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A Writing/ERLM/GOv1.pdf A Writing/ERLM/goals-and-outcomes/v1.tex A Writing/ERLM/goals-and-outcomes/v2.tex M Writing/ERLM/main.aux M Writing/ERLM/main.fdb_latexmk M Writing/ERLM/main.fls M Writing/ERLM/main.log M Writing/ERLM/main.pdf
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Writing/ERLM/GOv1.pdf
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Writing/ERLM/goals-and-outcomes/v1.tex
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\section{Goals and Outcomes}
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The goal of this research is to use formal methods to create control systems
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that can switch between operating modes with a high assurance of correct
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construction. Modern control systems today often exist as hybrid control
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systems. Hybrid systems are those that have both continuous and discrete
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dynamics. Because of this, hybrid systems cannot be fully analyzed using only
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tools from continuous or discrete methods. Today, hybrid control systems are
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unable to be completely verified, that is to say we do not currently have ways
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of being building hybrid control systems that we can be certain meet high level
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strategic objectives, or who's behavior is totally understood.
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The ambiguity on hybrid system behavior is problematic when one of the most
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useful cases of hybrid system control is for improved autonomy of critical
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systems. Nuclear power is a salient example. For a nuclear reactor during
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start-up, every mode of power from initially cold-start, to controlled core
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heating, and eventually full operating power is well understood dynamically.
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For each of these modes, significant portions of the control are optimized using
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automated controllers for each stage. The problem that remains for human
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operators is choosing when to switch from control law to the next, and ensuring
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that the proper conditions are met to do so--but these conditions are also
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clearly defined in regulation and operating procedures a priori.
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We can use the fact that these transition points are well understood in
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combination with formal methods to synthesize the discrete part of a hybrid
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system. From that point, we can have a robust chain of proof that our discrete
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jumps will happen only at the correct times. Once that is established, we can
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use reachability analysis and traditional control theory to ensure that each
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operation 'mode' satisfies liveness, stability, or performance requirements.
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With the combination of these two methods, we can be sure of correct behavior
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switching between modes, and that strategic goals remain met while transitioning
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from one mode switch to the next.
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If this research is successful, we will be able to do the following:
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\begin{enumerate}
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\item
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\textbf{Formalize} mode switching requirements as logical statements that
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can then be translated into a controller implementation. This piece will
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address the correct-by-construction generation of the mode switching
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controller.
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\item
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\textbf{Categorize} different continuous modes by their strategic relevance.
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Certain modes exist as control laws from one mode to the next, such as a
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controlled heating rate on reactor start-up before reaching operational
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conditions. Other modes exist as stable regions, such as full-power
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operation.
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\item
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\textbf{Verify} continuous modes and accompanying continuous control laws
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satisfy strategic requirements. This can be done with reachability analysis,
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and ensuring that each mode transition as allowed from the requirements
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synthesis squares up against the reachability analysis and the continuous
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dynamics.
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\item
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\textbf{Prove} that a given hybrid system achieves strategic goals across
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hybrid control modes. By seperately formalizing and analyzing continuous
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dyanmics and discrete dynamics, we can come back to say the whole hybrid
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system has met a strong guarantee of requirement adherence.
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\end{enumerate}
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\section{Goals and Outcomes}
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The goal of this research is to use formal methods to create high-assurance
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hybrid control systems. Hybrid control systems have great potential for
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implementation in autonomous control as they are able to change control laws
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based on discrete triggers in the operating range of the controller. This allows
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the autonomous controller to use several easily tractable control laws for different
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regions in the state space, instead of using one controller over the entire
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systems operating range. But, the discrete jumps between control laws in a
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hybrid controller present challenges in proving stability and liveness
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properties of the whole system. While tools from control theory can prove
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properties for each individual control mode, they do not generalize when
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switching between control laws is introduced.
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This research will take a different approach to hybrid controller synthesis and
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verification. Using tools from the formal methods community, we will create
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controllers that are correct-by-construction and allow guarantees to be made
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about the whole system's behavior. To demonstrate this, an autonomous controller
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for a nuclear power plant start-up procedure will be created. Nuclear power is
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an excellent test case for this work as the continuous piece of reactor dynamics
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is well studied, while the discrete component of mode switching is explicitly
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stated in regulatory requirements and operating procedures. Nuclear reactor
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control today \textit{is} a hybrid control system--many functions in the control
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room use automated controllers for basic tasks, but the engagement and selection
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of these controllers is done by human operators referencing procedures to make
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decisions.
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The capability to create high-assurance hybrid control systems has the potential
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to reduce the labor required to operate critical systems by removing the human
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operator from the loop. Nuclear power stands to greatly benefit from greater
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controller autonomy as the largest expense for reactors today is operations and
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maintenance. Technologies such as microreactors and modular reactors will
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improve the maintenance costs required through the use of factory-made
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replacement components, but will suffer increased operating costs per megawatt
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produced if they are required to staff the same way reactors today are staffed.
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But, if increased autonomy can be introduced, these costs will be ameliorated.
