Large-Scale Systems Control and Decision MakingSix contributors from Japanese universities explore the basic theory and methodology of control and decision making in systems that either contain many variables or have some special characteristics such as multiple subsystems or control stations, a decentralized and/or hierarchical information stru |
Contents
Models of LargeScale Systems | 3 |
Stability of Composite Systems | 31 |
Control of Composite Systems | 71 |
Decentralized Control Systems and Fixed Modes | 97 |
Optimal Control of Decentralized Systems | 121 |
LargeScale and TwoLevel | 151 |
Common terms and phrases
algorithm analog computer analysis Applications Araki aspiration level Assumptions Automatic Control b₂ closed-loop system composite model composite system conditional utility function constraints convex dependence convex function CS-f Dantzig-Wolfe decomposition decentralized control system decision maker decision problem decomposition defined denotes described diagonal diagonal matrix directional derivative eigenvalues elements equations exists f₁ fixed modes G₁ given by Eqs gradient group utility IEEE Trans Ikeda information structure interactive interconnections k₁ Kuhn-Tucker large-scale systems linear linear programming Lipschitz-continuous Lyapunov function Lyapunov stability M-matrix matrix Minimize multiattribute nonlinear nonlinear programming nonnegative normalized conditional utility objective function obtain optimal control optimal solution optimality condition optimization problems parameter Pareto solution positive-definite s-partition satisficing satisfied scalarization function Shimizu Siljak solve stability station subproblem subsystems Tamura Theorem Theorem 2.1 theory tion two-level u₁ u₂ utility function value function vector well-posedness X₁ y₁ Yoshikawa