This paper presents the modelling of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as the quadrotor aircraft. The paper presents a new model design method for the flight control of an autonomous quad rotor. The paper describes the controller architecture for the quadrotor as well. The dynamic model of the quad-rotor, which is an under actuated aircraft with fixed four pitch angle rotors, will be described. The Modeling of a quadrotor vehicle is not an easy task because of its complex structure. The aim is to develop a model of the vehicle as realistic as possible. The model is used to design a stable and accurate controller. This paper explains the developments of a PID (proportional-integral-derivative) control method to obtain stability in flying the Quad-rotor flying object. The model has four input forces which are basically the thrust provided by each propeller connected to each rotor with fixed angle. Forward (backward) motion is maintained by increasing (decreasing) speed of front (rear) rotor speed while decreasing (increasing) rear (front) rotor speed simultaneously which means changing the pitch angle. Left and right motion is accomplished by changing roll angle by the same way. The front and rear motors rotate counter-clockwise while other motors rotate clockwise so that the yaw command is derived by increasing (decreasing) counter-clockwise motors speed while decreasing (increasing) clockwise motor speeds.

This paper proposes the use of a novel algorithm for smart-direct load control (S-DLC) and load shedding to minimize power outages in sudden grid load changes and reduce the peak-to-average ratio. The algorithm utilizes forecasting, shedding, and S-DLC. It also uses the Internet of Things and stream analytics to provide real-time load control, and generates a daily schedule for customers' equipped with intelligent electronic devices based on their demands, thermal comfort, and the forecasted load model. The demand response techniques are utilized for real-time load control and optimization. To test the algorithm, a simulation system was developed, which takes into account 100 customers owning randomly selected appliances. The results indicated that load shedding using autoregressive integrated moving average time-series prediction model, and applying S-DLC and Internet of Things can significantly reduce customers' power outage.

This paper presents a new multilevel selective harmonic elimination pulse-width modulation (MSHE-PWM) technique for transformerless static synchronous compensator (STATCOM) system employing cascaded H-bridge inverter (CHI) configuration. The proposed MSHE-PWM method optimizes both the dc-voltage levels and the switching angles, enabling more harmonics to be eliminated without affecting the structure of the inverter circuit. The method provides constant switching angles and linear pattern of dc-voltage levels over the modulation index range. This in turns eliminates the tedious steps required for manipulating the offline calculated switching angles and therefore, easing the implementation of the MSHE-PWM for dynamic systems. Although the method relies on the availability of the variable dc-voltage levels which can be obtained by various topologies, however, the rapid growth and development in the field of power semiconductor devices led to produce high-efficiency dc-dc converters with a relatively high-voltage capacity and for simplicity, a buck dc-dc converter is considered in this paper. Current and voltage closed loop controllers are implemented for both the STATCOM and the buck converter to meet the reactive power demand at different loading conditions. The technique is further compared with an equivalent conventional carrier-based pulse-width modulation to illustrate its enhanced characteristics. The effectiveness and the theoretical analysis of the proposed approach are verified through both simulation and experimental studies.

This paper details a new coordinated design between power system stabilizers (PSSs) and a unified power flow controller (UPFC) using genetic algorithms (GAs). A GA scheme determines the optimal location for a UPFC while tuning its control parameters, resulting in the optimization of the quantity, parameters, and locations of PSSs under different operating conditions. The problem is formulated as a multiobjective optimization problem in order to maximize the damping ratio(s) of electromechanical modes, matching different numbers of PSSs with a UPFC. The approach is successfully tested on the New England-New York interconnected system (a 16-machine and 68-bus system), proving its effectiveness in damping local and interarea modes of oscillations.

This paper proposes a new framework for digital image processing; it relies on inexact computing to address some of the challenges associated with the discrete cosine transform (DCT) compression. The proposed framework has three levels of processing; the first level uses approximate DCT for image compressing to eliminate all computational intensive floating-point multiplications and executing the DCT processing by integer additions and in some cases logical right/left shifts. The second level further reduces the amount of data (from the first level) that need to be processed by filtering those frequencies that cannot be detected by human senses. Finally, to reduce power consumption and delay, the third level introduces circuit level inexact adders to compute the DCT. For assessment, a set of standardized images are compressed using the proposed three-level framework. Different figures of merits (such as energy consumption, delay, power-signal-to-noise-ratio, average-difference, and absolute-maximum-difference) are compared to existing compression methods; an error analysis is also pursued confirming the simulation results. Results show very good improvements in reduction for energy and delay, while maintaining acceptable accuracy levels for image processing applications.