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Predictive Control and Estimation for Systems with Information Structured Constraints
Toru Namerikawa,Takeshi Hatanaka,Masayuki Fujita 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper deals with a predictive control and estimation problem with information structured constraints in a constrained finite-time optimal control framework. A large-scale system with information structures is defined as a system in which each subsystem collects spatio-temporally different information, and in general it is necessary to collect and process information in a distributed fashion. We propose a novel predictive control scheme and an estimation law with local information that each distributed subsystem obtains. The effectiveness of the proposed control and estimation law is evaluated through numerical simulations of a simplified micro grid.
Traffic Signal Control Considering Switching Timing via Distributed Model Predictive Control
S. Sasaki,T. Namerikawa 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
In this paper, we aim to alleviate traffic congestion on each link online by traffic signal control for local road transport network to be controlled. We first propose a transportation model with time delay system considering the travel time of the vehicle and calculate the optimal signal phases with variable cycle length and offset using distributed model predictive control for that model to reduce congestion rate on local roads. We then explain algorithms for distributed control that each intersection solves the optimization problem in parallel sharing information only with adjacent intersection. Finally, the effectiveness of the proposed method is confirmed by numerical simulation.
Nam Duc Do,Toru Namerikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper focuses on a new proposal system input of impedance control that relates tofor cereflection(FR) scheme of teleoperation with time varying incommunication lines. To improve the tracking performance and transparency, the control algorithm uses one more communication channel to transfer the FR information from the master side to the slave side. Using variabled amping values, the contact stability is achieved at the time while the slave robot contacts with the environment. In this work, the input-to-output stability(IOS) small gain approach is used to show the overall force-reflecting teleoperation to be input-to-states table(ISS). Several experimental results show the effectiveness of our proposed algorithm.
Hierarchical Control of Power Networks by using Overlapping Information
Tomoharu Suehiro,Toru Namerikawa 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10
This study deals with decentralized and hierarchical control for electric power networks by using overlapping information. The control objective is to minimize the cost function of the load frequency control problem. The control law consists of three steps. We apply the decentralized hierarchical control methodology to large-scale electrical power networks consisting of distributed power storage and generation sources such as batteries and wind power generators. Through several numerical simulation results of decentralized power networks, we verified their stability, compared the proposed and the previous decentralized methods, and showed the effectiveness of the proposed method.
Parking Lot Allocation Based on Matching Theory using Prediction-based Optimal Vehicle Routing
T. Nakazato,T. Namerikawa 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
The purpose of this paper is to relax traffic congestion caused by the decrease in vehicle speed in case of a driver searching for a parking lot in traffic network, by using Smart Parking System. Smart Parking System is a system that allocates parking lot considering both the driver’s preference and the parking lot manager’s preference in advance. At that time, driver should know the optimal route and its time from currrent location to each parking lot. In this paper, Smart Parking System consider the road condition in traffic network and present the driver time by the optimal route from the driver’s current location to each parking lot. Then, the parking lot allocation is determined by using matching theory considering both the driver’s preference including information of optimal route and its time and the parking lot manager’s preference. Finally, the effectiveness is confirmed by numerical simulations and results of parking lot allocation using optimal vehicle routing.
H<SUB>∞</SUB> filtering Convergence and It’s Application to SLAM
Hamzah Ahmad,Toru Namerikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
KF-SLAM(Kalman filter-SLAM) have been used as a popular solution by researchers in many SLAM ap-plication. Nevertheless, it short comings of a ssumption for Gaussian noise limited its efficiency and demand researcher to consider better filter and algorithm to achieve a promising result of estimation. In this paper, we proposed one of its family, the H∞ filter-based SLAM to determine its competency for SLAM problem. Unlike Kalm an filter, H∞ filterable to work in an unknown statistical noise behavior and thus more robust. It rely on a guess that the noise is in bounded energy and does not require a priori knowledge about the system. Therefore, we proposed the H∞ filter aso ther available technique to in fer the location for both robot and landmarks while simult aneously building the map. From the results of simulation, H∞ filter produces better outcome than the Kalman filter especially in the linear case estimation. As a result, H∞ filter may provide sanother available estimation methods with the capability to ensure and improve estimation for the robotic mapping problem especally in SLAM.