Stability radius for structured perturbations and the algebraic Riccati equation
Systems & Control Letters
Structured singular values and stability analysis of uncertain polynomials, part 2: a missing link
Systems & Control Letters
A formula for computation of the real stability radius
Automatica (Journal of IFAC)
Robust and optimal control
Robust Control: The Parametric Approach
Robust Control: The Parametric Approach
The Set of Stable Polynomials of Linear Discrete Systems: Its Geometry
Automation and Remote Control
Automation and Remote Control
Stable polyhedra in parameter space
Automatica (Journal of IFAC)
Polynomial solution to stabilization problem for multivariable sampled-data systems with time delay
Automation and Remote Control
Design of the low-order controllers by the H∞ criterion: A parametric approach
Automation and Remote Control
Plane geometry and convexity of polynomial stability regions
Proceedings of the twenty-first international symposium on Symbolic and algebraic computation
Automation and Remote Control
Randomized methods of stabilization of the discrete linear systems
Automation and Remote Control
D-decomposition technique state-of-the-art
Automation and Remote Control
Convexity of the coefficient sequence and discrete systems stability
Automation and Remote Control
Fixed order controller design subject to engineering specifications
Automation and Remote Control
Study of D-decompositions by the methods of computational real-valued algebraic geometry
Automation and Remote Control
| Hi-index | 22.14 |
The challenging problem in linear control theory is to describe the total set of parameters (controller coefficients or plant characteristics) which provide stability of a system. For the case of one complex or two real parameters and SISO system (with a characteristic polynomial depending linearly on these parameters) the problem can be solved graphically by use of the so-called D-decomposition. Our goal is to extend the technique and to link it with general M-@D framework. In this way we investigate the geometry of D-decomposition for polynomials and estimate the number of root invariant regions. Several examples verify that these estimates are tight. We also extend D-decomposition for the matrix case, i.e. for MIMO systems. For instance, we partition real axis or complex plane of the parameter k into regions with invariant number of stable eigenvalues of the matrix A+kB. Similar technique can be applied to double-input double-output systems with two parameters.