Property:Abstract
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N
The Caltech Multi Vehicles Wireless Testbed (MVWT)
is a platform designed to explore theoritical advances
in multi-vehicle coordination and control, networked
control systems and high con�dence distributed
computation. The contribution of this report is to
present simulation and experimental results on the
generation and implementation of optimal trajectories
for the MVWT vehicles. The vehicles are nonlinear
and spatially contrained with bounded input control.
The trajectories are generated using the NTG software
package developed at Caltech. Minimum time trajectories
and the application of Model Predictive Control (MPC)
are investigated.
can actually follow i.e. trajectories that satisfy every
constraint of the testbed. Those constraints can either
be linear, like the boundaries of the testbed or nonlinear
like the constraints on the input. The main di�erence and
also di�culty in our case is that the system is not linearly
controllable around its equilibrium.
In Section 2 we will give a quick description of the systems
properties and in Section 3 and 4 we will describe the
progression which led us from the optimization problem
to the implementation on the real vehicles. In Section
5 other optimization problems such as minimum time
trajectory generation and model predictive control are
investigated. +
M
The Caltech Multi-Vehicle Wireless Testbed is
an experimental platform for validating theoretical advances
in multiple-vehicle coordination and cooperation, real-time
networked control system, and distributed computation. This
paper describes the design and development of an additional
fleet of 12 second-generation vehicles. These vehicles are
hovercrafts and designed to have lower mass and friction as
well as smaller size than the first generation vehicles. These
hovercrafts combined with the outdoor wireless testbed provide
a perfect hardware platform for RoboFlag competition. +
R
The Electrostatically Suspended Gyroscope (ESG) is a two-axis inertial orientati on
sensor manufactured by Boeing and currently in use on U.S. Navy submarines. The additi
onal ability of the ESG to act as an accelerometer is well known, but extraction of
precision acceleration measuremen ts from an ESG has not been achieved. The major
obstacles to precision accelerometry are the nonlinear dynamics of the ESG rotor and param
etric variation of the ESG electronics. In this paper, we derive a model for the ESG
dynamics with an eye toward efficient representation of the uncertainties in the model. We
represent the model uncert ainties and nonlinearities in a framework amenable to
mu-analysis and analyze ESG accelerometer precision using $\mu$-analysis tools. Finally,
we discuss the implementation of a digital ESG control architecture for use in ESG system
identification and testing of suspension control and acce lerometer algorithms. +
A
The Goursat normal form theorem gives conditions under which an
Pfaffian exterior differential system is equivalent to a certain
normal form. This paper details how the Goursat normal form and its
extensions provide a unified framework for understanding feedback
linearization, chained form, and differential flatness.
<p> Keywords: Exterior differential systems, nonholonomic constraints,
chained form, feedback linearization, differentially flat. +
O
Optimizing protein expression in the One-Pot PURE system: Insights into reaction composition and translation efficiency +
The One-Pot PURE system for in vitro protein expression, which results from a co-culture and one-step purification of 36 essential proteins to support gene transcription and translation, can significantly improve the accessibility and affordability of PURE systems. However, replicating this protocol to match the productivity of the traditional PURE system can take considerable time and effort due to variability in the expression level of individual proteins. In this work, we observed unstable PURE protein expression in two E. coli protein expression strains, M15/pREP4 and BL21(DE3), and addressed this instability using catabolite repression. We identified key proteins whose concentration in the One-Pot PURE mixture significantly impacted the reaction’s protein expression capacity. Compared to the original method using two E. coli protein expression strains, we found that consolidating all expression vectors onto one BL21 (DE3) strain led to more uniform cell growth at the time of protein induction, thereby improving the composition of critical translation initiation factors in the purified mixture for efficient translation. We also found that variations in commercial energy solution formulations could compensate for deficiencies in the One-Pot PURE protein composition. Additionally, our study revealed significant differences in the translation capacity of commercially available E. coli tRNAs, suggesting the potential of optimizing tRNA composition to improve protein translation. Taken together, this work highlights the intricate biochemical interplay influencing protein expression capacity in the One-Pot PURE system and presents strategies to improve its robustness and productivity. +
T
The Python Control Systems Library (python-control) is an open source set of Python classes and functions that implement common operations for the analysis and design of feedback control systems. In addition to support for standard LTI control systems (including time and frequency response, block diagram algebra, stability and robustness analysis, and control system synthesis), the package provides support for nonlinear input/output systems, including system interconnection, simulation, and describing function analysis. A MATLAB compatibility layer provides an many of the common functions corresponding to commands available in the MATLAB Control Systems Toolbox. The library takes advantage of the Python “scientific stack” of Numpy, Matplotlib, and Jupyter Notebooks and offers easy interoperation with other category-leading software systems in data science, machine learning, and robotics that have largely been built on Python. +
A
A Method for Cost-Effective and Rapid Characterization of Engineered T7-based Transcription Factors by Cell-Free Protein Synthesis Reveals Insights into the Regulation of T7 RNA Polymerase-Driven Expression +