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If this research is successful, we will be able to do the following:
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\begin{enumerate}
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\item
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\textbf{Formalize mode switching requirements as logical specifications that
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can be translated into discrete controller implementations.} The discrete
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transitions between continuous controller modes is often explicitly defined
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for critical systems in operating procedures and regulatory requirements.
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These statements will be translated into a temporal logic, which will then
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be synthesized into a discrete controller implementation for continuous
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controller mode switching.
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\item
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\textbf{Categorize different continuous controller modes by their strategic
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relavance.} Different control modes serve one of two purposes: they may be
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transitory or stabilizing. Knowing when to switch from one control mode to
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another is handled by the discrete component of the hybrid system, but this
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outcome will identify the properties the continuous components must satisfy
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for each controller mode.
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\item
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\textbf{Verify that continuous controller modes satisfy dynamic
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requirements.} For the discrete transitions between control modes to be
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useful, we must ensure that the continuous control modes will actually move
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the system to the transition, or if stabilizing, keep the system from
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leaving the control mode.
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\item
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\textbf{Prove that a hybrid system implementation achieve strategic goals
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across the entire controller operating range.} By creating discrete
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controller transitions from logical specifications that are
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correct-by-construction and validating that continuous components perform
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appropriately between discrete transitions, we can be confident that the
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hybrid system is free from defect and can be utilized as a critical
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autonomous controller.
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\end{enumerate}
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@ -1,6 +1,6 @@
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\section{Goals and Outcomes}
|
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|
||||
The goal of this research is to use formal methods to create control systems
|
||||
that can switch between operating modes with a high assurance of correct
|
||||
construction. Modern control systems today often exist as hybrid control
|
||||
systems. Hybrid systems are those that have both continuous and discrete
|
||||
dynamics. Because of this, hybrid systems cannot be fully analyzed using only
|
||||
tools from continuous or discrete methods. Today, hybrid control systems are
|
||||
unable to be completely verified, that is to say we do not currently have ways
|
||||
of being building hybrid control systems that we can be certain meet high level
|
||||
strategic objectives, or who's behavior is totally understood.
|
||||
|
||||
The ambiguity on hybrid system behavior is problematic when one of the most
|
||||
useful cases of hybrid system control is for improved autonomy of critical
|
||||
systems. Nuclear power is a salient example. For a nuclear reactor during
|
||||
start-up, every mode of power from initially cold-start, to controlled core
|
||||
heating, and eventually full operating power is well understood dynamically.
|
||||
For each of these modes, significant portions of the control are optimized using
|
||||
automated controllers for each stage. The problem that remains for human
|
||||
operators is choosing when to switch from control law to the next, and ensuring
|
||||
that the proper conditions are met to do so--but these conditions are also
|
||||
clearly defined in regulation and operating procedures a priori.
|
||||
|
||||
We can use the fact that these transition points are well understood in
|
||||
combination with formal methods to synthesize the discrete part of a hybrid
|
||||
system. From that point, we can have a robust chain of proof that our discrete
|
||||
jumps will happen only at the correct times. Once that is established, we can
|
||||
use reachability analysis and traditional control theory to ensure that each
|
||||
operation 'mode' satisfies liveness, stability, or performance requirements.
|
||||
With the combination of these two methods, we can be sure of correct behavior
|
||||
switching between modes, and that strategic goals remain met while transitioning
|
||||
from one mode switch to the next.
|
||||
|
||||
If this research is successful, we will be able to do the following:
|
||||
|
||||
\begin{enumerate}
|
||||
|
||||
\item
|
||||
\textbf{Formalize} mode switching requirements as logical statements that
|
||||
can then be translated into a controller implementation. This piece will
|
||||
address the correct-by-construction generation of the mode switching
|
||||
controller.
|
||||
|
||||
\item
|
||||
\textbf{Categorize} different continuous modes by their strategic relevance.
|
||||
Certain modes exist as control laws from one mode to the next, such as a
|
||||
controlled heating rate on reactor start-up before reaching operational
|
||||
conditions. Other modes exist as stable regions, such as full-power
|
||||
operation.
|
||||
|
||||
\item
|
||||
\textbf{Verify} continuous modes and accompanying continuous control laws
|
||||
satisfy strategic requirements. This can be done with reachability analysis,
|
||||
and ensuring that each mode transition as allowed from the requirements
|
||||
synthesis squares up against the reachability analysis and the continuous
|
||||
dynamics.
|
||||
|
||||
\item
|
||||
\textbf{Prove} that a given hybrid system achieves strategic goals across
|
||||
hybrid control modes. By seperately formalizing and analyzing continuous
|
||||
dyanmics and discrete dynamics, we can come back to say the whole hybrid
|
||||
system has met a strong guarantee of requirement adherence.
|
||||
|
||||
\end{enumerate}
|
||||
\input{goals-and-outcomes/v2}
|
||||
|
||||
\bibliography{references}
|
||||
|
||||
\end{document}
|
||||
|
||||
|
||||
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Reference in New Issue
Block a user