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Ut for mean and covariance propagation a actual b first order linearization ekf c ut
UT for mean and covariance propagation a) actual, b) first-order linearization (EKF) c) UT
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Unmodified filter solution generates an estimate that converges to the true equivariant errorstate e
Optimal adaptive robust H∞ H2 sliding mode
Comparison between EKF and UKF The first part shows the actual nonlinear model
Optimal adaptive robust H∞ H2 sliding mode
Lyapunov theory and contraction theory
Optimal adaptive robust H∞ H2 sliding mode
Unscented Kalman Filter (UKF)
Electrical
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General PID controller based control system
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Convex hull
Optimal adaptive robust H∞ H2 sliding mode
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Optimal adaptive robust H∞ H2 sliding mode
Illustration of set-intersection-based outer bound
Optimal adaptive robust H∞ H2 sliding mode
Convex sets and concave sets
Optimal adaptive robust H∞ H2 sliding mode
if vol(Ω∗) ≤ ϵ for Ω∗ of Ω , then ∃ T ≥ 0 so that for any x0 ∈ D the solution stays in the domain D
Optimal adaptive robust H∞ H2 sliding mode
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Contraction of the distance induced The Finsler-Lyapunov function assigns a positive value to each
Optimal adaptive robust H∞ H2 sliding mode
