Property:Abstract
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C
In this paper, we discuss consensus problems for a network of dynamic agents with fixed and switching topologies. We analyze three cases: i) networks with switching topology and no time-delays, ii) networks with fixed topology and communication time-delays, and iii) max-consensus problems (or leader determination) for groups of discrete-time agents. In each case, we introduce a linear/nonlinear consensus protocol and provide convergence analysis for the proposed distributed algorithm. Moreover, we establish a connection between the Fiedler eigenvalue of the information flow in a network (i.e. algebraic connectivity of the network) and the negotiation speed (or performance) of the corresponding agreement protocol. It turns out that balanced digraphs play an important role in addressing average-consensus problems. We introduce disagreement functions that play the role of Lyapunov functions in convergence analysis of consensus protocols. A distinctive feature of this work is to address consensus problems for networks with directed information flow. We provide analytical tools that rely on algebraic graph theory, matrix theory, and control theory. Simulations are provided that demonstrate the effectiveness of our theoretical results. +
R
Resource Competition as a Source of Non-Minimum Phase Behavior in Transcription-Translation Systems +
In this paper, we explore how resource limitations can lead to coupling interactions between orthogonal com- ponents in a transcription-translation system and the effect those interactions have on its dynamical behavior. To illustrate these ideas, we present a motivating example featuring a classical network motif: the signal cascade. We show that through coupling interactions arising from competition for limited resources, the system exhibits a non-minimum phase step response. These observations lead us to identify a key network motif with the potential to introduce right half plane zeros into the system transfer function. We characterize the parametric conditions under which the network motif produces a non-minimum phase transfer function and illustrate with two examples how resource limitations can 1) introduce the network motif through these coupling interactions, 2) satisfy the parametric conditions sufficient to produce a right half plane zero. +
F
In this paper, we generalize a recently proposed
method for model reduction of linear systems to the frequencyweighted
case. The method uses convex optimization and can be
used both with sample data and exact models. We also derive
simple a priori bounds on the frequency-weighted error. We
combine the method with a rank-minimization heuristic, to
approximate multi-inputÂmulti-output systems. We also present
two applications  environment compensation and simpli�cation
of interconnected models  where we argue the proposed
methods are useful. +
C
In this paper, we introduce a consensus protocol for a network of dynamic
agents that allows the agents to reach
a decision in a distributed and cooperative
fashion. We consider both linear and nonlinear protocols as well as
the characteristic function of the communication links in the network.
This includes links with delay and (possible) distortion/filtering effects.
It turns out that for a number of protocols, the convergence properties
and the decision-value obtained via this protocol is strongly related
to connectivity and algebraic graph theoretic properties of the information
flow in the network of decision-making agents. Standard
tools from multivariable control and linear control theory such as Nyquist
plots appear naturally for convergence analysis of the obtained linear
protocols. For the analysis of the nonlinear protocols, certain
disagreement costs are constructed that are minimized by the consensus
protocols in a distributed way. Simulation results are provided for attitude
alignment of a group of 20 dynamic agents. +
S
In this paper, we investigate formal test-case generation for high-level mission objectives, specifically reachability, of autonomous systems. We use Kripke structures to represent the high-level decision-making of the agent under test and the abstraction of the test environment. First, we define the notion of a test specification, focusing on a fragment of linear temporal logic represented by sequence temporal logic formulas. Second, we formulate the problem of test graph synthesis to find a test configuration for which the agent must satisfy the test specification to satisfy its mission objectives. We an algorithm, based on network flows, for synthesizing a test graph by restricting transitions, represented by edge deletions, on the original graph induced by the Kripke structures. The algorithm synthesizes the test graph iteratively using an integer linear program. We prove completeness for our algorithm, and we show that the edge deletions in each iteration maintain feasibility of the integer linear program in the subsequent iteration. We formalize the notion of a minimally constrained test graph in terms of maximum flow, and prove the synthesized test graph to be minimally constrained. We demonstrate our algorithm on a simple graph and on gridworlds. +
P
In this paper, we investigate pre-orders for reasoning about input-to-state stability properties of hybrid systems. We define the notions of uniformly continuous input simulations and bisimulations, which extend the notions in previous work to include inputs. We show that uniformly con- tinuous input bisimulations preserve incremental input-to-state stability of hybrid systems, and thus provide a basis for constructing abstractions for verification. We show that Lyapunov function based input-to-state stability analysis can be cast in our framework as constructing a simpler one-dimensional system, using a uniformly continuous input simulation, which is input-to-state stable, and thus, inferring the input-to-state stability of the original system. +
B
