SICE Journal of Control, Measurement, and System Integration
New Arrival Alert : OFF

You can use this feature after you logged into the site.
Please click the button below.

Log in / Sign up
ONLINE ISSN: 1884-9970
PRINT ISSN: 1882-4889

SICE Journal of Control, Measurement, and System Integration Vol. 13 (2020), No. 2

  • Optimal Path Construction Incorporating a Biarc Interpolation and Smooth Path Following for Automobiles

    pp. 23-29

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.9746/jcmsi.13.23

    In this paper, path construction and path following methods are proposed. The path construction method addresses the problem to generate a path satisfying boundary conditions which are assigned points and tangent directions at the endpoints of the path. This problem is so-called G1 Hermite interpolation, and it has been widely researched, for example, in the area of computer-aided design. The proposed path construction method utilizes one of them, namely the biarc interpolation, as an initial guess for obtaining an optimal path. Trials in some initial conditions show that the proposed method can generate a smooth path with a low computational cost. Meanwhile, the path following method assumes that a linear bicycle model follows a reference path by using the set-point regulator. The proposed method smooths the curvature profile of the reference path to be suited for the path following. Simulation results show that the proposed path construction and following methods achieve smoother tracking than the case without optimal path and smoothing.
  • Optimal Motion Planning of Connected and Automated Vehicles at Signal-Free Intersections with State and Control Constraints

    pp. 30-39

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.9746/jcmsi.13.30

    This paper presents the optimal motion planning problem for connected and automated vehicles (CAVs) to cross a conflict area at an intersection with state and control constraints. First, we formulate the scheduled merging (or crossing) time for all CAVs as a mixed integer linear programming (MILP) problem where the merging time is solved frequently. Second, we formulate the optimal motion planning problem so that the CAVs can achieve their scheduled merging time as well as minimizing the energy consumption. Since we solve the motion planning problem analytically, not all the solutions are feasible to comply with the frequently updated merging time. To solve this problem, we propose a feasibility enforcement period (FEP). Then, we validate the proposed solution through simulation, and the results show that even the merging time is frequently updated, the CAVs can still achieve the merging time with a minimal deviation. Besides, our proposed framework also shows a significant improvement in terms of travel time as compared to the conventional one.
  • Bayesian Inference for Path Following Control of Port-Hamiltonian Systems with Training Trajectory Data

    pp. 40-46

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.9746/jcmsi.13.40

    This paper describes a procedure to design a path following controller of port-Hamiltonian systems based on a training trajectory dataset. The trajectories are generated by human operations, and the training data consist of several trajectories with variations. Hence, we regard the trajectory as a stochastic process model. Then we design a deterministic controller for path following control from the model. In order to obtain reasonable design parameters for a path following controller from the training data, Bayesian inference is adopted in this paper. By using Bayesian inference, we estimate a probability density function of the desired trajectory. Moreover, not only the mean value of the trajectory but also the covariance matrix is acquired. A potential function for path following control is obtained from the probability density function. By incorporating the covariance information into the control system design, it is possible to create a potential function that takes into account uncertainty at each position on the trajectory, and it is expected to construct a control system that generates appropriate assist force for a human operator.

Article Access Ranking

27 May. (Last 30 Days)

  1. Influence of Thermomechanical Treatment on Delayed Fracture Property of Mo-Bearing Medium-Carbon Steel ISIJ International Vol.62(2022), No.2
  2. Comparison of Oxidation Behavior of Various Reactive Elements in Alloys during Electroslag Remelting (ESR) Process: An Overview ISIJ International Advance Publication
  3. Ironmaking Using Municipal Solid Waste (MSW) as Reducing Agent: A Preliminary Investigation on MSW Decomposition and Ore Reduction Behavior ISIJ International Advance Publication
  4. Solute Concentration Distribution in the Vicinity of Solid-Liquid Interface under the Imposition of a Time-Varying Force ISIJ International Advance Publication
  5. A Novel Process for Separation of Magnetite and Phosphorous Phases from a CaO–SiO2–FeO–P2O5 Slag ISIJ International Advance Publication
  6. Interaction Coefficients of Mo, B, Ni, Ti and Nb with Sn in Molten Fe–18mass%Cr Alloy ISIJ International Vol.62(2022), No.3
  7. Phenomenological Understanding about Melting Temperature of Multi-Component Oxides Tetsu-to-Hagané Vol.108(2022), No.4
  8. Removal of Inclusions using Swirling Flow in a Single-Strand Tundish ISIJ International Advance Publication
  9. Fundamentals of Silico-Ferrite of Calcium and Aluminium (SFCA) and SFCA-I Iron Ore Sinter Bonding Phase Formation: Effects of MgO Source on Phase Formation during Heating ISIJ International Vol.62(2022), No.4
  10. Dissolution Kinetics of Synthetic FeCr2O4 in CaO–MgO–Al2O3–SiO2 Slag ISIJ International Vol.62(2022), No.4

Search Phrase Ranking

27 May. (Last 30 Days)

  1. blast furnace
  2. blast furnace productivity
  3. blast furnace permeability
  4. big river steel
  5. galvannealing
  6. jet impingement
  7. jet impingement + cooling + runout table
  8. nitrogen
  9. refractory
  10. steel