Property:Abstract
From Murray Wiki
Jump to navigationJump to search
This is a property of type Text.
E
In this paper we use ellipsoidal cones to achieve
rendezvous of multiple agents. Rendezvous of multiple
agents is shown to be equivalent to ellipsoidal cone invariance
and a controller synthesis framework is presented.
We first demonstrate the methodology on first order LTI
systems and then extend it to rendezvous of mechanical
systems, that is systems that are force driven. +
In this paper, a cascade discrete-continuous state estimator on a partial
order is proposed and its existence investigated. The continuous state estimation
error is bounded by a monotonically nonincreasing function of the discrete state
estimation error, with both the estimation errors converging to zero. This work
shows that the lattice approach to estimation is general as the proposed estimator
can be constructed for any observable and discrete state observable system.
The main advantage of using the lattice approach for estimation becomes clear
when the system has monotone properties that can be exploited in the estimator
design. In such a case, the computational complexity of the estimator can be drastically
reduced and tractability can be achieved. Some examples are proposed to
illustrate these ideas. +
In this paper, we analyze the oscillatory dynamics of a class of cyclic gene regulatory networks and provide engineering principles for the robust synthesis of biochemical oscillators. We first review the first authorâs previous result that the oscillatory parameter regime of the gene regulatory circuits can be rigorously explored by the local stability analysis of a unique equilibrium. The local stability analysis then leads to the first engineering principle that the circuit components, or genes, should be chosen so that the kinetic profiles of the circuit components are similar to each other. Using a homogeneous oscillator model, we further discuss how to reduce the cell-to-cell variability of the oscillators that is caused by intrinsic noise. +
A
In this paper, we analyze the problem of bifurcation control from a
geometric perspective. Our goal is to provide coordinate free,
geometric conditions under which control can be used to alter the
bifurcation properties of a nonlinear control system. These
insights are expected to be useful in understanding the role that
magnitude and rate limits play in bifurcation control, as well as
giving deeper understanding of the types of control inputs that are
required to alter the nonlinear dynamics of bifurcating systems. We
also use a model from active control of rotating stall in axial
compression systems to illustrate the geometric sufficient
conditions of stabilizability. +
In this paper, we approximate models of interconnected
systems that are to be used for decentralized control
design. The suggested approach is based on approximation of
so-called subnetwork models. A subnetwork model is a model
of the interconnected system, as seen from one specific
position
in the network. The simplification is done by using
weighted model reduction, and several approximation
criteria
are given. A new method for weighted model reduction is
used.
The method is based on a combination of known techniques
that use semidefinite programming and frequency-data
samples
of transfer functions. The method is guaranteed to preserve
stability and does not depend strongly on the order of the
original model. This is particularly important for large
interconnected systems. Two examples are given to
illustrate the technique. +
K
In this paper, we consider Kalman filtering over a packet-delaying network. Given the probability distribution of the delay, we
can completely characterize the filter performance via a probabilistic approach. We assume the estimator maintains a buffer of length D so that at each time k, the estimator is able to retrieve all available data packets up to time k â D + 1. Both the cases of sensor with and without necessary computation capability for filter updates are considered. When the sensor has no computation capability, for a given D, we give lower and upper bounds on the probability for which the estimation error covariance is within a prescribed bound. When the sensor has computation capability, we show that the previously derived lower and upper bounds are equal to each other. An approach for determining the minimum buffer length for a required performance in probability is given and an evaluation on the number of expected filter updates is provided. Examples are provided to demonstrate the theory developed in the paper. +
E
In this paper, we consider a discrete time state
estimation problem over a packet-based network. In each
discrete time step, the measurement is sent to a Kalman
filter with some probability that it is received or dropped.
Previous pioneering work on Kalman filtering with intermittent
observation losses shows that there exists a certain threshold of
the packet dropping rate below which the estimator is stable in
the expected sense. In their analysis, they assume that packets
are dropped independently between all time steps. However we
give a completely different point of view. On the one hand, it
is not required that the packets are dropped independently but
just that the information gain pi_g, defined to be the limit of the
ratio of the number of received packets n during N time steps
as N goes to infinity, exists. On the other hand, we show that
for any given pi_g, as long as pi_g > 0, the estimator is stable
almost surely, i.e. for any given epsilon > 0 the error covariance
matrix P{k is bounded by a finite matrix M, with probability
1 â epsilon. Given an error tolerance M, pi_g can in turn be found.
