Beschreibung
Inhaltsangabe1 Control of Boilers for Thermoelectric Power Plants by Means of a Statistical Model.- 1.1 Introduction.- 1.2 Problems in Controlling Multi variable System.- 1.3 System Analysis and Control by Means of Statistical Model.- 1.4 Practical Procedure for Optimal Controller Design.- 1.5 Application Results at Actual Plants.- 1.6 Closing Remarks.- 2 Feedback Analysis of a Living Body by a Multivariate Autoregressive Model.- 2.1 Introduction.- 2.2 Body Liquid Control and Feedback.- 2.3 Example of the Relative Power Contribution and Impulse Response.- 2.4 Using an Autoregressive Model for Feedback Analysis.- 2.5 Obtaining the Power Contribution.- 2.6 State Equation and Impulse Response.- 2.7 Impulse Response of the Closed and Open Systems.- 2.8 Confirmation by a Virtual Feedback System.- 2.9 Conclusions.- 3 Factor Decomposition of Economic Time Series Fluctuations - Economic and Statistical Models in Harmony.- 3.1 Introduction.- 3.2 Model 1 (Model with Stochastic Components Only).- 3.3 Model 2 (the Model Including Deterministic Components).- 3.4 Model 3 (the Model by Which Macroeconomic Policy Effect can Also be Measured).- 3.5 Has Fine Tuning been Successful?.- 3.6 Is Prediction Ability Available?.- 3.7 Conclusions and Subjects in the Future.- 4 The Statistical Optimum Control of Ship Motion and a Marine Main Engine.- 4.1 Introduction.- 4.2 Outline of the Control of the Motion of the Hull and Main Engine.- 4.3 Statistical Model of Ship Motions and Its Control.- 4.4 Design of Optimum Autopilot System Based on the Control-Type Autoregressive Model.- 4.5 Noise-Adaptive Control System.- 4.6 Rudder-Roll Control System.- 4.7 Application to the Marine Main Engine Governor System.- 4.8 Conclusions.- 5 High Precision Estimation of Seismic Wave Arrival Times.- 5.1 Introduction.- 5.2 Locally Stationary AR Model.- 5.3 Automatic Division of a Locally Stationary Interval.- 5.4 Precision Estimation of Seismic Wave Arrival Times.- 5.5 Application: Earthquake Location and Velocity Structure Determination from Precise Arrival Time Estimates.- 5.6 Conclusions.- 6 Analysis of Dynamic Characteristics of a Driver-Vehicle System.- 6.1 Introduction.- 6.2 Dynamics of Automobile under Later al-Wind Disturbance.- 6.3 Application of Multivariate AR Model to Driver-Vehicle System.- 6.4 Dynamics of Driver-Vehicle System under Lateral-Wind.- 6.5 Conclusions.- 7 Estimation of Directional Wave Spectra Using Ship Motion Data.- 7.1 Introduction.- 7.2 Cross-spectrum Analysis by a Multivariate AR Model.- 7.3 Relation Between the Directional Wave Spectrum and the Ship Motions.- 7.4 Estimation of the Directional Wave Spectrum Using a Bayesian Model.- 7.5 Results of the Tank Test Using a Model Ship.- 7.6 Conclusions.- 8 Control of Filature Production Process.- 8.1 Dropping-end Control and Gap Process.- 8.2 Size Control of Raw Silk.- 8.3 Dwell Time in a Black Box.- 9 Application to Pharmacokinetic Analysis.- 9.1 Introduction.- 9.2 Pharmacokinetic Model.- 9.3 Monte Carlo Estimation of Maximum Log Likelihood.- 9.4 Example.- 9.5 Concluding Remarks.- 10 State Space Modeling of Switching Time Series.- 10.1 Introduction.- 10.2 Time Series Data with Pulses and the Existing Methods.- 10.3 The State Space Model for Time Series with Pulses.- 10.4 Conclusions.- 11 Time Varying Coefficient AR and VAR Models.- 11.1 Introduction.- 11.2 Time Varying Coefficient AR Models.- 11.3 Time Varying Coefficient VAR Models.- 11.4 An Example of Seismic Data Analysis.- 12 Statistical Control of Cement Process.- 12.1 Introduction.- 12.2 Cement Plant.- 12.3 Identification and Control of the Kiln Process.- 12.4 Collection and Identification of the Data under the On-line Control.- 12.5 Optimal Production Level and Pursuit Control.- 12.6 Conclusions.- 13 Analysis of a Human/2-Wheeled-Vehicle System by ARdock.- 13.1 Introduction.- 13.2 Data.- 13.3 AR Model and ARdock.- 13.4 Numerical Results.- 13.5 Analysis of the Hands-Free Steering.- 13.6 The Optimum Control.- 14 Vibration Data Analysis of Automobiles.- 1
