Solar energy can be captured by Photovoltaics (PV) and converted into electrical power. This power then connected to grids electronic converters, which also operate the PV panels at around their maximum point (MPP), maximizing harvested energy. When are in an array, partial shading effect generates a distortion of curve result loss since tracking algorithms might not able detect MPP. To solve t...

This paper is a survey of some results obtained in evolutionary genetics by algebraical methods. The main topics: 1 . Some special classes bf algebras which arising in population genetics (stochastic. haric, RmtxsTEINian, genetic etc.). 2. The BERNSTEIS’S problem and the stationary genetic structure. 3. The convergence to an equilibrium. the rate of convergence. 4. The exact linearization of ev...

In this paper, we study the tracking control problem for a nonlinear system in which the zero dynamics may be unstable. The objective here is to approximate the nonlinear system by another singularly perturbed system by using a small singular perturbation parameter  . The proposed approach is based on the methodology of exact input output linearization control, the integrator backstepping appr...

This paper considers the position tracking problem of a voltage-controlled magnetic levitation system. It is well known that the control problem is quite complicated and challenging due to inherent nonlinearities associated with the electromechanical dynamics. And feedback linearization approach via coordinate transformation is considered to be a useful candidate to tackle the control problem. ...

Abstract: Feedback linearization is a common approach used in controlling nonlinear systems. The approach involves coming up with a transformation of the nonlinear system into an equivalent linear system through a change of variables and a suitable control input. In this paper a new control structure based on the application of the method of exact linearization by Direct Feedback Linearization ...

In the present work, we propose a novel polynomial approach to approximate the Input-State feedback linearization control. The aim of this new method is to simplify the implementation complexity of the exact InputState feedback linearization. Indeed, the present approach leads to an analytical control law via analytical nonlinear transformations without need to resolve a set of partial differen...

Effective and causal observable functions for low-order lifting linearization of nonlinear controlled systems are learned from data by using neural networks. While Koopman operator theory allows us to represent a system as linear in an infinite-dimensional space observables, exact is guaranteed only autonomous with no input, finding effective approximation remains open question. Dual-Faceted Li...