Architecting decentralized control in large-scale self-adaptive systems

Decentralized Adaptive Control of Large-Scale Non-affine Nonlinear Time-Delay Systems Using Neural Networks

In this paper, a decentralized adaptive neural controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, non-affine subsystems and unknown nonlinear time-delay interconnections. The stability of the closed loop system is guaranteed through Lyapunov-Krasovskii stability analysis. Simulation results are provided to show the effectiveness of the proposed approache...

Decentralized Model Reference Adaptive Control of Large Scale Interconnected Systems with Time-Delays in States and Inputs

This paper investigates the problem of decentralized model reference adaptive control (MRAC) for a class of large scale systems with time varying delays in interconnected terms and state and input delays. The upper bounds of the interconnection terms are considered to be unknown. Time varying delays in the nonlinear interconnection terms are bounded and nonnegative continuous functions and thei...

Optimal decentralized control of large scale systems

This paper presents a new optimized decentralized controller designmethod for solving the tracking and disturbance rejection problems for large-scale linear time-invariant systems, using only low-order decentralized controllers. To illustrate the type of results which can be obtained using the new optimized decentralized control design method, the control of a large flexible space structure is ...

Hybrid Decentralized Control of Large Scale Systems

Motivated by three applications which are under investigation at the Honeywell Research Laboratory in Minneapolis, we introduce a class of large scale control problems. In particular we show that a formation flight problem, a paper machine control problem and the coordination of cameras in a monitoring network can be cast into this class. In the second part of the paper we propose a decentraliz...

Decentralized Interaction Estimators in Large Scale Power Systems with Neural Networks.