In industrial production systems, manufacturers often face difficulties in sorting different types of objects. Color and height-based sorting which is done manually by human is quite a tedious task and its needs countless time as well. For manual sorting, many workers are required, which can be quite expensive. Moreover, robots that can sort only color or height can’t be effective when there is a need of products with same color with different heights and vice versa. In this paper, a computer vision based robotic sorter is proposed, which is capable of detecting and sorting objects by their colors and heights at the same time. This work isn’t done before as height sorting of same shapes is a new technique, which is done with color sorting techniques by computer vision. It is equipped with a robotic arm having 6 degree of freedom (DOF), by which it picks up and then place objects according to its color and height, to a predetermined place as per the production system requirement. A camera with the computer vision software detects various colors and heights. Haar Cascade algorithm has been used to sort the products. This multi-DOF robotic sorter can be a remarkably useful tool for automating the production process completely, where multiple conveyor belts are used, which can reduce time complexity as well. In the proposed system, the efficiency of color and height sorting is around 99%, which proves the efficiency of our system. The overall improvement in the efficiency of the production process can be significantly enhanced by using this system.
The integration of distributed generations (DG’s) to the grid has led to number of challenges apart from the advantages, one of the challenge associated is the voltage regulation. Photovoltaic (PV) system as a DG is considered as it has a better edge when compared to the other DG’s. The application of PV system to the grid requires extra compensating devices to mitigate the voltage regulation issues. A novel voltage regulation strategy for three phase grid connected PV system using fractional order proportional plus integral (FOPI) controller is proposed in this paper. The modelling&analysis of FOPI controller along with the integer orderproportional plus integral (IOPI) controlleris presented in this paper. FOPI controllers are designed in Matlab using FOMCON toolbox (Fractional order Modeling and Control).The simulation is consequently carried out in the Matlab/Simulink environment for both the controllers with resistive loads, resistive & inductive loadsand resistive, inductive & capacitive loads.The FOPI controller outperforms IOPI controller, results of simulation reflectthat controller using FOPI gives better performancewhen compared with the IOPI controller. The effectiveness ofthe FOPI controller confirms the authentication and the simulation results are deliberated for all the different loads.
Abstract.A method is proposed for model order reduction for a linear multivariable system by using the combined advantages of dominant pole reduction method and Particle Swarm Optimization (PSO). The PSO reduction algorithm is based on minimization of Integral Square Error (ISE) pertaining to a unit step input. Unlike the conventional method, ISE is circumvented by equality constraints after expressing it in frequency domain using Parseval's theorem. In addition to this, many existing methods for MIMO model order reduction are also considered. The proposed method is applied to the transfer function matrix of a 10 th order two-input two-output linear time invariant model of a power system. The performance of the algorithm is tested by comparing it with the other soft computing technique called Genetic Algorithm and also with the other existing techniques.Keywords: Reduced order model, Integral Square Error, Parseval's theorem, Particle Swarm Optimization, Genetic Algorithm. IntroductionIn real problems the analysis of high order systems (HOS) is costly and tedious. Hence simplification procedure for original HOS are generally employed to realize for simple models based on physical considerations or by using mathematical approaches. Numerous methods are available in the literature for order reduction for linear continuous systems in time domain as well in frequency domain such as step response, frequency response etc. The reduced order model must be a good approximation of original model and it should retain the physical characteristics of the system such as step response, stability etc. Further, numerous methods of order reduction are also available in the literature, which are based on the minimization of the integral square error (ISE) criterion. However, a common feature in these methods is that the values of the denominator coefficients of the low order system (LOS) are chosen arbitrarily by some stability preserving methods such as dominant pole, Routh Approximation Methods, Routh Stability Criterion etc. and then the numerator coefficients of the LOS are determined by minimization of the ISE.
In this paper, the focus is on the dispatching strategy of microgrids with minimization in costs and emissions. The novelty of this paper is in proposing a new approach toward combined heat and power generation in a grid with renewable energy resources, such as wind turbines, photovoltaic cells which reduces the overall costs considerably. In this research, for simulating the optimal dispatch of DG units and other power generation resources, GAMS software is applied to the problem, which results in a lower calculation time.
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