Linear system of differential equations with periodic coefficients
A system of linear ordinary differential equations of the form
where is a real variable, and are complex-valued functions, and
The number is called the period of the coefficients of the system (1). It is convenient to write (1) as one vector equation
It is assumed that the functions are defined for and are measurable and Lebesgue integrable on , and that the equalities (2) are satisfied almost-everywhere, that is, . A solution of (3) is a vector function with absolutely-continuous components such that (3) is satisfied almost-everywhere. Suppose that and are an (arbitrarily) given number and vector. A solution satisfying the condition exists and is uniquely determined. A matrix of order with absolutely-continuous entries is called the matrizant (or evolution matrix, or transition matrix, or Cauchy matrix) of (3) if almost-everywhere on one has
and , where is the unit matrix. The transition matrix satisfies the relation
The matrix is called the monodromy matrix, and its eigen values are called the multipliers of (3). The equation
for the multipliers is called the characteristic equation of equation (3) (or of the system (1)). To every eigen vector of the monodromy matrix with multiplier corresponds a solution of (3) satisfying the condition
The Floquet–Lyapunov theorem holds: The transition matrix of (3) with -periodic matrix can be represented in the form
where is a constant matrix and is an absolutely-continuous matrix function, periodic with period , non-singular for all , and such that . Conversely, if and are matrices with the given properties, then the matrix (5) is the transition matrix of an equation (3) with -periodic matrix . The matrix , called the indicator matrix, and the matrix function in the representation (5) are not uniquely determined. In the case of real coefficients in (5), is a real matrix, but and are complex matrices, generally speaking. For this case there is a refinement of the Floquet–Lyapunov theorem: The transition matrix of (3) with -periodic real matrix can be represented in the form (5), where is a constant real matrix and is a real absolutely-continuous matrix function, non-singular for all , satisfying the relations
where is a real matrix such that
In particular, . Conversely, if , and are arbitrary matrices with the given properties, then (5) is the transition matrix of an equation (3) with a -periodic real matrix .
An immediate consequence of (5) is Floquet's theorem, which asserts that equation (3) has a fundamental system of solutions splitting into subsets, each of which has the form
where the are absolutely-continuous -periodic (generally speaking, complex-valued) vector functions. (The given subset of solutions corresponds to one -cell of the Jordan form of .) If all elementary divisors of are simple (in particular, if all roots of the characteristic equation (4) are simple), then there is a fundamental system of solutions of the form
Formula (5) implies that (3) is reducible (see Reducible linear system) to the equation
by means of the change of variable (Lyapunov's theorem).
Let be the multipliers of equation (3) and let be an arbitrary indicator matrix, that is,
The eigen values of are called the characteristic exponents (cf. Characteristic exponent) of (3). From (6) one obtains , . The characteristic exponent can be defined as the complex number for which (3) has a solution that is representable in the form
where is a -periodic vector-valued function. The main properties of the solutions in which one is usually interested in applications are determined by the characteristic exponents or multipliers of the given equation (see the Table).'
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In applications, the coefficients of (1) often depend on parameters; in the parameter space one must distinguish the domains at whose points the solutions of (1) have desired properties (usually these are the first four properties mentioned in the Table, or the fact that with given). These problems thus reduce to the calculation or estimation of the characteristic exponents (multipliers) of (1).
where and are a measurable -periodic matrix function and vector function, respectively, that are Lebesgue integrable on (, almost-everywhere), is called an "inhomogeneous linear ordinary differential equation with periodic coefficientsinhomogeneous linear ordinary differential equation with periodic coefficients" . If the corresponding homogeneous equation
does not have -periodic solutions, then (7) has a unique -periodic solution. It can be determined by the formula
where and is the transition matrix of the homogeneous equation (8), where , .
