The State-Dependent Riccati Equation (SDRE) control strategy is one of the most efficient approaches for the nonlinear feedback control algorithm by allowing nonlinearities in the system states. This method can be considered as a nonlinear LQR based control design, where the system matrices (and the weight matrices) are functions of the states. SDRE–based techniques have important properties which make them applicable for different nonlinear systems. In this paper we study some properties of these algorithms in order to improve the control efficiency and robustness of nonlinear process control. Also we compare the results of applied suboptimal and optimal SDRE control in continuous and discrete time case.

The presence of a second reactive gas in the magnetron sputtering chamber makes the process much more complicated, and the process control much more difficult than in the case of a single reactive gas. Macroscopic models have been developed in order to explain the complex phenomena and to provide support for the process control. These models are able to explain the nonlinearities of the process and the strong coupling between the control channels. This paper introduces a model created with the intention to of gaining a good grasp of the process, especially regarding the conditions necessary to obtain the required stoichiometry of the film deposited on the substrate. For this purpose, we modelled the formation of the desired ternary compound both directly from the available particle fluxes and from intermediary compounds. The surface of the substrate is divided into eight dynamically variable regions, covered by different compounds, each exposed to the streams of five types of particles. We present the analytical model and provide simulation results in order to demonstrate its capability toof describeing the nonlinear phenomena, which that characterisze the two-gas sputtering process.

The paper focuses on providing an insight into the current state of computational modeling regarding reactive magnetron sputtering systems. A detailed compilation of developed models is gathered and grouped into categories based on the phenomena being modeled. The survey covers models developed for the analysis of magnetron discharges, particle-surface interactions at the target and the substrate, as well as macroscopic models. Corresponding software packages available online are also presented. After gaining the necessary insight into the current state of research, a list of the most challenging tasks is given, comparing diffierent approaches, that have been used to combat the encountered difficulties. The challenges associated with modeling tasks range from analytical complexity, mathematical know-how used for model approximation and reduction, as well as optimization between computational load and result accuracy. As a conclusion, the future challenges are compiled into a list and a probable direction in modeling is given, that is likely to be further pursued.

Nanocrystalline multilayer thin film coatings, composed of nanometer-scale thick CrN, TiAlN and MoS2 tri-layer systems, were prepared by reactive co-sputtering processes. The self-lubricated multilayer coating structures were deposited by one-fold oscillating movement of substrates in front of the sputter sources. Three independently operated direct current (dc) excited unbalanced magnetrons (UM) with rectangular cathodes of TiAl alloy (50/50%), pure chromium and MoS2 were used as sputter sources. The reactive sputtering process was performed in a mixture of Ar-N2 atmosphere. Hardened high-speed-steel (HSS) and thin oxide covered Si (100) wafers were used as substrates for tribological- and microstructure investigations, respectively. According to results of the chemical composition evaluated by Auger-electron spectroscopy (AES) and microstructure investigation by cross sectional transmission electron microscopy (XTEM), the CrN, TiAlN and the MoS2 phases form practically continuous layers with large gradient transition of composition. The as-deposited CrN/ (Al,Ti)N/MoS2 coatings have shown good friction behaviour, tested at room temperature in dry sliding condition with a ball-on-disk tribometer.

The paper presents in detail a unique multilevel control architecture designed for the comprehensive management of the DC magnetron sputtering process and of all subsystems of the sputtering equipment. The ultimate goal is to increase the repeatability, stability and the controllability of the complex process. The presented topics include embedded and distributed electronics, data acquisition and supervisory control, networking, data management, redundant local and remote data-archiving. There are presented platform independent algorithms managing the data exchange between computational devices, and conclusions are drawn regarding the efficiency of the various algorithms used.

In electric vehicles battery life can be prolonged by using hybrid energy storage systems (HESS ), which combine high energy density batteries with supercapacitors, characterized by high power density. This paper deals with the control of electronic power converters from an active parallel HESS. The load of the HESS is the electrical motor drive of an electric vehicle. The interfaces between the DC-link and the power sources are four-phase bidirectional DC-DC converters driven in current control mode, based on the current references supplied by an active parallel HESS power distribution algorithm. We present a rule-based fuzzy energy management algorithm for a HESS powered electric vehicle and its simulation in MATLAB/Simulink^® environment using the Quasi-Static Simulation (QSS ) and Fuzzy Logic toolboxes. Also, simulation results in driving and regenerative braking operation modes of the electric vehicle are presented.