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Assessment and Future Directions of Nonlinear Model Predictive ...

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Optimal Online Control <strong>of</strong> Dynamical Systems Under Uncertainty 333In the control process under consideration the optimal value <strong>of</strong> the objectivefunction was equal to 0.1046290478. Figure 1 presents the estimates ˆα i (τ), ˆβ i (τ),i = 1, 4; t ∈ [0, 2]. Figure 2 shows the optimal control function u ∗ (t), t ∈ T ,<strong>and</strong> the projections on the phase planes xẋ <strong>and</strong> ϕ ˙ϕ <strong>of</strong> the corresponding optimaltrajectories.Fig. 1. Linear estimates ˆα i(τ), ˆβ i(τ), τ ∈ T h , i = 1, 4Fig. 2. Optimal control <strong>and</strong> projections <strong>of</strong> the optimal trajectoriesFig. 3. Two-mode algorithm: estimate ρ(t), t ∈ T h , <strong>and</strong> optimal trajectoriesTo estimate the delay s(τ) assume that σ is maximal time required to integrateprimal or adjoint equations on the whole interval T . We used methods from [9, 11]to perform online corrections <strong>of</strong> solutions <strong>of</strong> optimal control <strong>and</strong> observationproblems. The maximal length <strong>of</strong> the intervals, where differential equations wereintegrated, was l max =0.043t ∗ (4.3% <strong>of</strong> the control interval). If σ is such thatσl max

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