The T7 bacteriophage RNA polymerase (T7 RNAP) serves as a model for understanding RNA synthesis, as a tool for protein expression, and as an actuator for synthetic gene circuit design in bacterial cells and cell-free extract. T7 RNAP is an attractive tool for orthogonal protein expression in bacteria owing to its compact single subunit structure and orthogonal promoter specificity. Understanding the mechanisms underlying T7 RNAP regulation is important to the design of engineered T7-based transcription factors, which can be used in gene circuit design. To explore regulatory mechanisms for T7 RNAP-driven expression, we developed a rapid and cost-effective method to characterize engineered T7-based transcription factors using cell-free protein synthesis and an acoustic liquid handler. Using this method, we investigated the effects of the tetracycline operator’s proximity to the T7 promoter on the regulation of T7 RNAP-driven expression. Our results reveal a mechanism for regulation that functions by interfering with the transition of T7 RNAP from initiation to elongation and validates the use of the method described here to engineer future T7-based transcription factors. +
R
The ability to guarantee safety and progress for all vehicles is vital to the success of the autonomous vehicle industry. We present a framework for designing autonomous vehicle behavior in a way that is safe and guarantees progress for all agents. In this paper, we first introduce a new game paradigm which we term the quasi-simultaneous game. We then define an agent protocol that all agents must use to make decisions in this quasi-simultaneous game setting. According to the protocol, agents first select an intended action using a behavioral profile. Then, the protocol defines whether an agent has precedence to take its intended action or must take a sub-optimal action. The protocol ensures safety under all traffic conditions and liveness for all agents under `sparse' traffic conditions. We provide proofs of correctness of the protocol and validate our results in simulation. +
S
The ability to rapidly design, build, and test prototypes is of key importance to every engineering discipline. DNA assembly often serves as a rate limiting step of the prototyping cycle for synthetic biology. Recently developed DNA assembly methods such as isothermal assembly and type IIS restriction enzyme systems take different approaches to accelerate DNA construction. We introduce a hybrid method, Golden Gate-Gibson (3G), that takes advantage of modular part libraries introduced by type IIS restriction enzyme systems and isothermal assembly's ability to build large DNA constructs in single pot reactions. Our method is highly efficient and rapid, facilitating construction of entire multi-gene circuits in a single day. Additionally, 3G allows generation of variant libraries enabling efficient screening of different possible circuit constructions. We characterize the efficiency and accuracy of 3G assembly for various construct sizes, and demonstrate 3G by characterizing variants of an inducible cell-lysis circuit. +
A
The acrobot is a simple mechanical system patterned after a gymnast
performing on a single parallel bar. By swinging her legs, a gymnast
is able to bring herself into an inverted position with her center of
mass above the part and is able to perform manuevers about this
configuration. This report studies the use of nonlinear control
techniques for designing a controller to operate in a neighborhood of
the manifold of inverted equilibrium points. The techniques described
here are of particular interest because the dynamic model of the
acrobot violates many of the necessary conditions required to apply
current methods in linear and nonlinear control theory.
<p>
The approach used in this report is to approximate the system in such
a way that the behavior of the system about the manifold of
equilibrium points is correctly captured. In particular, we construct
an approximating system which agrees with the linearization of the
original system on the equilibrium manifold and is full state
linearizable. For this class of approximations, controllers can be
constructed using recent techniques from differential geometric control
theory. We show that application of control laws derived in this
manner results in approximate trajectory tracking for the system under
certain restrictions on the class of desired trajectories. Simulation
results based on a simplified model of the acrobot are included. +
The bootstrapping problem consists in designing agents that laern a model of themsleves and the world, and utilize it to achieve useful tasks. It is different from other learning problems as the agent starts with uninterpreted observaions and commands, and with minimal prior information about the world. In this paper, we give a mathematical formalizatoin of this aspect of the problem. We argue that the vague constraint of having âno prior informationâ can be recast as a precise algebraic condition on the agent: that its behavior is invariant to particular classes of nuisances on the world, which we show can be well represented by actions of groups (diffeomorphisms, permutatations, linear transformations) on observations and commands. We then introduce the class of bilinear gradient dynamics sensors (DGDS) as a candidate for learning generic rootic sensorimotor cascades. We show how framing the problem as rejections of group nuisances allows a compact and modular analysis of typical preprocessing stages, such as learning the toplogy of sensors. We demonstrate learning and using such models on real-world range-finder and camera data from publicly available datasets. +
C
The bottom up design of genetic circuits to control cellular behavior is one of the central objectives within Synthetic Biology. Performing design iterations on these circuits in vivo is often a time consuming process, which has led to E. coli cell extracts to be used as simplified circuit prototyping environments. Cell extracts, however, display large batch-to-batch variability in gene expression. In this paper, we develop the theoretical groundwork for a model based calibration methodology for correcting this variability. We also look at the interaction of this methodology with the phenomenon of parameter (structural) non-identifiability, which occurs when the parameter identification inverse problem has multiple solutions. In particular, we show that under certain consistency conditions on the sets of output- indistinguishable parameters, data variability reduction can still be performed, and when the parameter sets have a cer- tain structural feature called covariation, our methodology may be modified in a particular way to still achieve the desired variability reduction. +
P
