30,011 research outputs found
Decentralized State Feedback and Near Optimal Adaptive Neural Network Control of Interconnected Nonlinear Discrete-Time Systems
In this paper, first a novel decentralized state feedback stabilization controller is introduced for a class of nonlinear interconnected discrete-time systems in affine form with unknown subsystem dynamics, control gain matrix, and interconnection dynamics by employing neural networks (NNs). Subsequently, the optimal control problem of decentralized nonlinear discrete-time system is considered with unknown internal subsystem and interconnection dynamics while assuming that the control gain matrix is known. For the near optimal controller development, the direct neural dynamic programming technique is utilized to solve the Hamilton-Jacobi-Bellman (HJB) equation forward-in-time. The decentralized optimal controller design for each subsystem utilizes the critic-actor structure by using NNs. All NN parameters are tuned online. By using Lyapunov techniques it is shown that all subsystems signals are uniformly ultimately bounded (UUB) for stabilization of such systems
Stabilization of Linear Systems Over Gaussian Networks
The problem of remotely stabilizing a noisy linear time invariant plant over
a Gaussian relay network is addressed. The network is comprised of a sensor
node, a group of relay nodes and a remote controller. The sensor and the relay
nodes operate subject to an average transmit power constraint and they can
cooperate to communicate the observations of the plant's state to the remote
controller. The communication links between all nodes are modeled as Gaussian
channels. Necessary as well as sufficient conditions for mean-square
stabilization over various network topologies are derived. The sufficient
conditions are in general obtained using delay-free linear policies and the
necessary conditions are obtained using information theoretic tools. Different
settings where linear policies are optimal, asymptotically optimal (in certain
parameters of the system) and suboptimal have been identified. For the case
with noisy multi-dimensional sources controlled over scalar channels, it is
shown that linear time varying policies lead to minimum capacity requirements,
meeting the fundamental lower bound. For the case with noiseless sources and
parallel channels, non-linear policies which meet the lower bound have been
identified
Mathematical control of complex systems
Copyright © 2013 ZidongWang et al.This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Active damping of a DC network with a constant power load: an adaptive passivity-based control approach
This paper proposes a nonlinear, adaptive controller to increase the stability margin of a direct-current (DC) small-scale electrical network containing a constant power load, whose value is unknown. Due to their negative incremental impedance, constant power loads are known to reduce the effective damping of a network, leading to voltage oscillations and even to network collapse. To tackle this problem, we consider the incorporation of a controlled DC-DC power converter between the feeder and the constant power load. The design of the control law for the converter is based on the use of standard Passivity-Based Control and Immersion and Invariance theories. The good performance of the controller is evaluated with numerical simulations.Postprint (author's final draft
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Closing feedback loops fast and over long distances is key to emerging
applications; for example, robot motion control and swarm coordination require
update intervals of tens of milliseconds. Low-power wireless technology is
preferred for its low cost, small form factor, and flexibility, especially if
the devices support multi-hop communication. So far, however, feedback control
over wireless multi-hop networks has only been shown for update intervals on
the order of seconds. This paper presents a wireless embedded system that tames
imperfections impairing control performance (e.g., jitter and message loss),
and a control design that exploits the essential properties of this system to
provably guarantee closed-loop stability for physical processes with linear
time-invariant dynamics. Using experiments on a cyber-physical testbed with 20
wireless nodes and multiple cart-pole systems, we are the first to demonstrate
and evaluate feedback control and coordination over wireless multi-hop networks
for update intervals of 20 to 50 milliseconds.Comment: Accepted final version to appear in: 10th ACM/IEEE International
Conference on Cyber-Physical Systems (with CPS-IoT Week 2019) (ICCPS '19),
April 16--18, 2019, Montreal, QC, Canad
Stabilization of Cascaded Two-Port Networked Systems Against Nonlinear Perturbations
A networked control system (NCS) consisting of cascaded two-port
communication channels between the plant and controller is modeled and
analyzed. Towards this end, the robust stability of a standard closed-loop
system in the presence of conelike perturbations on the system graphs is
investigated. The underlying geometric insights are then exploited to analyze
the two-port NCS. It is shown that the robust stability of the two-port NCS can
be guaranteed when the nonlinear uncertainties in the transmission matrices are
sufficiently small in norm. The stability condition, given in the form of
"arcsin" of the uncertainty bounds, is both necessary and sufficient.Comment: 8 pages, in preparation for journal submissio
Integral population control of a quadratic dimerization process
Moment control of a simple quadratic reaction network describing a
dimerization process is addressed. It is shown that the moment closure problem
can be circumvented without invoking any moment closure technique. Local
stabilization and convergence of the average dimer population to any desired
reference value is ensured using a pure integral control law. Explicit bounds
on the controller gain are provided and shown to be valid for any reference
value. As a byproduct, an explicit upper-bound of the variance of the monomer
species, acting on the system as unknown input due to the moment openness, is
obtained. The obtained results are illustrated by an example relying on the
simulation of a cell population using stochastic simulation algorithms.Comment: 7 pages; 3 figures; accepted at the 52nd IEEE Conference on Decision
and Contro
- …