Linear Systems of Differential Equations with Variable Coefficients
A normal linear system of differential equations with variable coefficients can be written as
where \({{x_i}\left( t \right)}\) are unknown functions, which are continuous and differentiable on an interval \(\left[ {a,b} \right].\) The coefficients \({{a_{ij}}\left( t \right)}\) and the free terms \({f_i}\left( t \right)\) are continuous functions on the interval \(\left[ {a,b} \right].\)
Using vector-matrix notation, this system of equations can be written as
where
In the general case, the matrix \(A\left( t \right)\) and the vector functions \({\mathbf{X}}\left( t \right),\) \({\mathbf{f}}\left( t \right)\) can take both real and complex values.
The corresponding homogeneous system with variable coefficients in vector form is given by
Fundamental System of Solutions and Fundamental Matrix
The vector functions \({\mathbf{x}_1}\left( t \right),{\mathbf{x}_2}\left( t \right), \ldots ,{\mathbf{x}_n}\left( t \right)\) are linearly dependent on the interval \(\left[ {a,b} \right],\) if there are numbers \({c_1},{c_2}, \ldots ,{c_n},\) not all zero, such that the following identity holds:
If this identity is satisfied only if
the vector functions \({\mathbf{x}_i}\left( t \right)\) are called linearly independent on the given interval.
Any system of \(n\) linearly independent solutions \({\mathbf{x}_1}\left( t \right),\) \({\mathbf{x}_2}\left( t \right), \ldots ,\) \({\mathbf{x}_n}\left( t \right)\) is called a fundamental system of solutions.
A square matrix \(\Phi\left( t \right)\) whose columns are formed by linearly independent solutions \({\mathbf{x}_1}\left( t \right),{\mathbf{x}_2}\left( t \right), \ldots ,{\mathbf{x}_n}\left( t \right),\) is called the fundamental matrix of the system of equations. It has the following form:
where \({{x_{ij}}\left( t \right)}\) are the coordinates of the linearly independent vector solutions \({\mathbf{x}_1}\left( t \right),\) \({\mathbf{x}_2}\left( t \right), \ldots ,\) \({\mathbf{x}_n}\left( t \right).\)
Note that the fundamental matrix \(\Phi \left( t \right)\) is nonsingular, i.e. there always exists the inverse matrix \({\Phi ^{ - 1}}\left( t \right).\) Since the fundamental matrix has \(n\) linearly independent solutions, after its substitution into the homogeneous system we obtain the identity
We multiply this equation on the right by the inverse function \({\Phi ^{ - 1}}\left( t \right):\)
The resulting relation uniquely defines a homogeneous system of equations, given the fundamental matrix.
The general solution of the homogeneous system is expressed in terms of the fundamental matrix in the form
where \(\mathbf{C}\) is an \(n\)-dimensional vector consisting of arbitrary numbers.
Let us mention an interesting special case of homogeneous systems. It turns out that if the product of the matrix \(A\left( t \right)\) and the integral of this matrix is commutative, that is
the fundamental matrix \(\Phi\left( t \right)\) for such a system of equations is given by
Such property is satisfied for symmetric matrices and, in particular, for diagonal matrices.
Wronskian and Liouville's Formula
The determinant of the fundamental matrix \(\Phi\left( t \right)\) is called the Wronskian of the system of solutions \({\mathbf{x}_1}\left( t \right),\) \({\mathbf{x}_2}\left( t \right), \ldots ,\) \({\mathbf{x}_n}\left( t \right):\)
The Wronskian is useful to check the linear independence of solutions. The following rules apply:
- The solutions \({\mathbf{x}_1}\left( t \right),\) \({\mathbf{x}_2}\left( t \right), \ldots ,\) \({\mathbf{x}_n}\left( t \right)\) of the homogeneous system form a fundamental system if and only if the corresponding Wronskian is not zero at any point \(t\) of the interval \(\left[ {a,b} \right].\)
- The solutions \({\mathbf{x}_1}\left( t \right),\) \({\mathbf{x}_2}\left( t \right), \ldots ,\) \({\mathbf{x}_n}\left( t \right)\) are linearly dependent on the interval \(\left[ {a,b} \right]\) if and only if the Wronskian is identically zero on this interval.
The Wronskian of the solutions \({\mathbf{x}_1}\left( t \right),\) \({\mathbf{x}_2}\left( t \right), \ldots ,\) \({\mathbf{x}_n}\left( t \right)\) is given by Liouville's formula:
where \({\text{tr}\left( {A\left( \tau \right)} \right)}\) is the trace of the matrix \({A\left( \tau \right)},\) i.e. the sum of all diagonal elements:
Liouville's formula can be used to construct the general solution of the homogeneous system if a particular solution is known.
Method of Variation of Constants (Lagrange Method)
Now we consider the nonhomogeneous system that can be written in vector-matrix form as
The general solution of such a system is the sum of the general solution \({\mathbf{X}_0}\left( t \right)\) of the corresponding homogeneous system and a particular solution \({\mathbf{X}_1}\left( t \right)\) of the nonhomogeneous system, that is
where \(\Phi \left( t \right)\) is a fundamental matrix, \(\mathbf{C}\) is an arbitrary vector.
The most common method for solving the nonhomogeneous systems is the method of variation of constants (Lagrange method). With this method, instead of the constant vector \(\mathbf{C}\) we consider the vector \(\mathbf{C}\left( t \right)\) whose components are continuously differentiable functions of the independent variable \(t,\) that is we assume
Substituting this into the nonhomogeneous system, we find the unknown vector \(\mathbf{C}\left( t \right):\)
Given that the matrix \(\Phi \left( t \right)\) is nonsingular, we multiply this equation on the left by \({\Phi^{ - 1}}\left( t \right):\)
After integration we obtain the vector \(\mathbf{C}\left( t \right).\)