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Your search keyword '"Tatsuo NARIKIYO"' showing total 262 results
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262 results on '"Tatsuo NARIKIYO"'

1. Feedback control for steering support system based on flatness and particle swarm optimization

Author

Michihiro KAWANISHI, Yuta TSUGE, Shi-Jia PEI, and Tatsuo NARIKIYO

Subjects
differential flatness, particle swarm optimization, steering support system, Engineering machinery, tools, and implements, TA213-215, Mechanical engineering and machinery, TJ1-1570
Abstract

In this study we give a feedback control method for steering support system. In this method we consider the stability of the path tracking control system under the limitation of steering angle, so that drivers can drive safer and more comfortable. In order to do this, we have derived linearized system from the nonholonomic kinematic system by the differential flatness consideration and linear control law which stabilizes the path tracking control system. Furthermore, feedback gains are tuned to satisfy the closed loop stability and the limitation of the steering angle by using Particle Swarm Optimization. Usefulness of the proposed control method has been demonstrated by experiments using a 1/10 scale robot car.

Published
2016
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2. Application of Sigmoidal Gompertz Curves in Reverse Parallel Parking for Autonomous Vehicles

Author

Aneesh Chand, Michihiro Kawanishi, and Tatsuo Narikiyo

Subjects
Electronics, TK7800-8360, Electronic computers. Computer science, QA75.5-76.95
Abstract

A new method for the planning and autonomous execution of a single-trajectory, velocity-independent, parallel parking manoeuvre for autonomous vehicles is presented. The procedure commences with the identification and pre-selection of a smooth sigmoidal trajectory known as the Gompertz curve in parametric format. Trajectory parameters are determined in real-time during the path-planning phase using an optimization scheme in order to generate a candidate path. The optimization scheme takes into account the maximum steering angles that can be physically realized and checks the generated candidate trajectory for collisions. Thereafter, the trajectory is reparametrized to arc-length format using the cubic interpolation method and the vehicle orientation at every point of the trajectory is deduced. Following that, values of the steering angle(s) are determined. In the final step, the vehicle uses dead-reckoning to follows the arc-length parametrized path in reverse in order to park itself in a single-manoeuvre. The proposed method is substantiated through both extensive simulations and real sensor data.

Published
2015
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34. Analysis of average consensus of multi-agent systems with time delay using packet selection and synchronization protocol

Author

Binh Minh Nguyen, Tatsuo Narikiyo, Michihiro Kawanishi, Tran Huynh Ngoc, and Satoshi Kikuchi

Subjects
Lyapunov function, State variable, Network packet, Computer science, Applied Mathematics, Linear matrix inequality, Synchronization, Computer Science Applications, Linear dynamical system, symbols.namesake, Control and Systems Engineering, Control theory, symbols, Electrical and Electronic Engineering, Instrumentation, Selection algorithm
Abstract

A stabilization approach for the average consensus of homogeneous multi-agent systems (MASs) entailing non-uniform, asymmetric, and time-varying delays in communication networks is proposed. Agents are modeled using a continuous-time linear dynamical system with a local discrete-time controller. To address communication delays, we propose two logic functions, namely, a packet selection algorithm that constantly selects and updates the latest received control signal packets and a synchronization algorithm that asymmetrically synchronizes these packets to preserve the average value of state variables. Based on the Lyapunov theory, we establish a linear matrix inequality (LMI) condition that sufficiently guarantees the stability and consensus of the overall system. To establish this condition, only the time delay upper bound is required, without any special assumptions on the delay pattern. We thoroughly discuss the proposed algorithm and evaluate its effectiveness via numerical simulations.

Published
2022
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