Exact(7)
A class of decentralized adaptive feedback controllers are proposed, which can render the resulting closed-loop error system uniformly ultimately bounded stable.
We present a class of decentralized scheduling algorithms that eliminate contention for I/O ports while maintaining an efficient use of bandwidth.
After determining the appropriate conditions for the stochastic GCC controller, a class of decentralized local state feedback controllers is derived using the linear matrix inequality (LMI).
Based on the Linear Matrix Inequality (LMI) design approach, a class of decentralized local state feedback controllers with additive gain perturbations is established.
Stabilization in multimachine (synchronous generators) power systems is dealt with through a class of decentralized and nonlinear state feedback laws that can be separately designed in a generator-wise fashion, based on what we call the improved swing equations.
Based on the LMI design approach, a class of decentralized local state feedback controllers is proposed, and some sufficient conditions for the existence of guaranteed cost controllers are derived by making use of the LMI.
Similar(53)
This paper investigates an application of neural networks to the guaranteed cost control problem of decentralized robust control for a class of discrete-time uncertain large-scale systems.
First, a new method for designing linear robust decentralized controllers for a class of nonlinear systems is presented.
The problem of robust decentralized stabilization for a class of large-scale, time delay, and uncertain impulsive dynamical systems is introduced and studied.
This paper focuses on the problem of decentralized event-triggered control for a class of interconnected time delay stochastic nonlinear systems with unmodeled dynamics.
This paper considers the problem of designing a decentralized, high frequency, continuous-time periodic controller to simultaneously stabilize a class of two strongly interconnected LTI MIMO systems with or without decentralized fixed modes.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com