Algebraic theory of discrete optimal control for single-variable systems. I. Preliminaries
Algebraic theory of discrete optimal control for single-variable systems. III. Closed-Loop Control
Algorithm 60. Determination of the Jordan canonical form of real matrix
Algorithms for solution of equations and resulting in Lyapunov stability analysis of linear systems
Algoritmus pro výpočet diskrétního přenosu lineární dynamické soustavy
Almost sure tracking for linear discrete-time periodic systems with independent random perturbations.
An algebraic approach to the synthesis of control for linear discrete meromorphic systems
An algebraic framework for linear identification
A closed loop parametrical identification procedure for continuous-time constant linear systems is introduced. This approach which exhibits good robustness properties with respect to a large variety of additive perturbations is based on the following mathematical tools: (1) module theory; (2) differential algebra; (3) operational calculus. Several concrete case-studies with computer simulations demonstrate the efficiency of our on-line identification scheme.
An algebraic framework for linear identification
A closed loop parametrical identification procedure for continuous-time constant linear systems is introduced. This approach which exhibits good robustness properties with respect to a large variety of additive perturbations is based on the following mathematical tools: (1) module theory; (2) differential algebra; (3) operational calculus. Several concrete case-studies with computer simulations demonstrate the efficiency of our on-line identification scheme.
An approach to the Morgan problem
An LPV pole-placement approach to friction compensation as an FTC problem
The concept of combining robust fault estimation within a controller system to achieve active Fault Tolerant Control (FTC) has been the subject of considerable interest in the recent literature. The current study is motivated by the need to develop model-based FTC schemes for systems that have no unique equilibria and are therefore difficult to linearise. Linear Parameter Varying (LPV) strategies are well suited to model-based control and fault estimation for such systems. This contribution involves...
An ordinary differential equation homeomorphic with an essential control system
Analysis of the descriptor Roesser model with the use of the Drazin inverse
A method of analysis for a class of descriptor 2D discrete-time linear systems described by the Roesser model with a regular pencil is proposed. The method is based on the transformation of the model to a special form with the use of elementary row and column operations and on the application of a Drazin inverse of matrices to handle the model. The method is illustrated with a numerical example.
Analytic results for oscillatory systems with extremal dynamic properties
Anticipation in discrete-time LQ control. I. Closed-loop control
Anticipation in discrete-time LQ control. I. Open-loop control
Application of the Drazin inverse to the analysis of descriptor fractional discrete–time linear systems with regular pencils
Application of the Drazin inverse to the analysis of descriptor fractional discrete-time linear systems with regular pencils
The Drazin inverse of matrices is applied to find the solutions of the state equations of descriptor fractional discrete-time systems with regular pencils. An equality defining the set of admissible initial conditions for given inputs is derived. The proposed method is illustrated by a numerical example.
Applications entrée-sortie sur un corps fini
Approximation of fractional positive stable continuous-time linear systems by fractional positive stable discrete-time systems
Fractional positive asymptotically stable continuous-time linear systems are approximated by fractional positive asymptotically stable discrete-time systems using a linear Padé-type approximation. It is shown that the approximation preserves the positivity and asymptotic stability of the systems. An optional system approximation is also discussed.