Online ISSN: 2515-8260

Keywords : Fuzzy system


Smart Energy Management in Green Buildings

Akhil Nigam; Kamal Kant Sharma

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 7, Pages 4627-4637

With the increasing size of supply and demand growth in the next decades there will be
need of smarter distribution system. The installation of large number of electric power
generation units may have adverse impact on environment. So smart energy management
system is one of the best and novel approaches which enables smart grid operations.
During the installation and incorporation of smart grids there are some factors like
consumption of electric energy, energy storage, and generation resources should be
optimized in such a manner that saves energy, improves efficiency, maintains security and
enhances reliability during increasing demand at minimum operating cost. Some of the
renewable energy sources may be taken as the pillars for making smart energy buildings
which reduces the cost of building systems. From the point of distributed generation it may
be considered as future power generation by the installation of renewable energy systems
and storage systems. It will lead into smart energy buildings which will be in the form of
Off-grid/Hybrid/Grid tied based solar system. Due to the development of smart techniques
like fuzzy systems and artificial neural network system it is helpful to reduce billing cost of
energy building systems. Green house gas emission is also a serious concern during the
installation of energy buildings so hydro or wind energy systems are fully weather
dependent and they can reach up to only 14% generation of electricity due to intermittent
sources in nature. To overcome the problem of more energy demand and gas emission a
new method proposed such as smart system services for the improvement of building
performance. This paper deals with advanced techniques for smart home energy
management system in order to control its operations in reliable, secure and economical
manner.

Enhancement for the Position of Inverted Pendulum Using Linear Quadratic Regulator Based Fuzzy System

Komali Dammalapati; Smritilekha Das; B. Prabha; VVS Sasank

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 757-765

In this work, the problem of controlling the inverted pendulum has been investigated in detail. A different application that resembles inverted pendulum system has been studied. It considers the model, state space form representation with ricotta equation for optimal control applied to the nonlinear system with state and output variables. Later, to control the system several control system techniques has been applied in the literature survey. The challenging part is the fuzzy based method, to control position and for stabilization of the inverted pendulum with the application of appropriate rules of the overshoot and settling time is obtained within the desired value. The fuzzy based LQR is designed for a nonlinear system using MATLAB/SIMULINK. Also, a detailed study about the mathematical model of an inverted pendulum system is deliberated. The position of inverted pendulum is tuned using the same LQR controller. The simulation results show the performance of fuzzy LQR. By varying the pendulum parameters to different values, the robustness of the controller that has been used is checked.