The control programs of complex autonomous systems that have conditional branching can be modeled as linear hybrid systems. When the state knowledge is perfect, linear hybrid systems with state-based transition conditions can be verified against a specified unsafe set using existing model checking software. This paper introduces a formal method for calculating the failure probability due to state estimation uncertainty of these sensor-driven hybrid systems. Problem complexity is described and some reduction techniques for the failure probability calculation are given. An example goal-based control program is given and the failure probability for that system is calculated. +
J
The cost of the great expressivity of motion planning subject to temporal logic formulae is intractability. Recent advances in sampling-based methods seem to be only applicable to âlow-levelâ control. The problem of realizing âhigh-levelâ controllers that satisfy a temporal logic specification does not readily admit approximations, unless the notion of correctness is relaxed as might be achieved with probabilistic variants of temporal logics. In this paper, we argue that not all possible environment (uncontrolled) behaviors need to be explicitly planned for, but rather short-time strategies can be generated online while maintaining global correctness. We achieve this by separating feasibility from controller synthesis, using a metric from the underlying continuous state space to ensure short-time strategies chained together provide globally correct behavior. +
A
The development of autonomous vehicles for urban driving has seen rapid progress in the past 30 years. This paper provides a summary of the current state of the art in autonomous driving in urban environments, based primarily on the experiences of the authors in the 2007 DARPA Urban Challenge (DUC). The paper briefly summarizes the approaches that different teams used in the DUC, with the goal of describing some of the challenges that the teams faced in driving in urban environments. The paper also highlights the long term research challenges that must be overcome in order to enable autonomous driving and points to opportunities for new technologies to be applied in improving vehicle safety, exploiting intelligent road infrastructure and enabling robotic vehicles operating in human environments. +
O
The fact that genes compete for shared cellular resources poses a fundamental challenge when identifying pa- rameters of synthetic gene circuits. A recently developed model of gene expression tackles this problem by explicitly accounting for resource competition. In addition to accurately describing experimental data, this model only depends on a handful of easily identifiable parameters with clear physical interpretation. Based on this model, we outline a procedure how to select the optimal set of experiments to characterize biomolecular parts in synthetic biology. Additionally, we reveal the role competition for shared resources plays, provide guidelines how to minimize its detrimental effects, and how to leverage this phenomenon to extract the most information about unknown parameters. To illustrate the results, we consider the case of part characterization in cell-free extracts, treat plasmid DNA concentrations as decision variables, and demonstrate the significant performance difference between na ̈ıve and optimal experiment design. +
F
The field of control provides the principles and methods used to design
physical and information systems that maintain desirable performance by sensing
and automatically adapting to changes in the environment. As we begin the 21st
Century, the opportunities to apply control principles and methods are exploding.
New developments in this increasingly information rich world will require a significant
expansion of the basic tool sets of control. This article summarizes the main
findings and recommendations of the Panel on Future Directions in Control, Dynamics,
and Systems, which has recently released its report. The report spells out some
of the prospects for control in the current and future technological environment,
describes the role the field will play in military, commercial, and scientific
applications over the next decade, and recommends actions required to enable new
breakthroughs in engineering and technology through application of control research. +
M
The focus of this paper is on modeling and control of Smart Thermal Grids (STGs) in which the uncertainties in the demand and/or supply are included. We solve the corre- sponding robust model predictive control (MPC) optimization problem using mixed-integer-linear programming techniques to provide a day-ahead prediction for the heat production in the grid. In an example, we compare the robust MPC approach with the robust optimal control approach, in which the day-ahead production plan is obtained by optimizing the objective function for entire day at once. There, we show that the robust MPC approach successfully keeps the supply-demand balance in the STG while satisfying the constraints of the production units in the presence of uncertainties in the heat demand. Moreover, we see that despite the longer computation time, the performance of the robust MPC controller is considerably better than the one of the robust optimal controller. +
P
The goal of this work is to provide accurate dynamical models of oscillations in the flow past a rectangular cavity, for the purpose of bifurcation analysis and control. We have performed an extensive set of direct numerical simulations which provide the data used to derive and evaluate the models. Based on the method of Proper Orthogonal Decomposition (POD) and Galerkin projection, we obtain low-order models (from 6 to 60 states) which capture the dynamics very accurately over a few periods of oscillations, but deviate for long time. +
R
The increasing complexity of electric power sys- tems leads to integration and verification challenges. We consider the problem of designing a control protocol for the aircraft electric power system that meets these system requirements and reacts dynamically to changes in internal system states. We formalize these requirements by translating them into a temporal logic specification language describing the correct behaviors of the system, and apply formal methods to automatically synthesize a controller protocol that satisfies these overall properties and requirements. Through an example, we perform a design exploration to show the benefits and tradeoffs between centralized and distributed control architectures. +
