Adaptive fuzzy-based stability control and series impedance correction for the grid-tied inverter.

The regenerative braking in the tram allows the energy to be returned to the power grid through a power inverter. Since the inverter location between the tram and the power grid is not fixed, resulting in a wide variety of impedance networks at grid coupling points, posing a severe threat to the stable operation of the grid-tied inverter (GTI). By independently changing the loop characteristics of the GTI, the adaptive fuzzy PI controller (AFPIC) can adjust according to different impedance network parameters. It is challenging to fulfill the stability margin requirements of GTI under high network impedance since the PI controller has phase lag characteristics. A correction method of series virtual impedance is proposed, which connects the inductive link in a series configuration with the inverter output impedance, correcting the inverter equivalent output impedance from resistance-capacitance to resistance-inductance and improving the system stability margin. Feedforward control is adopted to improve the system's gain in the low-frequency band. Finally, the specific series impedance parameters are obtained by determining the maximum network impedance and setting the minimum phase margin of 45°. The realization of virtual impedance is simulated by conversion to an equivalent control block diagram, and the effectiveness and feasibility of the proposed method are verified by simulation and a 1 kW experimental prototype.

Implementation of a Distributed Framework for Permissioned Blockchain-Based Secure Automotive Supply Chain Management.

An automotive supply chain includes a range of activities from the concept of the product to its final transfer to a customer and subsequent vehicle maintenance. The three distinct stages of this chain are production, sales, and maintenance. In many countries, automobile records are not available to the public and anyone who has access to the central database or government systems can tamper with these records. In addition, used vehicle maintenance and transfer histories remain unavailable or inaccessible. These issues can be overcome by incorporating state-of-the-art blockchain technology into automotive supply chain management. Blockchain technology uses a chain of blocks for distributed transfer and storage of information, creating a decentralized data register that makes records of any digital asset tamper-proof and transparent. In this paper, we implement a permissioned blockchain-based framework for secure and efficient supply chain management of the automobile industry. We employed Hyperledger Fabric; an enterprise-grade distributed ledger platform for developing solutions. In our solution, the blockchain is customized and private in order to ensure system security. We evaluated our system in terms of memory cost, monetary cost, and speed of execution. Our results demonstrate that only 346 MB of extra memory space is required for storing the automotive data of 1 million users, thus rendering the memory cost negligible. The monetary cost is insignificant as all open source blockchain resources are employed, and the speed of record update is also fast. Our results also show that the decentralization of the automotive supply chain using blockchain can implement system security with minor modifications in the established configuration of the web application database.

Three-Dimensional Multi-Target Tracking Using Dual-Orthogonal Baseline Interferometric Radar.

Multi-target tracking (MTT) generally needs either a Doppler radar network with spatially separated receivers or a single radar equipped with costly phased array antennas. However, Doppler radar networks have high computational complexity, attributed to the multiple receivers in the network. Moreover, array signal processing techniques for phased array radar also increase the computational burden on the processing unit. To resolve this issue, this paper investigates the problem of the detection and tracking of multiple targets in a three-dimensional (3D) Cartesian space based on range and 3D velocity measurements extracted from dual-orthogonal baseline interferometric radar. The contribution of this paper is twofold. First, a nonlinear 3D velocity measurement function, defining the relationship between the state of the target and 3D velocity measurements, is derived. Based on this measurement function, the design of the proposed algorithm includes the global nearest neighbor (GNN) technique for data association, an interacting multiple model estimator with a square-root cubature Kalman filter (IMM-SCKF) for state estimation, and a rule-based M/N logic for track management. Second, Monte Carlo simulation results for different multi-target scenarios are presented to demonstrate the performance of the algorithm in terms of track accuracy, computational complexity, and IMM mean model probabilities.

Low-Stress and Optimum Design of Boost Converter for Renewable Energy Systems.

This paper examines the design and analysis of DC-DC converters for high-power and low-voltage applications such as renewable energy sources (RESs) and comparisons between converters based on switch stresses and efficiency. The RESs including photovoltaic arrays and fuel cell stacks must have enhanced output voltages, such as 380 V DC in the case of a full bridge inverter or 760 V DC in the case of a half bridge inverter, in order to interface with the 220 V AC grid-connected power system. One of the primary difficulties in developing renewable energy systems is enhancing DC-DC converters' efficiency to enable high step-up voltage conversion with high efficiency and low voltage stress. In the present work, the efficiency, current, and voltage stress of switches of an isolated Flyback boost converter, simple DC-DC Boost converter, and an Interleaved boost converter, are explored and studied relatively. The most suitable and optimized options with a high efficiency and low switching stress are investigated. The more suitable topology is designed and analyzed for the switch technology based on the Silicon-Metal Oxide Semiconductor Field Effect Transistor (Si-MOSFET) and the Gallium Nitride-High Electron Mobility Transistor (GaN-HEMT). The Analytical approach is analyzed in this paper based on efficiency and switching stress. It is explored that GaN HEMT based Flyback boost converter is the best. Finally, the future direction for further improving the efficiency of the proposed boost converter is investigated.

Cascaded robust control of mechanical ventilator using fractional order sliding mode control.

A mechanical ventilator is an important medical equipment that assists patients who have breathing difficulties. In recent times a huge percentage of COVID-19 infected patients suffered from respiratory system failure. In order to ensure the abundant availability of mechanical ventilators during COVID-19 pandemic, most of the manufacturers around the globe utilized open source designs. Patients safety is of utmost importance while using mechanical ventilators for assisting them in breathing. Closed loop feedback control system plays vital role in ensuring the stability and reliability of dynamical systems such as mechanical ventilators. Ideal characteristics of mechanical ventilators include safety of patients, reliability, quick and smooth air pressure buildup and release.Unfortunately most of the open source designs and mechanical ventilator units with classical control loops cannot achieve the above mentioned ideal characteristics under system uncertainties. This article proposes a cascaded approach to formulate robust control system for regulating the states of ventilator unit using blower model reduction techniques. Model reduction allows to cascade the blower dynamics in the main controller design for airway pressure. The proposed controller is derived based on both integer and non integer calculus and the stability of the closed loop is ensured using Lyapunov theorems. The effectiveness of the proposed control method is demonstrated using extensive numerical simulations.

Duplex PD inertial damping control paradigm for active power decoupling of grid-tied virtual synchronous generator.

The growth of distributed generation significantly reduces the synchronous generators' overall rotational inertia, causing large frequency deviation and leading to an unstable grid. Adding virtual rotational inertia using virtual synchronous generators (VSG) is a promising technique to stabilize grid frequency. Due to coupled nature of frequency and active output power in a grid-tied virtual synchronous generator (GTVSG), the simultaneous design of transient response and steady state error becomes challenging. This paper presents a duplex PD inertial damping control (DPDIDC) technique to provide active power control decoupling in GTVSG. The power verses frequency characteristics of GTVSG is analyzed emphasizing the inconsistencies between the steady-state error and transient characteristics of active output power. The two PD controllers are placed in series with the generator's inertia forward channel and feedback channel. Finally, the performance superiority of the developed control scheme is validated using a simulation based study.