Model reference adaptive control of a nonsmooth dynamical system

In this paper a modified model reference adaptive control (MRAC) technique is presented which can be used to control systems with nonsmooth characteristics. Using unmodified MRAC on (noisy) nonsmooth systems leads to destabilization of the controller. A localized analysis is presented which shows that the mechanism behind this behavior is the presence of a time invariant zero eigenvalue in the system. The modified algorithm is designed to eliminate this zero eigenvalue, making all the system eigenvalues stable. Both the modified and unmodified strategies are applied to an experimental system with a nonsmooth deadzone characteristic. As expected the unmodified algorithm cannot control the system, whereas the modified algorithm gives stable robust control, which has significantly improved performance over linear fixed gain control

Role of Microbes in Plant Growth and Food Preservation

Introduction: Microbes perform better functions for agricultural production by promoting various direct and indirect mechanisms in soil and plants. If agricultural development is to satisfy the needs of an increasing global population, a deeper understanding of soil microbiology is needed. Furthermore, microbial biota such as yeast, bacteria etc., plays a significant role in food preservation by various mechanisms. Review results: Despite their pathogenicity, microbes play a substantial role in dispensing an assortment of fermented drinks and foods in the food industry and home. Probiotics, fermented foods and alcoholic beverages are flattering extra popular due to their health benefits and flavour. Furthermore, they increase the yield and growth of plants by improving mineral availability to the plants and by another mechanism. Review implementation: This present review also discusses the various organisms used in the agricultural processing of beverages and food and the benefits of using the following microbes in the beverage and food industry

Adaptive Neuro-Genetic Control of Chaos applied to the Attitude Control Problem

Conventional adaptive control techniques have, for the most part, been based on methods for linear or weakly non-linear systems. More recently, neural network and genetic algorithm controllers have started to be applied to complex, non-linear dynamic systems. The control of chaotic dynamic systems poses a series of especially challenging problems. In this paper, an adaptive control architecture using neural networks and genetic algorithms is applied to a complex, highly nonlinear, chaotic dynamic system: the adaptive attitude control problem (for a satellite), in the presence of large, external forces (which left to themselves led the system into a chaotic motion). In contrast to the OGY method, which uses small control adjustments to stabilize a chaotic system in an otherwise unstable but natural periodic orbit of the system, the neuro-genetic controller may use large control adjustments and proves capable of effectively attaining any specified system state, with no a prioriknowledge of the dynamics, even in the presence of significant noise

Recent Advances in Experimental Techniques for Flow and Mass Transfer Analyses in Thermal Separation Systems

Modelling flow and mass transfer of thermal separation equipment constitutes one of the most challenging tasks in fluids process engineering. The difficulty of this task comes from the multiscale multiphase flow phenomena in rather complex geometries. Both analysis of flow and mass transfer on different scales as well as validation of models and simulation results require advanced experimental and measurement techniques. As a follow-up to intensive discussions during the 2019 Tutzing Symposium “Separation Units 4.0” a wide set of available modern experimental technologies is presented. © 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinhei