26,223 research outputs found
Robust Hinf tracking control design for a class of switched linear systems using descriptor redundancy approach
International audienceThe work presented in this paper concerns the output feedback tracking control for a class of Switched Linear Systems (SLS) with external disturbances. The main result is based on a descriptor redundancy formulation of the closedloop dynamics. The proposed approach allows the avoiding of the crossing terms appearance between the controller's and the switched system's matrices leading to easier Linear Matrix Inequality (LMI) formulation. Multiple Lyapunov functional methods are utilized to the stability analysis and controller design. By introducing the Proportional-Derivative (PD) controller, a robust Hinf output feedback tracking performance has been satisfied. The efficiency of the proposed synthesis procedure has been illustrated by a numerical example
Symbolic Models for Stochastic Switched Systems: A Discretization and a Discretization-Free Approach
Stochastic switched systems are a relevant class of stochastic hybrid systems
with probabilistic evolution over a continuous domain and control-dependent
discrete dynamics over a finite set of modes. In the past few years several
different techniques have been developed to assist in the stability analysis of
stochastic switched systems. However, more complex and challenging objectives
related to the verification of and the controller synthesis for logic
specifications have not been formally investigated for this class of systems as
of yet. With logic specifications we mean properties expressed as formulae in
linear temporal logic or as automata on infinite strings. This paper addresses
these complex objectives by constructively deriving approximately equivalent
(bisimilar) symbolic models of stochastic switched systems. More precisely,
this paper provides two different symbolic abstraction techniques: one requires
state space discretization, but the other one does not require any space
discretization which can be potentially more efficient than the first one when
dealing with higher dimensional stochastic switched systems. Both techniques
provide finite symbolic models that are approximately bisimilar to stochastic
switched systems under some stability assumptions on the concrete model. This
allows formally synthesizing controllers (switching signals) that are valid for
the concrete system over the finite symbolic model, by means of mature
automata-theoretic techniques in the literature. The effectiveness of the
results are illustrated by synthesizing switching signals enforcing logic
specifications for two case studies including temperature control of a six-room
building.Comment: 25 pages, 4 figures. arXiv admin note: text overlap with
arXiv:1302.386
Control of quad-rotor UAVs using switched-system synthesis methods
This thesis applies switched systems synthesis and linear quadratic regulator (LQR) theory to control of a quad-rotor unmanned aerial vehicle (UAV). The thesis presents the development of the system dynamics, the theory of LQR and its implementation, the synthesis and simulation results of switched control of the UAV, which consists of a central rigid body and four propellers in a cross configuration. Since first introduced in 1917, UAVs have been extensively studied and utilized in various circumstances that prefer no human pilots aboard, due to safety, expenses, etc. Stability is crucial in controller design, while other parameters also draw great concerns, depending on the environment.
The methodologies of LQR control and semidefinite programming (SDP) are discussed to provide preliminary knowledge of the switched control. Benefits of the LQR control include tracking of reference trajectories and cost function minimization. The core of switched control methods is the design and analysis of systems whose dynamical models and performance specifications are governed by the modes of an automaton. By assigning the weights properly on the performance states, the controller allows transitions between modes with stability guaranteed. The model of the UAV was established by analyzing the equations of motions based on kinemics and dynamics, then linearized and discretized for design purposes. Both the LQR and switched controllers were generated and simulated using MATLAB, and the LQR controller was transferred to the physical UAV for test and data collection. To incorporate with reality, lags to commands and saturation of the motors were taken into consideration
New advances in H∞ control and filtering for nonlinear systems
The main objective of this special issue is to
summarise recent advances in H∞ control and filtering
for nonlinear systems, including time-delay, hybrid and
stochastic systems. The published papers provide new
ideas and approaches, clearly indicating the advances
made in problem statements, methodologies or applications
with respect to the existing results. The special
issue also includes papers focusing on advanced and
non-traditional methods and presenting considerable
novelties in theoretical background or experimental
setup. Some papers present applications to newly
emerging fields, such as network-based control and
estimation
Low-Complexity Quantized Switching Controllers using Approximate Bisimulation
In this paper, we consider the problem of synthesizing low-complexity
controllers for incrementally stable switched systems. For that purpose, we
establish a new approximation result for the computation of symbolic models
that are approximately bisimilar to a given switched system. The main advantage
over existing results is that it allows us to design naturally quantized
switching controllers for safety or reachability specifications; these can be
pre-computed offline and therefore the online execution time is reduced. Then,
we present a technique to reduce the memory needed to store the control law by
borrowing ideas from algebraic decision diagrams for compact function
representation and by exploiting the non-determinism of the synthesized
controllers. We show the merits of our approach by applying it to a simple
model of temperature regulation in a building
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
Optimal Switching Synthesis for Jump Linear Systems with Gaussian initial state uncertainty
This paper provides a method to design an optimal switching sequence for jump
linear systems with given Gaussian initial state uncertainty. In the practical
perspective, the initial state contains some uncertainties that come from
measurement errors or sensor inaccuracies and we assume that the type of this
uncertainty has the form of Gaussian distribution. In order to cope with
Gaussian initial state uncertainty and to measure the system performance,
Wasserstein metric that defines the distance between probability density
functions is used. Combining with the receding horizon framework, an optimal
switching sequence for jump linear systems can be obtained by minimizing the
objective function that is expressed in terms of Wasserstein distance. The
proposed optimal switching synthesis also guarantees the mean square stability
for jump linear systems. The validations of the proposed methods are verified
by examples.Comment: ASME Dynamic Systems and Control Conference (DSCC), 201
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