Copy edit: Final tactical pass on dense technical sections
- Improved clarity in continuous controller verification sections - Shorter sentences in complex technical passages - Better topic-stress positioning in verification discussions - Maintained technical precision while improving readability
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@ -314,9 +314,7 @@ the vector fields at discrete state interfaces makes reachability analysis
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computationally expensive, and analytic solutions often become intractable
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computationally expensive, and analytic solutions often become intractable
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\cite{MANYUS THESIS}.
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\cite{MANYUS THESIS}.
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These issues are circumvented by designing the hybrid system from the bottom up
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I circumvent these issues by designing the hybrid system from the bottom up with verification in mind. The discrete transitions define each continuous control mode's input and output sets clearly \textit{a priori}.
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with verification in mind. The discrete transitions define each continuous
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control mode's input and output sets clearly \textit{a priori}.
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Each discrete mode $q_i$ provides
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Each discrete mode $q_i$ provides
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three key pieces of information for continuous controller design:
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three key pieces of information for continuous controller design:
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@ -374,9 +372,7 @@ reachable within time horizon $T$:
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\text{Reach}(\mathcal{X}_{entry}, f_i, [0,T]) \cap \mathcal{X}_{exit} \neq \emptyset
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\text{Reach}(\mathcal{X}_{entry}, f_i, [0,T]) \cap \mathcal{X}_{exit} \neq \emptyset
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\]
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\]
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The discrete controller defines clear boundaries in continuous state
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The discrete controller defines clear boundaries in continuous state space. This makes the verification problem for each transitory mode well-posed. The possible initial conditions, target conditions, and safety envelope are all known before verification begins. The verification task then confirms that the candidate continuous controller achieves the objective from all possible starting points.
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space, making the verification problem for each transitory mode well-posed. The possible initial conditions, target conditions, and safety envelope are all known. The verification task then confirms that the candidate
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continuous controller achieves the objective from all possible starting points.
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Several tools exist for computing reachable sets of hybrid
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Several tools exist for computing reachable sets of hybrid
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systems, including CORA, Flow*, SpaceEx, and JuliaReach. The choice of tool
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systems, including CORA, Flow*, SpaceEx, and JuliaReach. The choice of tool
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@ -423,12 +419,7 @@ the time derivative of $B$ is non-negative. Geometrically, this means the
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vector field points inward or tangent to the boundary, never outward. If this
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vector field points inward or tangent to the boundary, never outward. If this
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condition holds, no trajectory starting inside $\mathcal{C}$ can ever leave.
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condition holds, no trajectory starting inside $\mathcal{C}$ can ever leave.
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Because the design of the discrete controller defines careful boundaries in
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The discrete controller design defines careful boundaries in continuous state space. Therefore, the barrier is known prior to designing the continuous controller. This eliminates the search for an appropriate barrier. It minimizes complication in validating stabilizing continuous control modes. The discrete specifications tell us what region must be invariant. The barrier certificate then confirms that the candidate controller achieves this invariance.
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continuous state space, the barrier is known prior to designing the continuous
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controller. This eliminates the search for an appropriate barrier and minimizes
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complication in validating stabilizing continuous control modes. The discrete
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specifications tell us what region must be invariant; the barrier certificate
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confirms that the candidate controller achieves this invariance.
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Finding barrier certificates can be formulated as a
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Finding barrier certificates can be formulated as a
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sum-of-squares (SOS) optimization problem for polynomial systems, or solved
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sum-of-squares (SOS) optimization problem for polynomial systems, or solved
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