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Below we present a short overview of how the theory discussed in the previous sections applies to constrained mechanical systems and variational integration of such systems.

2.5.1 Lagrangian and Hamiltonian descriptions of constrained systems

Suppose we have a Lagrangian system with a configuration manifold Q and a regular La- grangian LT Q Ð→R, but we restrict the allowable configurations of the system to the

submanifoldN =g−1(0) ⊂Q, where gQÐ→

Rd is theconstraint function and we assume 0

is a regular value ofg(so thatN is indeed a submanifold; see [38]). Note that, ifiN Ð→Q

is the inclusion map, then T iT N Ð→T Qprovides a canonical way to embed T N in T Q, and T N can be regarded as a submanifold of T Q. In fact, in a local bundle chart on T Q

we have the characterization

T N = {(q,q˙) ∈T Qg(q) =0 and Dg(q)q˙=0}, (2.5.1) whereDg(q) denotes the Jacobi matrix of the (local representative of) constraint function

g(q). We can therefore consider the restricted Lagrangian system with the configuration manifoldN and the Lagrangian LN =LT N, and the theory presented in Section 2.3 can be

directly applied. However, it is often more elegant and convenient to consider this restricted system as a constrained version of the larger system defined onQ. It is particularly useful in numerical computations when Q has a vector space structure, which is easier to handle than the possibly nonlinear structure of the constraint submanifoldN.

It can be shown that ifLis regular, so isLN (see [41]). Therefore, T N can be endowed with the Lagrangian symplectic form ΩLN, as explained in Section 2.3, and this form is

preserved by the flow of the Lagrangian vector field associated withLN. It can be further shown that this symplectic structure onT N is compatible with the symplectic structure on

T Q, that is, ΩLN = (T i)∗ΩL, where ΩL is the Lagrangian form on T Q.

is defined on the set of all smooth curves C(Q) = {q∶ [a, b] Ð→Q}, that is,S ∶ C(Q) Ð→R.

The action functional SN ∶ C(N) Ð→ R for the Lagrangian LN is given by an analogous

formula. SinceNQandT NT Qare submanifolds, we haveSN =S∣C(N). The dynamics

of the constrained system is given by Hamilton’s principle, i.e., extremizingSN. To consider this dynamics in the embedding space, we further introduce the augmented configuration manifold Q×Rd and the augmented LagrangianLCT(Q×Rd) Ð→R defined by

LC(q, λ,q,˙ λ˙) =L(q,q˙) − ⟨λ, g(q)⟩, (2.5.2)

where λ ∈ Rd denotes the vector of Lagrange multipliers and ⟨., .⟩ is the standard scalar

product onRd. The corresponding augmented action functional SC ∶ C(Q) × C(Rd) Ð→Ris

given by SC[q(t), λ(t)] = ∫ b a LC(q(t), λ(t), ˙ q(t)˙(t))dt=S[q(t)] − ∫ b aλ(t), g(q(t))⟩dt. (2.5.3) The relation between the dynamics of the restricted system onN and the augmented system on Q×Rd is given by the following theorem (see [38]).

Theorem 2.5.1 (Lagrange multiplier theorem). The following statements are equiva- lent:

1. The curve q∶RÐ→NQis an extremum of SN;

2. The pair of curves q∶ [a, b] Ð→Q andλ∶ [a, b] Ð→Rd is an extremum of SC.

The curves extremizing the augmented action functional SC satisfy the Euler-Lagrange

equations associated withLC, the so-called constrained Euler-Lagrange equations,

∂L ∂qµd dt ∂L ∂q˙µ = ⟨λ, ∂g ∂qµ, g(q) =0. (2.5.4)

Deriving the equations of motion for constrained Hamiltonian systems is a little more cumbersome. Suppose we have a Hamiltonian system with the HamiltonianHTQÐ→

but we restrict the dynamics to the constraint submanifold N =g−1(0) ⊂Q as before. The

main complication is the fact that there is no canonical way of embedding TN in TQ,

and it is not obvious how to define an appropriate Hamiltonian HN on TN. However,

if the Hamiltonian H is hyperregular, that is, there exists a corresponding hyperregular Lagrangian L on T Q, as in Theorem 2.3.3, then one can realize TN as a symplectic

submanifold of TQ by defining the embeddingηTNÐ→TQasη=

FLT i○ (FLN)−1.

Using canonical coordinates on TQ, we have the following characterization

η(T

N) = {(q, p) ∈T

Qg(q) =0 andDg(q)∂H

∂p =0}. (2.5.5)

It is straightforward to show that the canonical symplectic form ΩN on TN is then com-

patible with the canonical symplectic form Ω on TQ

, that is, ΩN =η

Ω. We can further take HN =Hη. The Hamiltonian equations onTN will be defined by (2.1.4), and the

theory discussed in Section 2.1 directly applies. However, it is again useful to consider the dynamics of this constrained system in the embedding space. We have the natural embed- ding T ηT TN Ð→T TQ, so the Hamiltonian vector field ZN on TN can be regarded

as a vector field on η(TN). This leads to the following constrained equations on motion

on TQ: ˙ = ∂H ∂pµ, ˙ = −∂H ∂qµ− ⟨λ, ∂g ∂qµ, g(q) =0, (2.5.6)

where λ again denotes Lagrange multipliers. If the Lagrangian L is hyperregular, then (2.5.6) and (2.5.4) are equivalent, as in Theorem 2.3.3.

