Magnetic Levitation systems are nonlinear, frictionless and noiseless which use electromagnetic fields to hover ferromagnetic objects in air. For this purpose, we have proposed Supertwisting and Integral Backstepping sliding mode controllers. The designed controllers ensure the air gap to be maintained at the desired value while tracking the magnetic flux and momentum to their respective references. The stability analysis of the proposed controllers has been presented using Lyapunov theory which proves the global asymptotic stability of the system. The performance of the proposed controllers is analyzed using ODE 45 solver in MATLAB/Simulink environment. The proposed controllers reduce the chattering and improves the dynamic response of the system. Robustness of the proposed controllers has been checked by adding noise and disturbance in system’s state space model. Furthermore, comparison of proposed controllers with each other, with conventional PI and recently published nonlinear controllers for MagLev system in terms of dynamic response has also been presented. The results show that the dynamic behavior of supertwisting sliding mode controller is best among analyzed controllers.

Energy consumption in the residential sector is 25% of all the sectors. The advent of smart appliances and intelligent sensors have increased the realization of home energy management systems. Acquiring balance between energy consumption and user comfort is in the spotlight when the performance of the smart home is evaluated. Appliances of heating, ventilation and air conditioning constitute up to 64% of energy consumption in residential buildings. A number of research works have shown that fuzzy logic system integrated with other techniques is used with the main objective of energy consumption minimization. However, user comfort is often sacrificed in these techniques. In this paper, we have proposed a Fuzzy Inference System (FIS) that uses humidity as an additional input parameter in order to maintain the thermostat set-points according to user comfort. Additionally, we have used indoor room temperature variation as a feedback to proposed FIS in order to get the better energy consumption. As the number of rules increase, the task of defining them in FIS becomes time consuming and eventually increases the chance of manual errors. We have also proposed the automatic rule base generation using the combinatorial method. The proposed techniques are evaluated using Mamdani FIS and Sugeno FIS. The proposed method provides a flexible and energy efficient decision-making system that maintains the user thermal comfort with the help of intelligent sensors. The proposed FIS system requires less memory and low processing power along with the use of sensors, making it possible to be used in the IoT operating system e.g., RIOT. Simulation results validate that the proposed technique reduces energy consumption by 28%.

Conventional Energy Resources (CER) are being rapidly replaced by Renewable Energy Resources (RER) due to their abundant, environmentally friendly, clean, and inexhaustible nature. In recent years, Solar Photovoltaic (SPV) energy installation is booming at a rapid rate among various RER. Grid-Connected PVS required advance DC-link controllers to overcome second harmonic ripple and current controllers to feed-in high-quality current to the grid. This paper successfully presents the design of a Fuzzy-Logic Based PI (F-PI) and Fuzzy-Logic based Sliding Mode Controller (F-SMC) for the DC-link voltage controller and Proportional Resonant (PR) with Resonant Harmonic Compensator (RHC) as a current controller for a Single-Phase Two-Stages Grid-connected Transformerless (STGT) Photovoltaic (PV) Inverter. The current controller is designed with and without a feedforward PV power loop to improve dynamics and control. A Second Order General Integral (SOGI)-based Phase Lock Loop (PLL) is also designed that has a fast-dynamic response, fast-tracking accuracy, and harmonic immunity. A 3 kW STGT-PV system is used for simulation in Matlab/Simulink. A comparative assessment of designed controllers is carried out with a conventionally well-tuned PI controller. The designed controllers improve the steady-state and dynamic performance of the grid-connected PV system. In addition, the results, performance measure analysis, and harmonics contents authenticate the robustness, fastness, and effectiveness of the designed controllers, related to former works.