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Constrained Optimal Control of Linear and Hybrid Systems by Francesco Borrelli

By Francesco Borrelli

Many useful regulate difficulties are ruled through features equivalent to nation, enter and operational constraints, alternations among diverse working regimes, and the interplay of continuous-time and discrete occasion platforms. at the present no technique is accessible to layout controllers in a scientific demeanour for such structures. This booklet introduces a brand new layout idea for controllers for such limited and switching dynamical platforms and ends up in algorithms that systematically remedy keep watch over synthesis difficulties. the 1st half is a self-contained creation to multiparametric programming, that is the most approach used to review and compute nation suggestions optimum keep watch over legislation. The book's major goal is to derive houses of the country suggestions answer, in addition to to procure algorithms to compute it successfully. the focal point is on restricted linear platforms and restricted linear hybrid platforms. The applicability of the idea is validated via experimental case reviews: a mechanical laboratory strategy and a traction keep watch over approach constructed together with the Ford Motor corporation in Michigan.

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Example text

19a) we obtain U P 0 D z q = . 18) one may choose any one of the dual optimizers y0∗ in order to characterize the value function. 24a) Dθ = r. 24b) We distinguish between two cases: Case 1. Matrix D is the null matrix and r is the null vector. Then we have a full-dimensional primal degenerate critical region CRA(x0 ) . Case 2. The rank of D is p > 0. Then, CRA(x0 ) has dimension n − p < n = dim(K). 1, we conclude that CRA(x0 ) is an (n − p)dimensional face of another critical region CRA for some combination A ⊃ A(x0 ).

Z¯dNi bi , that have already been explored in the region CRi . 3. For each CRi an integer feasible variable z¯dNi bi +1 ∈ / Zi such that there ˆ ∈ CRi for which Gz ≤ W + S x ˆ and c z < J¯i (ˆ x) where exists zc and x z = {zc , z¯dNi bi +1 }. That is, z¯dNi bi +1 is an integer variable that improves the current bound for at least one point of the current polyhedron. At step j = 0, set: N0 = 1, CR1 = K, Z1 = ∅, J¯1 = +∞, z¯d11 = z¯d . 5 Multiparametric Mixed-Integer Linear Programming J˜i (x) = 45 min c z z subj.

2 A Summary of the mp-QP Algorithm Based on the above discussion and results, the main steps of the off-line mpQP solver are outlined in the following algorithm. 34) 1 2 3 4 5 6 7 8 9 10 11 12 Let K ⊆ Rn be the set of parameters (states); execute partition(K); end. 9; For each new sub-region Ri, partition(Ri ); end procedure. 9 into polyhedral sets Ri , use the same method to partition each set Ri further, and so on. This can be represented 36 1 Multiparametric Programming: a Geometric Approach as a search tree, with a maximum depth equal to the number of combinations of active constraints (see Sect.

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