We also give explicit formula for the relationship between M
and epsilon. +
R
In this paper, we consider a robust network
control problem. We consider linear unstable and uncertain
discrete time plants with a network between the sensors and
controller and the controller and plant. We investigate two
defining characteristics of network controlled systems and the
impact of uncertainty on these. Namely, the minimum data rates
required for the two networks and the tolerable data drop out
in the form of packet losses. We are able to derive sufficient
conditions in terms of the minimum data rate and minimum
packet arrival rate to ensure stability of the closed loop system. +
T
In this paper, we consider a robust network
control problem. We consider linear unstable and uncertain
discrete time plants with a network between the sensor and
controller and the controller and plant. We investigate the
effect of data drop out in the form of packet losses. Four
distinct control schemes are explored and sufficient conditions
to ensure almost sure stability of the closed loop system are
derived for each of them in terms of minimum packet arrival
rate and the maximum uncertainty. +
C
In this paper, we consider a robust networked control problem. We consider linear unstable and uncertain discrete time plants with a network between the sensor and controller as well as between
the controller and plant. We investigate the effect of data drop out in the form of packet losses and
we focus on the tradeoff between packet arrival rate versus the uncertainties of the system dynamics. We show that the minimum packet arrival rate and the maximum uncertainty of the system dynamics have a positive correlation. Four distinct control schemes are
explored and serve as examples to study this tradeoff. We derive sufficient condition for each scheme to ensure almost sure stability of the closed loop system. Simulation and examples are provided to assist the theory. +
E
Effective Sensor Scheduling Schemes in a Sensor Network by Employing Feedback in the Communication Loop +
In this paper, we consider a state estimation problem over a bandwidth limited network. A sensor network consisting of N sensors is used to observe the states of M plants, but only p les N sensors can transmit their measurements to a centralized esti..... +
D
In this paper, we consider the following problem. Suppose a sensor is taking measurements of a dynamic process.
It needs to communicate the information over a network of communication links that can drop packets stochastically. What
is the optimal processing at each node in the network? We provide a strategy that yields the optimal performance at the
cost of constant memory and processing at each node. We also provide conditions on the network for the estimate error
covariance to be stable under this algorithm. +
F
In this paper, we consider the optimal control of time-scalable systems.
The time-scaling property is shown to convert the PDE associated
with the Hamilton-Jacobi-Bellman (HJB) equation to a purely spatial PDE.
Solution of this PDE yields the value function at a fixed time, and that solutio
n can be
scaled to find the value function at any point in time. Furthermore, in certain
cases the
unscaled control law stabilizes the system, and the unscaled value function acts
as a
Lyapunov function for that system. For the example of the
nonholonomic integrator, this PDE is solved, and the
resulting optimal trajectories coincide with the known solution to that problem. +
O
In this paper, we consider the problem of active
sensing using mobile sensor nodes that are jointly estimating
the state of a dynamic target as a sensor network. We propose
a gradient search-based decentralized algorithm that demonstrates
the benefits of distributed sensing. We then examine the
task of tracking multiple targets. We use a greedy algorithm
for associating sensors with targets along with the gradientsearch
strategy for sensor vehicle motion planning. Simulation
results show that these simple decentralized strategies perform
quite well and the sensor nodes exhibit interesting cooperative
behavior. +
T
In this paper, we consider the problem of state estimation
using the standard Kalman filter recursions which takes
account of the available sensor health information. Given
a stochastic description of the sensor health, we are able
to show that the expected error covariance converges to a
unique value for all initial values, while the available
previous work only showed the upper bound of the expected
error covariance converges. Our approach provides both
theoretical value to the analysis as well as the potential
to get tighter upper bound. Our results provide a criterion
of evaluating the sensor measurement. In the multisensor
fusion problem, depending on the system error tolerance
levels, it can then be determined whether to fuse a
particular sensor measurement or not. Examples and
simulations are provided to assist the theory. +
A