In this paper, we investigate pre-orders for reason- ing about input-to-state stability properties of hybrid systems. We define the notions of uniformly continuous input simulations and bisimulations, which extend the notions in previous work to include inputs. We show that uniformly continuous input bisimulations preserve incremental input-to-state stability of hybrid systems, and thus provide a basis for constructing abstractions for verification. We show that Lyapunov function based input-to-state stability analysis can be cast in our frame- work as constructing a simpler one-dimensional system, using a uniformly continuous input simulation, which is input-to-state stable, and thus, inferring the input-to-state stability of the original system. +
P
In this paper, we pose the N-scalar agent rendezvous
as a polyhedral cone invariance problem in the N
dimensional phase space. The underlying dynamics of the
agents are assumed to be linear. We derive a condition
for positive invariance for polyhedral cones. Based on this
condition, we demonstrate that the problem of determining a
certificate for rendezvous can be stated as a convex feasibility
problem. Under certain rendezvous requirements, we show
that there are no robust closed-loop linear solutions that satisfy
the invariance conditions. We show that the treatment of the
rendezvous problem on the phase plane can be extended to
the case where agent dynamics are non-scalar. +
D
Distributed Cooperative Control of Multiple Vehicle Formations Using Structural Potential Functions +
In this paper, we propose a framework for formation stabilization of
multiple autonomous vehicles in a distributed fashion. Each vehicle is assumed to
have simple dynamics, i.e. a double-integrator, with a directed (or an undirected)
information ow over the formation graph of the vehicles. Our goal is to find
a distributed control law (with an efficient computational cost) for each vehicle
that makes use of limited information regarding the state of other vehicles. Here,
the key idea in formation stabilization is the use of natural potential functions
obtained from structural constraints of a desired formation in a way that leads to
a collision-free, distributed, and bounded state feedback law for each vehicle. +
V
In this paper, we propose reactive control impro- visation to synthesize voluntary lane-change policy that meets human preferences under given traffic environments. We first train Markov models to describe traffic patterns and the motion of vehicles responding to such patterns using traffic data. The trained parameters are calibrated using control improvisation to ensure the traffic scenario assumptions are satisfied. Based on the traffic pattern, vehicle response models, and Bayesian switching rules, the lane-change environment for an automated vehicle is modeled as a Markov decision process. Based on human lane-change behaviors, we train a voluntary lane- change policy using explicit-duration Markov decision process. Parameters in the lane-change policy are calibrated through reactive control improvisation to allow an automated car to pursue faster speed while maintaining desired frequency of lane-change maneuvers in various traffic environments. +
D
In this paper, we provide a theoretical framework that consists of
graph theoretical and Lyapunov-based approaches to stability analysis and
distributed control of multi-agent formations.
This framework relays on the
notion of graph rigidity as a means of identifying the shape variables
of a formation. Using this approach, we can
formally define formations of multiple vehicles and three types of
stabilization/tracking problems for dynamic multi-agent systems.
We show how these three problems can be addressed mutually independent of
each other for a formation of two agents. Then, we introduce a procedure
called dynamic node augmentation that allows construction of a larger
formation with more agents that can be rendered structurally stable
in a distributed manner from some initial formation that
is structurally stable. We provide two examples of formations
that can be controlled using this approach, namely, the V-formation
and the diamond formation. +
A
In this paper, we provide tools for convergence and
performance analysis of an agreement protocol for a
network of integrator agents with directed information
flow. We also analyze algorithmic robustness of this
consensus protocol for networks with mobile nodes and
switching topology. A connection is established between the Fiedler eigenvalue of the graph Laplacian and
the performance of this agreement protocol. We demon-
strate that a class of directed graphs, called balanced
graphs, have a crucial role in solving average-consensus
problems. Based on the properties of balanced graphs,
a group disagreement function (i.e. Lyapunov function)
is proposed for convergence analysis of this agreement
protocol for networks with directed graphs and switching topology. +
M
In this paper, we study automated test generation for discrete decision-making modules in autonomous systems. First, we consider a subset of Linear Temporal Logic to represent formal requirements on the system and the test environment. The system specification captures requirements for the system under test while the test specification captures basic attributes of the test environment known to the system, and additional structure provided by a test engineer, which is unknown to the system. Second, a game graph representing the high-level interaction between the system and the test environment is constructed from transition systems modeling the system and the test environment. We provide an algorithm that finds the projection of the acceptance conditions of the system and test specifications on the game graph. Finally, to ensure that the system meets the test specification in addition to satisfying the system specification, we present a framework to construct a minimally constrained test. Specifically, we formulate this as a multi-commodity network flows problem, and present two optimizations to solve for the minimally constrained test. We conclude with future directions on applying these algorithms to constrain test environments in self-driving applications. +
