability and uncertainty of the plant. Therefore apart from the model of the plant we determined a model of the parametrical uncertainty. The uncertainty is modeled as additive. Current stiffness kiand displacement stiffness ks are assumed to be the uncertainty parameters. The performance of the closed-loop system, signals limits, and the disturbances influence are determined with the aid of the weighting functions. Three weighting functions are designed: We(s) – penalizing the error signal e, Wu(s) – penalizing the input signal u, and Wy(s) – penalizing the output signal x. For these functions and the uncertainty model we assigned the augmented control model. For the augmented control system we assigned the robust controller. The robust controller assures high quality of control despite of the uncertainty model of the plant, disturbances in the systems, signals limits and high dynamics of the system. Next the H∞ closed-loop system is compared with the standard PID closed-loop system. Finally simulation results show effectiveness of the control system as good initial responses/transient responses and robustness of the designed robust controller.
keywords: active magnetic bearings (AMB), robust controller, weighting functions, H∞ norm
Abdelhalim Tlemcani, Hachemi Chekireb, Mohamed Seghir Boucherit (Laboratoire de Commande des Processus, Ecole Nationale Polytechnique, Algers, Algeria)
Based on the Lyapunov synthesis approach, several adaptive fuzzy control schemes have been developed during the last few years. In this paper we develop a robust adaptive fuzzy control law for MIMO nonlinear system class. The proposed method uses the Sugeno-Takagi fuzzy system as an universal approximator of continuous nonlinear functions. The adaptive control law is established based on the Lyapunov method. So, the output convergence, the boundedness of the parameters and the states are derived. Moreover, the fuzzy adaptive law incorporates a compensatory sliding term, which compensates for effects of the unavoidable reconstruction errors.