Hyoung-Joon Park

Shipboard integrated power systems, the key enablers of ship electrification, call for effective power management control (PMC) to achieve optimal and reliable operation in dynamic environments under hardware limitations and operational constraints. The design of PMC can be treated naturally in a model predictive control (MPC) framework, where a cost function is minimized over a prediction horizon subject to constraints. The real-time implementation of MPC-based PMC, however, is challenging due

A Model Predictive Control (MPC) approach is developed for spacecraft rendezvous and docking to a rotating/ tumbling platform and for debris avoidance maneuvers. With this approach, the constraints on thrust, approach velocity and spacecraft positioning within the Line-of-Sight cone from the docking port are systematically treated. The trajectories are simulated and time-to-dock and fuel consumption are evaluated as cost function parameters are varied. Debris avoidance maneuvers are considered,

Presented at AIAA/AAS Astrodynamics Specialist Conference, Long Beach, CA. The article of record as published may be found at https://doi.org/10.2514/6.2016-5269

To be published in the proceedings of the 27th AAS/AIAA Spaceflight Mechanics Meeting, San Antonio, TX, Feb. 6-9, 2017

This paper reviews the integrated perturbation analysis - sequential quadratic programming (IPA-SQP) approach. The IPA-SQP approach has been proposed to address computational challenges in nonlinear model predictive control (MPC) problems. This approach combines the complementary features of perturbation analysis and sequential quadratic programming in a unified framework. An overview of the IPA-SQP approach is provided, its methodological extension to adaptive MPC is discussed, and computationa

One of the major issues when applying truck destination choice models with a large number of alternatives is how to sample a set of non-chosen traffic analysis zones (TAZs) to construct a destination choice set. Despite the large number of studies applying various sampling strategies, the question remains as to what are optimal strategies in model development. This study examined how the sampling strategies affect the performances of truck destination choice models. Two sampling methods (simple

Background: Non-communicable diseases (NCDs) are an important issue worldwide. Obesity has a close relationship with NCDs. Various age-related changes should be considered when evaluating obesity. Methods: National representative cohort data from the National Health Insurance Service National Sample Cohort from 2012 to 2013 were used. Sex-specific and age group-specific (10-year intervals) means for body mass index (BMI), waist circumference (WC), and waist-to- height ratio (WtHR) were calculate

In this paper, a Model Predictive Controller (MPC) based on the Integrated Perturbation Analysis and Sequential Quadratic Programming (IPA-SQP) is designed and analyzed for spacecraft relative motion maneuvering. To evaluate the effectiveness of the IPA-SQP MPC, the results are compared with the linear quadratic MPC algorithm developed in [4, 13–15]. It is shown that the IPA-SQP algorithm can handle directly nonlinear constraints on thrust magnitude without resorting to saturation or polyhedral

This paper presents a novel six degree-of-freedom guidance and control algorithm for free-flyer robots equipped with a robotic manipulator operating on the International Space Station. The proposed algorithm combines a sliding mode controller for rotational motion and a model predictive controller for translational motion. A novel prediction-twisting sliding mode controller (PT-SMC) is introduced to stabilize configuration changes induced by the manipulator and correlated disturbances and to ach

Model Predictive Control (MPC) is an effective control method that has been used for a diverse set of applications. Specifically, MPC for linear systems with quadratic cost functions is considered a mature technology. For nonlinear systems whose underlying dynamics are fast, however, the computational complexity of the numerical optimization has emerged as one of the main challenges in MPC applications. An integrated perturbation analysis and sequential quadratic programming (IPA-SQP) algorithm