Missouri University of Science and Technology

About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Control theory & Artificial neural network. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.

Optimal Sizing of a Vanadium Redox Battery System for Microgrid Systems

Abstract: The vanadium redox battery (VRB) has proven to be a reliable and highly efficient energy storage system (ESS) for microgrid applications. However, one challenge in designing a microgrid system is specifying the size of the ESS. This selection is made more complex due to the independent power and energy ratings inherent in VRB systems. Sizing a VRB for both required power output and energy storage capacity requires an in-depth analysis to produce both optimal scheduling capabilities and minimum capital costs. This paper presents an analytical method to determine the optimal ratings of VRB energy storage based on an optimal scheduling analysis and cost-benefit analysis for microgrid applications. A dynamic programming (DP) algorithm is used to solve the optimal scheduling problem considering the efficiency and operating characteristics of the VRBs. The proposed method has been applied to determine the optimal VRB power and energy ratings for both isolated and grid-connected microgrids, which contain PV arrays and fossil-fuel-based generation. We first consider the case in which a grid-tie is not available and diesel generation is the backup source of power. The method is then extended to consider the case in which a utility grid tie is available.

Reinforcement Learning Controller Design for Affine Nonlinear Discrete-Time Systems using Online Approximators

Abstract: In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

Optimum Angles for a Polarimeter: Part II

Abstract: The four optimum rotation angles for a polarimeter consisting of a quarter-wave plate in conjunction with a linear polarizer are found. This is done by using the determinant and condition numbers of the system measurement matrix as objective functions in a minimization procedure. The four angles so found result in the polarimeter's estimate of the incident Stokes vector to have a minimum sensitivity with respect to fluctuations in the detected flux and errors in the angular position of the optical components constituting the polarimeter. Four optimal angles are presented. These four angles also retain a simplicity of form for the measurement matrix.

Modeling of Laser Cladding with Powder Injection

Abstract: Laser cladding is one of the material additive manufacturing processes used to produce a metallurgically bonded deposition layer. To obtain a high-quality resulting part, a deep understanding of the underlying mechanisms is required. In this article, a mathematical model is developed to simulate the coaxial laser-cladding process with powder injection, which includes laser- substrate, laser-powder, and powder-substrate interactions. The model considers most of the associated phenomena, such as melting, solidification, evaporation, evolution of the free surface, and powder injection. The fluid flow in the melt pool, which is mainly driven by Marangoni shear stress as well as particle impinging, together with the energy balances at the liquid-vapor and the solid-liquid interfaces, are investigated. Powder heating and laser power attenuation due to the powder cloud are incorporated into the model in the calculation of the temperature distribution. The influences of the powder injection on the melt pool shape, penetration, and flow pattern are predicted through the comparison for the cases with powder injection and without powder injection. Dynamic behavior of the melt pool and the formation of the clad are simulated. The effects of the process parameters on the melt pool dimension and peak temperature are further investigated based on the validated model.