For more information on the geometry of constrained Lagrangian and Hamiltonian sys- tems we refer the reader to [38].

2.5.2 Variational integrators for constrained systems

Variational integration of constrained Lagrangian systems follows the main ideas presented in Section 2.4. We start with a regular discrete Lagrangian LdQ×QÐ→R. The discrete

dynamics is restricted to the constraint submanifold N×NQ×Q, whereN =g−1(0) ⊂Q

as before. We consider the augmented discrete state space (Q×Rd) × (Q×Rd) and the

augmented discrete LagrangianLCd ∶ (Q×Rd) × (Q×Rd) Ð→R,

LCd(q, λ,q,¯λ¯) =Ld(q,q¯) − ⟨λ, g(q)⟩. (2.5.7)

The discrete Euler-Lagrange equations (2.4.2) forLCd yield

D2Ld(qk−1, qk) +D1Ld(qk, qk+1) =Dg(qk) Tλ

k,

g(qk+1) =0, (2.5.8)

whereDgdenotes the Jacobi matrix of the constraint functiong, andλkdenotes the column

vector of Lagrange multipliers. If qk−1, qk are known, then (2.5.8) can be solved for qk+1

and λk.

The discrete Lagrangian Ld is chosen to approximate the exact discrete Lagrangian

for L. However, the exact discrete Lagrangian for a constrained system is not simply the standard exact discrete Lagrangian (2.4.9) restricted to the constraint submanifoldN×N, as that would be the action along an unconstrained trajectory. Instead, the constrained exact discrete LagrangianLN,EdN×N Ð→Ris defined by

LN,Ed (q,q¯) = ∫

h

0 L

N(q

E(t),q˙E(t))dt, (2.5.9)

where qE(t) is the solution to the constrained Euler-Lagrange equations (2.5.4) satisfying the boundary conditionsqE(0) =q and qE(h) =q¯.

Lobatto IIIA-IIIB pair. Higher-order variational integrators for constrained systems can be constructed as in Section 2.4.3: a variational Runge-Kutta method for a constrained Lagrangian system described by a regular Lagrangian L is equivalent to a symplectic par- titioned Runge-Kutta method applied to the constrained Hamiltonian equations (2.5.6).

Consider a Hamiltonian system HTQÐ→

Rwith the holonomic constraint gQÐ→ Rd, and two Runge-Kutta methods with the coefficientsaij,bi and ¯aij, ¯bi, respectively. An s-stageconstrained partitioned Runge-Kutta method is the map

Fhη(TN) ∋ (q, p) Ð→ (q,¯p¯) ∈η(TN), (2.5.10)

implicitly defined by the system of equations

˙ Qi=∂H ∂p(Qi, Pi), i=1, . . . , s, (2.5.11a) ˙ Pi= −∂H ∂q (Qi, Pi) −Dg(Qi) TΛi, i=1, . . . , s, (2.5.11b) 0=g(Qi), i=1, . . . , s, (2.5.11c) Qi=q+h sj=1 aijQ˙j, i=1, . . . , s, (2.5.11d) Pi=p+h sj=1 ¯ aijP˙j, i=1, . . . , s, (2.5.11e) ¯ q=q+h si=1 biQi,˙ (2.5.11f) ¯ p=p+h si=1 ¯biPi,˙ (2.5.11g) 0=Dg(q¯)∂H ∂p(q,¯ p¯), (2.5.11h)

where Qi, ˙Qi, Pi, ˙Pi and Λi are the internal stages of the method. However, this system

is not solvable for an arbitrary choice of the Runge-Kutta methods—note we have only (4s+2)n+sdunknowns (the internal stages and ¯q, ¯p), but(4s+2)n+(s+1)dequations. It can be shown that (2.5.11) is solvable if one chooses the coefficients of thes-stage Lobatto IIIA- IIIB method (see Section 2.2.2). For the Lobatto IIIA-IIIB schemes we have a1j =0 for j=1, . . . , s(cf. Table 2.4, Table 2.5, and Table 2.6), therefore in (2.5.11d) we have Q1=q.

If we assume g(q) = 0, i.e., the initial position is consistent with the constraint, then d

equations in (2.5.11c) for i=1 are automatically satisfied, and the whole system becomes solvable. Further, the Lobatto IIIA-IIIB schemes satisfy asj =bj for j = 1, . . . , s, so from (2.5.11d) and (2.5.11f) we have ¯q=Qs, and consequently, by (2.5.11c), we also haveg(q¯) =0,

i.e., the new position of the system is consistent with the constraint. This result, together with (2.5.11h), means that(q,¯ p¯) ∈η(TN), that is, (2.5.11) indeed defines an integrator for

the constrained Hamiltonian system. The following theorem can be proved (see [31], [23]). Theorem 2.5.2. The s-stage constrained Lobatto IIIA-IIIB scheme (2.5.11)is symplectic

onη(TN) and convergent of order 2s2.

If one defines the discrete Lagrangian LdQ×QÐ→Ras

Ld(q,q¯) =h s

i=1

biL(Qi,Q˙i), (2.5.12)

whereQiand ˙Qi satisfy (2.5.11), then the resulting variational integrator will be equivalent

to the constrained Lobatto IIIA-IIIB scheme, whereLandHare related as in Theorem 2.3.3. More information on variational and symplectic integration of constrained mechanical systems can be found in [23], [26], and [41].

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