Suppose that (8) has linearly independent -periodic solutions . Then the adjoint equation
also has linearly independent -periodic solutions, . The inhomogeneous equation (7) has a -periodic solution if and only if that the orthogonality relations
hold. If so, an arbitrary -periodic solution of (7) has the form
where are arbitrary numbers and is a -periodic solution of (7). Under the additional conditions
the -periodic solution is determined uniquely; moreover, there is a constant , independent of , such that
Suppose one is given an equation
with a matrix coefficient that holomorphically depends on a complex "small" parameter :
Suppose that for the series
which guarantees the (componentwise) convergence of the series (11) for in the space . Then the transition matrix of (10) for fixed is an analytic function of for . Let be a constant matrix with eigen values , . Let be the multipliers of equation (10), . If is a multiplier of multiplicity , then
where are integers. If simple elementary divisors of the monodromy matrix correspond to this multiplier, or, in other words, if to each , , correspond simple elementary divisors of the matrix (for example, if all the numbers are distinct), then is called an -fold characteristic exponent (of equation (10) with ) of simple type. It turns out that the corresponding characteristic exponents of (10) with small can be very easily computed to a first approximation. Namely, let and be the corresponding normalized eigen vectors of the matrices and ;
be the Fourier series of , and let
where are the numbers from (12). Then for the corresponding characteristic exponents , , of (10), which become for , one has series expansions in fractional powers of , starting with terms of the first order:
Here the are the roots (written as many times as their multiplicity) of the equation
and are natural numbers equal to the multiplicities of the corresponding (, for ). If the root is simple, then and the corresponding function is analytic for . From (13) it follows that cases are possible in which the "unperturbed" (that is, with ) system is stable (all the are purely imaginary and simple elementary divisors correspond to them), but the "perturbed" system (small ) is unstable ( for at least one ). This phenomenon of stability loss for an arbitrary small periodic change of parameters (with time) is called parametric resonance. Similar but more complicated formulas hold for characteristic exponents of non-simple type.
Let be the distinct multipliers of equation (3) and let be their multiplicities, where . Suppose that the points on the complex -plane are surrounded by non-intersecting discs and that a cut, not intersecting these discs, is drawn from the point to the point . Suppose that with each multiplier is associated an arbitrary integer and that is the transition matrix of (10). The branches of the logarithm are determined by means of the cut. The matrix ( "matrix logarithmmatrix logarithm" ) can be defined by the formula
where is the circle . The set of numbers determines a branch of the matrix logarithm. Also, for small . Generally speaking, formula (14) for all possible does not cover all the values of the matrix logarithm, that is, all solutions of the equation . However, the solution given by (14) has the important property of holomorphy: The entries of the matrix in (14) are holomorphic functions of the entries of . For equation (10), formula (5) takes the form
where , . If is determined in accordance with (14), then
are series that converge for small . The main information about the behaviour of the solutions as which is usually of interest in applications is contained in the indicator matrix . Below a method for the asymptotic integration of (10) is given, that is, a method for successively determining the coefficients and in (16).
Suppose that in (11). Although , generally speaking there is no branch of the matrix logarithm such that the matrix is analytic for and . This branch of the logarithm will exist in the so-called non-resonance case, when among the eigen values of there are no numbers for which
( is an integer). In the resonance case (when such eigen values exist) equation (10) reduces by a suitable change of variable , where , to an analogous equation for which the non-resonance case holds. The matrix can be determined from the matrix .
In (16), in the non-resonance case , , and the matrices , , are found from the equation
after equating coefficients at the same powers of in this equation. To determine and one obtains a matrix equation of the form
where . The matrices and are found, and moreover uniquely (the non-resonance case), from (17) and the periodicity condition .
|||I.Z. Shtokalo, "Linear differential equations with variable coefficients: criteria of stability and unstability of their solutions" , Hindushtan Publ. Comp. (1961) (Translated from Russian)|
|||N.P. Erugin, "Linear systems of ordinary differential equations with periodic and quasi-periodic coefficients" , Acad. Press (1966) (Translated from Russian)|
|||V.A. Yakubovich, V.M. Starzhinskii, "Linear differential equations with periodic coefficients" , Wiley (1975) (Translated from Russian)|
|[a1]||R.W. Brockett, "Finite dimensional linear systems" , Wiley (1970)|
|[a2]||J.K. Hale, "Ordinary differential equations" , Wiley (1969)|
Linear system of differential equations with periodic coefficients. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Linear_system_of_differential_equations_with_periodic_coefficients&oldid=16408