Recently, the linearization of a class of unknown discrete-time dynamic systems has achieved considerable topics for the controller design. The unknown functions after system linearization have been estimated by several methods including artificial intelligence techniques such as neural networks, fuzzy logic systems and neurofuzzy networks. In a number of published articles, the issues of syste...

Some comparative studies of several nonlinear control techniques applied to dc-dc power converters are developed in this paper, like for instance the Immersion & Invariance, Passivity-Based Control, Feedback Linearization and the Sliding-Mode Control. All these different control strategies are used to drive dc-dc power converters in a dc microgrid. The load, modeled as a Constant Power Load typ...

u = a(x) + b(x)v, (3) where b(x) is a nonsingular matrix, and v ∈ Rp is a transformed or virtual input, so that the inputoutput response between v and y is linear. This requirement is called input-output linearization because only the input-output map h is made linear. On the other hand, full state linearization refers to the case when the whole state x must be “linearized”. Linearization of th...

Maneuver Regulation, Transverse Feedback Linearization and Zero Dynamics Christopher Nielsen Masters of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2004 The maneuver regulation (or path following) problem has received considerable attention in the control literature where feedback linearization has proven an effective approach to solving the ...

u = a(x) + b(x)v, (3) where b(x) is a nonsingular matrix, and v ∈ Rp is a transformed or virtual input, so that the inputoutput response between v and y is linear. This requirement is called input-output linearization because only the input-output map h is made linear. On the other hand, full state linearization refers to the case when the whole state x must be “linearized”. Linearization of th...

We consider analysis of nonlinear systems that can be brought into a state dependent representation known as extended linearization. Under this formulation, conventional linear analysis techniques may be adapted to study the stability, optimality, and robustness properties of nonlinear systems. When subject to system uncertainty, estimating the radius of stability for systems under extended lin...

Standard quadratic programs are non-convex quadratic programs with the only constraint that variables must belong to a simplex. By a famous result of Motzkin and Straus, those problems are connected to the clique number of a graph. In this paper, we study cutting plane techniques to obtain strong bounds for standard quadratic programs. Our cuts are derived in the context of a Spatial Branch & B...

We study Siegel’s center problem on the linearization of germs of diffeomorphisms in one variable. In addition of the classical problems of formal and analytic linearization, we give sufficient conditions for the linearization to belong to some algebras of ultradifferentiable germs closed under composition and derivation, including Gevrey classes. In the analytic case we give a positive answer ...

Linearization is the procedure of rewriting a process term into a linear form, which consist only of basic operators of the process language. This procedure is interesting both from a theoretical and a practical point of view. In particular, a linearization algorithm is needed for the Compositional Interchange Format (CIF), an automaton based modeling language. The problem of devising efficient...

The linearization curve generation is an important step in printer color characterization. The typical purpose of the linearization curves in conventional four ink printing is to compensate for dot overlapping and dot size variations and therefore to accommodate the non-linearity of the printing process. In CcMmYK “photo” printing, the introduction of light cyan and magenta inks presents new ch...