Every one of us knows about the rise of Coronavirus (COVID-19) from Wuhan (China) and its effects into nearby states and further motherlands, increased domestic and worldwide methods are being occupied to contain the outburst. In terms of Economic and Social point of view, it directly disturbs the metropolitan markets on a high level by engaging all the capitals and towns in a lock-down situation. It’s also highlighted if this situation increases in different countries then it can lead in a direction to world-wide health disaster and in many accommodations as well. Be that as it may, while compelling conventions concerning the sharing of good information is underscored, urban information, then again, explicitly identifying with urban well-being and safe city ideas, is still seen from a patriot point of view as exclusively profiting a country's economy and its monetary and political impact. This article will explore the new and better universal understandings and also shows how smart city/urban systems be able to improve uniform procedures for bigger data sharing in the time of tragedies.

The speed control of induction machines for multiple-speed handling is critical. When the vector control method is applied to induction machines, it has a significant impact on speed utilization. This strategy of operating the machine at a fixed predefined speed mode presents better results for electric vehicles. An effective model for a speed control loop is proposed in this paper, using a fixed-mode proportional integral (FM-PI) controller based on an upper and lower limit torque limiter. The power supply is fed using a lithium-ion battery with an inverter-fed mechanism. Moreover, the proposed model is validated using simulations with user-defined speed modes (40, 60, and 80 km/h). These speed modes, with different torque commands, have been considered for advanced modeling. In this model, torque is developed via a closed-loop control operation to attain the required speed assigned by the user. The sensors are used to collect data, and a multiple regression algorithm analyzes the dataset to predict input parameters (voltage (Vab), phase current (I), and torque (T)) required to achieve the desired speed mode. The efficiency of the proposed model is compared with induction motors bearing the same rating for the loaded and unloaded speed test. Effective machine parameter control is achieved by reaching the desired performance levels of 94.37% and 78.30% in a shorter time for the loaded and unloaded modes. A speed response comparison of the FOPID, KW-WOA-PID, SVR-PI, and FM-PI controller model simulation results indicates that the FM-PI speed controller guarantees better performance and displays an improvement in rising time and settling time, compared to other controllers. The implementation of different driving scenarios proves the model’s effectiveness for robust speed applications.

The substantial rise in the demand for electric vehicles (EVs) has emphasized an environment-friendly and intelligent design for speed control strategies. In this paper, a Mamdani fuzzy logic controller (MFLC) was proposed to vigorously control the speed of EVs at discrete levels. MFLC member functions (MFs) are tuned for EVs operating at three different speed modes (40, 60, and 80 km/h). The proposed speed controller operation for the speed tracking of EVs was designed and tested in MATLAB (Simulink) environment. The proposed speed controller validated a remarkable improvement in dynamic speed control compared with existing P-I, FLC, Fuzzy FOPID (ACO), Fuzzy FOPID (GA), and Fuzzy FOPID (PSO) controllers. Its stability under a user-defined drive pattern is also observed. In this proposed work, the speed controller highlights the better tracking of user-defined speed response compared to the conventional aforementioned controllers. Moreover, the speed tracking of the designed model was tested for robustness against speed transients at predefined time instants, respectively. The comparison suggests that the MFLC model removes overshoot and significantly reduces the steady-state time.

Abstract-Digital PID controller is one of the most powerful and efficient controller, which is widely used in industrial control systems. PID controllers can be implemented through either by microprocessors or they can be implemented through FPGA. FPGA based PID controllers are more advantageous in terms of speed and power consumption as compared to software based. Here we design two diverse realizations of FPGA based digital PID controller. One realization is multiplier based which needs multipliers for its implementation and other realization is multiplierless, which is implemented through Distributed Arithmetic Look Up Table (DALUT) method. Distributed arithmetic is an efficient technique to compute inner products using Look Up Tables (LUT). DALUT based PID controller is more efficient because it utilizes less power and hardware resources. Both realizations are simulated in Matlab/Simulink environment. Xilinx SysGen is used to translate both the realizations to bit stream which then can be synthesized, implemented and downloaded to the target FPGA using Xilinx ISE Project Navigator. The results obtained are very helpful for comparative analysis of both the realizations.

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