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@ -319,6 +319,15 @@ complex but deterministic behavior.
% talk a bit about tools here like FRET. Talk about previous attempts. % talk a bit about tools here like FRET. Talk about previous attempts.
\begin{figure}[htbp]
\centering
\framebox[0.8\textwidth]{\rule{0pt}{3cm}\textit{Strategic, operational,
tactical placeholder}}
\caption{Breakdown of control scope}
\label{fig:strat_op_tact}
\end{figure}
Human control of nuclear power can be divided into three different scopes: Human control of nuclear power can be divided into three different scopes:
strategic, operational, and tactical. Strategic control is the high-level and strategic, operational, and tactical. Strategic control is the high-level and
long term decision making for the plant. This level has objectives that are long term decision making for the plant. This level has objectives that are
@ -401,10 +410,32 @@ interpretation is a weakness that must be addressed.
%export, or naturlly support reactive synth solver ltlsynt, a sota react synth %export, or naturlly support reactive synth solver ltlsynt, a sota react synth
%solver %solver
Once system requirements we defined as temporal logic specifications we will use
the specifications to build the discrete control system. To do this, reactive
synthesis tools will be utilized. Reactive synthesis is a field in computer
science that deals with the automated creation of reactive programs from
temporal logic specifications. A reactive program is one that for a given state
takes an input, and produces an output. Our systems, such as the discrete
portion of the controller, fit exactly this this mold. The current discrete
state, and status of guard conditions are the input to the system, while the
output is the next discrete state. The output of a reactive synthesis algorithim
is a discrete automata.
Reactive synthesis' main advantage is the fact that at no point in the
production of a discrete automata of the program is human engineering required.
The resultant automata is correct by construction. This method of construction
eliminates the possibility of human error outright at the implementation state.
Instead, the effort on the human designer is directed at the specification of
the system behavior itself.
% talk about what the benefits of reactive synth are. Proof chain, machine % talk about what the benefits of reactive synth are. Proof chain, machine
% checkable, blah blah blah % checkable, blah blah blah
%%%%% I NEED TO WRITE ABOUT HOW REQUIREMENTS ARE EXTRACTED AND WHAT BECOME
CONTINUOUS CONTROLLER TRANSITIONS VS DISCRETE GUARD CONDITIONS
%%%%%%%%%%%% Building continuous controllers %%%%%%%%%%%% Building continuous controllers
\subsection{Continuous Controllers}
% The whole point of a hybrid system is that there are continuous components % The whole point of a hybrid system is that there are continuous components
% underneath the digital system. We built the discrete like the physical doesn't % underneath the digital system. We built the discrete like the physical doesn't
@ -424,6 +455,39 @@ interpretation is a weakness that must be addressed.
% Q: Who designs the continuous controllers and how? This methodology verifies % Q: Who designs the continuous controllers and how? This methodology verifies
% them, but doesn't synthesize them. Is this a scope problem? % them, but doesn't synthesize them. Is this a scope problem?
The synthesis of the discrete operational controller is only half of an
autonomous controller. These control systems are hybrid, with both discrete and
continuous components. In this section, we will talk about the continuous
control modes that are the transitions between discrete modes, how they may be
synthesized, and how we plan to verify them.
The operational control scope defines go/no-go decisions that themselves are
deciding what kind of continuous control to implement. To this end, the entry or
exit of a discrete state triggers are themselves the guard conditions \(G\) that
define the barriers of the continuous controller. These continuous controllers
all share a large state space, but each individual continuous control mode
operates within it's own partition defined by the discrete state \(q_i\) and
guard conditions \(G\). This partitioning of the continuous state space amongst
several discrete vector fields controlled by the given \(q_i\) has traditionally
been a difficult problem for validation and verification of systems properties.
Typically, the discontinuity of the vector fields at discrete state interfaces
make things like reachability analysis computationally expensive, and analytic
solutions become intractable.
We circumnavigate these issues by designing our hybrid system from the bottom up
with this verification in mind. Each continuous control mode has an input and
output set clearly defined by our discrete transitions \textit{a priori}.
Consider that we define the continuous state space as \(X\). Whenever we create
guard functions from our design requirements for a given system, we are
effectively creating subsets \(X_{entry,i}\) and \(X_{exit,i}\) for each
discrete mode \(q_i\). These subsets define when the state transitions occur
between discrete modes, but more importantly when building continuous control
modes, they become control objectives.
% Start talking about what it means to build controlelrs to the objectives
% rahter than the other why around. ALso why it makes things much easier to
% verify and validate
%%%%%% Transitory modes %%%%%% Transitory modes
% entry and exit conditions % entry and exit conditions

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@ -55,5 +58,5 @@
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\contentsline {subsection}{\numberline {2.3}HARDENS and Formal Methods}{4}{}% \contentsline {subsection}{\numberline {2.3}HARDENS and Formal Methods}{4}{}%
\contentsline {section}{\numberline {3}Research Approach}{6}{}% \contentsline {section}{\numberline {3}Research Approach}{6}{}%
\contentsline {subsection}{\numberline {3.1}System Requirement and Specifications}{6}{}% \contentsline {subsection}{\numberline {3.1}System Requirement and Specifications}{6}{}%
\contentsline {section}{\numberline {4}Metrics for Success}{7}{}% \contentsline {subsection}{\numberline {3.2}Continuous Controllers}{8}{}%
\contentsline {paragraph}{TRL 3 \textit {Critical Function and Proof of Concept}}{7}{}% \contentsline {section}{\numberline {4}Metrics for Success}{10}{}%
\contentsline {paragraph}{TRL 4 \textit {Laboratory Testing of Integrated Components}}{7}{}% \contentsline {paragraph}{TRL 3 \textit {Critical Function and Proof of Concept}}{10}{}%
\contentsline {paragraph}{TRL 5 \textit {Laboratory Testing in Relevant Environment}}{7}{}% \contentsline {paragraph}{TRL 4 \textit {Laboratory Testing of Integrated Components}}{10}{}%
\contentsline {section}{\numberline {5}Risks and Contingencies}{9}{}% \contentsline {paragraph}{TRL 5 \textit {Laboratory Testing in Relevant Environment}}{10}{}%
\contentsline {subsection}{\numberline {5.1}Computational Tractability of Synthesis}{9}{}% \contentsline {section}{\numberline {5}Risks and Contingencies}{12}{}%
\contentsline {subsection}{\numberline {5.2}Discrete-Continuous Interface Formalization}{9}{}% \contentsline {subsection}{\numberline {5.1}Computational Tractability of Synthesis}{12}{}%
\contentsline {subsection}{\numberline {5.3}Procedure Formalization Completeness}{10}{}% \contentsline {subsection}{\numberline {5.2}Discrete-Continuous Interface Formalization}{12}{}%
\contentsline {section}{\numberline {6}Broader Impacts}{12}{}% \contentsline {subsection}{\numberline {5.3}Procedure Formalization Completeness}{13}{}%
\contentsline {section}{\numberline {7}Schedule, Milestones, and Deliverables}{14}{}% \contentsline {section}{\numberline {6}Broader Impacts}{15}{}%
\contentsline {subsection}{\numberline {7.1}Milestones and Deliverables}{14}{}% \contentsline {section}{\numberline {7}Schedule, Milestones, and Deliverables}{17}{}%
\contentsline {section}{References}{15}{}% \contentsline {subsection}{\numberline {7.1}Milestones and Deliverables}{17}{}%
\contentsline {section}{References}{18}{}%

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