In this paper, we consider the problem of synthesizing correct-by-construction controllers for discrete-time dynamical systems. A commonly adopted approach in the literature is to abstract the dynamical system into a finite transition system (FTS) and thus convert the problem into a two player game between the environment and the system on the FTS. The controller design problem can then be solved using synthesis tools for general linear temporal logic or generalized reactivity(1) (GR1) specifications. In this article, we propose a new abstraction algorithm. Instead of generating a single FTS to represent the system, we generate two FTSs, which are underand over-approximations of the original dynamical system. We further develop an iterative abstraction scheme by exploiting the concept of winning sets, i.e., the sets of states for which there exists a winning strategy for the system. Finally, the e�ciency of the new abstraction algorithm is illustrated by numerical examples. +
S
In this paper, we consider the scenario where many sensors
co-operate to estimate a process. Only one sensor can take
a measurement at any time step. We wish to come up with
optimal sensor scheduling algorithms. The problem is motivated
by the use of sonar range-finders used by the vehicles
on the Caltech Multi-Vehicle Wireless Testbed. We see that
this problem involves searching a tree in general and propose
and analyze two strategies for pruning the tree to keep
the computation limited. The first is a sliding window strategy
motivated by the Viterbi algorithm, and the second one
uses thresholding. We also study a technique that employs
choosing the sensors randomly from a probability distribution
which can then be optimized. The performance of the
algorithms are illustrated with the help of numerical examples. +
R
In this paper, we describe a receding horizon scheme that satisfies a class of linear temporal logic specifications sufficient to describe a wide range of properties including safety, stability, progress, obligation, response and guarantee. The resulting embedded control software consists of a goal generator, a tra jectory planner, and a continuous controller. The goal generator essentially reduces the tra jectory generation problem to a sequence of smaller problems of short horizon while preserving the desired system-level temporal properties. Subsequently, in each iteration, the tra jectory planner solves the corresponding short-horizon problem with the currently observed state as the initial state and generates a feasible tra jectory to be implemented by the continuous controller. Based on the simulation property, we show that the composition of the goal generator, tra jectory planner and continuous controller and the corresponding receding horizon scheme guarantee the correctness of the system. To handle failures that may occur due to a mismatch between the actual system and its model, we propose a response mechanism and illustrate, through an example, how the system is capable of responding to certain failures and continues to exhibit a correct behavior. +
A
An In Silico Modeling Toolbox for Rapid Prototyping of Circuits in a Biomolecular “Breadboard” System +
In this paper, we develop an experimentally val- idated MATLAB software toolbox as an accompaniment to an in vitro cell-free biomolecular “breadboard” system. The toolbox gives insight into the dynamics of unmeasured states in the cell-free system, accounting especially for the resource usage. Parameter lumping and the reduced order modeling are used to maintain computational tractability and to avoid ill-conditioning. The toolbox allows for most applications to be implemented with standard set of commands for ease of use. Due to the breadboarding nature of the underlying cell-free sys- tem, the toolbox provides a general framework for experiment planning and predictive modeling for synthetic biomolecular circuits cell-free systems, accelerating our capacity to rationally design circuits from well characterized parts. +
T
In this paper, we develop the machinery of exterior differential forms, more particularly the Goursat normal form for a Pfaffian system, for solving nonholonomic motion planning problems, i.e., motion planning for systems with nonintegrable velocity constraints. We use this technique to solve the problem of steering a mobile robot with n trailers, We present an algorithm for finding a family of transformations which will convert the system of rolling constraints on the wheels of the robot with n trailers into the Goursat canonical form. Two of these transformations are studied in detail. The Goursat normal form for exterior differential systems is dual to the so-called chained-form for vector fields that has been studied previously. Consequently, we are able to give the state feedback law and change of coordinates to convert the N-trailer system into chained form. Three methods for planning trajectories for chained-form systems using sinusoids, piecewise constants, and polynomials as inputs are presented.
The motion planning strategy is therefore to first convert the N-trailer system into Goursat form, use this to find the chained-form coordinates, plan a path for the corresponding chained-form system, and then transform the resulting trajectory back into the original coordinates. Simulations and frames of movie animations of the N-trailer system for parallel parking and backing into a loading dock using this strategy are included. +