T
In this paper, we study the classical problem
of stabilizing a Linear Time Invariant (LTI) system in a
packet-based network setting. We assume that the LTI system
is unstable but both controllable and observable. The state
information is transmitted to the controller over a packetbased
network. We also assume that there is a perfect link
from the controller to the plant. We give a set of sufficient
conditions under which the system can be stabilized for a
given data rate C. In particular, these conditions can yield an
upper bound on the minimum C for which the system can
be stabilized. A recursive encoding-decoding scheme and an
associated control law are proposed to achieve stability for
rate exceeding this bound. An optimal bit allocation problem
is investigated in which we ask about how to allocate the
bits in a single packet for a subsystem of a general LTI
system such that a minimum upper bound on the data rate is
achieved.We then formulate the optimal bit allocation problem
as a Linear Matrix Inequality (LMI) optimization problem
which can be solved efficiently using standard Semi-definite
Programming (SDP) solvers. Examples and simulations are
given to demonstrate the results. +
C
In this paper, we synthesize a robust connected cruise controller with performance guarantee using probabilis- tic model checking, for a vehicle that receives motion informa- tion from several vehicles ahead through wireless vehicle-to- vehicle communication. We model the car-following dynamics of the preceding vehicles as Markov chains and synthesize the connected cruise controller as a Markov decision process. We show through simulations that such a design is robust against imperfections in communication. +
D
In this study, an Escherichia coli (E. coli) based transcription translation cell-free system (TX-TL) was employed to sample various enzyme expression levels of the violacein pathway. TX-TL enables rapid modifications and prototyping of the pathway without complicated cloning cycles. The violacein metabolic pathway has been successfully reconstructed in TX-TL. Analysis of the product via UV-Vis absorption and liquid chromatography-mass spectrometry detected 4.95 mM of violacein. Expression levels of pathway enzymes were modeled using the TX-TL Toolbox. The model revealed the length of an enzyme coding sequence (CDS) significantly affected its expression level. Finally, pathway exploration suggested an improvement in violacein production at high VioC and VioD DNA concentrations. +
E
In this work we consider a class of networked control systems (NCS) when the control signal is sent to the plant via a UDP-like communication protocol, the controller sends a communication packet to the plant across a lossy network but the controller..... +
A
An Estimation Algorithm for a Class of Networked Control Systems Using UDP-Like Communication Schemes +
In this work we consider a class of networked control
systems (NCS) when the control signal is sent to the plant
via a UDP-like communication protocol. In this case the
controller sends a communication packet to the plant across
a lossy network, but the controller does not receive any
acknowledgement signal indicating the status of the control
packet. Standard observer based estimators assume the
estimator has knowledge of what control signal is applied
to the plant. Under the UDP-like protocol the
controller/estimator does not have explicit knowledge
whether the control signals have been applied to the plant
or not. We present a simple estimation algorithm that
consists of a state and mode observer as well as a
constraint on the control signal sent to the plant. For
the class of systems considered, discrete time LTI plants
where at least one
of the states that is directly affected by the input is
also part of the measurement vector, the estimator is able
to recover the fate of the control packet from the
measurement at the next timestep and exhibit better
performance than other naive schemes. For
single-input-single-output (SISO) systems we are able to
show convergence properties of the estimation error and the
state. Simulations are provided to demonstrate the
algorithm and show it's effectiveness. +
C
Characterization of minimum inducer separation time for a two-input integrase-based event detector +
In this work, we present modeling and experimental characterization of the minimum time needed for flipping of a DNA substrate by a two-integrase event detector. The event detector logic diâµerentiates the temporal order of two chemical inducers. We find that bundling biological rate parameters (transcription, translation, DNA search- ing, DNA flipping) into only a few rate constants in a stochastic model is sufficient to accurately predict final DNA states. We show, through time course data in E.coli, that these modeling predictions are reproduced in vivo. We believe this model validation is critical for using integrase-based systems in larger circuits. +
L
Learning pose estimation for UAV autonomous navigation and landing using visual-inertial sensor data +
In this work, we propose a robust network-in-the-loop control system for autonomous navigation and landing of an Unmanned-Aerial-Vehicle (UAV). To estimate the UAV's absolute pose, we develop a deep neural network (DNN) architecture for visual-inertial odometry, which provides a robust alternative to traditional methods. We first evaluate the accuracy of the estimation by comparing the prediction of our model to traditional visual-inertial approaches on the publicly available EuRoC MAV dataset. The results indicate a clear improvement in the accuracy of the pose estimation up to 25% over the baseline. Finally, we integrate the data-driven estimator in the closed-loop flight control system of Airsim, a simulator available as a plugin for Unreal Engine, and we provide simulation results for autonomous navigation and landing. +
