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Weighting Pattern
A weighting pattern for a linear dynamical system describes the relationship between an input u and output y. Given the time-variant system described by : \dot(t) = A(t)x(t) + B(t)u(t) : y(t) = C(t)x(t), then the output can be written as : y(t) = y(t_0) + \int_^t T(t,\sigma)u(\sigma) d\sigma, where T(\cdot,\cdot) is the weighting pattern for the system. For such a system, the weighting pattern is T(t,\sigma) = C(t)\phi(t,\sigma)B(\sigma) such that \phi is the state transition matrix. The weighting pattern will determine a system, but if there exists a realization for this weighting pattern then there exist many that do so. Linear time invariant system In a LTI system then the weighting pattern is: ; Continuous : T(t,\sigma) = C e^ B where e^ is the matrix exponential In mathematics, the matrix exponential is a matrix function on square matrices analogous to the ordinary exponential function. It is used to solve systems of linear differential equations. In the theory of Lie grou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Dynamical System
Linear dynamical systems are dynamical systems whose evaluation functions are linear. While dynamical systems, in general, do not have closed-form solutions, linear dynamical systems can be solved exactly, and they have a rich set of mathematical properties. Linear systems can also be used to understand the qualitative behavior of general dynamical systems, by calculating the equilibrium points of the system and approximating it as a linear system around each such point. Introduction In a linear dynamical system, the variation of a state vector (an N-dimensional vector denoted \mathbf) equals a constant matrix (denoted \mathbf) multiplied by \mathbf. This variation can take two forms: either as a flow, in which \mathbf varies continuously with time : \frac \mathbf(t) = \mathbf \mathbf(t) or as a mapping, in which \mathbf varies in discrete steps : \mathbf_ = \mathbf \mathbf_ These equations are linear in the following sense: if \mathbf(t) and \mathbf(t) are two va ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Time-variant System
A time-variant system is a system whose output response depends on moment of observation as well as moment of input signal application. In other words, a time delay or time advance of input not only shifts the output signal in time but also changes other parameters and behavior. Time variant systems respond differently to the same input at different times. The opposite is true for time invariant systems (TIV). Overview There are many well developed techniques for dealing with the response of linear time invariant systems, such as Laplace and Fourier transforms. However, these techniques are not strictly valid for time-varying systems. A system undergoing slow time variation in comparison to its time constants can usually be considered to be time invariant: they are close to time invariant on a small scale. An example of this is the aging and wear of electronic components, which happens on a scale of years, and thus does not result in any behaviour qualitatively different from ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
State Transition Matrix
In control theory, the state-transition matrix is a matrix whose product with the state vector x at an initial time t_0 gives x at a later time t. The state-transition matrix can be used to obtain the general solution of linear dynamical systems. Linear systems solutions The state-transition matrix is used to find the solution to a general state-space representation of a linear system in the following form : \dot(t) = \mathbf(t) \mathbf(t) + \mathbf(t) \mathbf(t) , \;\mathbf(t_0) = \mathbf_0 , where \mathbf(t) are the states of the system, \mathbf(t) is the input signal, \mathbf(t) and \mathbf(t) are matrix functions, and \mathbf_0 is the initial condition at t_0. Using the state-transition matrix \mathbf(t, \tau), the solution is given by: : \mathbf(t)= \mathbf (t, t_0)\mathbf(t_0)+\int_^t \mathbf(t, \tau)\mathbf(\tau)\mathbf(\tau)d\tau The first term is known as the zero-input response and represents how the system's state would evolve in the absence of any input. The sec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Realization (systems)
In systems theory, a realization of a state space model is an implementation of a given input-output behavior. That is, given an input-output relationship, a realization is a quadruple of ( time-varying) matrices (t),B(t),C(t),D(t)/math> such that : \dot(t) = A(t) \mathbf(t) + B(t) \mathbf(t) : \mathbf(t) = C(t) \mathbf(t) + D(t) \mathbf(t) with (u(t),y(t)) describing the input and output of the system at time t. LTI System For a linear time-invariant system specified by a transfer matrix, H(s) , a realization is any quadruple of matrices (A,B,C,D) such that H(s) = C(sI-A)^B+D. Canonical realizations Any given transfer function which is strictly proper can easily be transferred into state-space by the following approach (this example is for a 4-dimensional, single-input, single-output system)): Given a transfer function, expand it to reveal all coefficients in both the numerator and denominator. This should result in the following form: : H(s) = \frac. The coefficients ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
LTI System
In system analysis, among other fields of study, a linear time-invariant (LTI) system is a system that produces an output signal from any input signal subject to the constraints of linearity and time-invariance; these terms are briefly defined below. These properties apply (exactly or approximately) to many important physical systems, in which case the response of the system to an arbitrary input can be found directly using convolution: where is called the system's impulse response and ∗ represents convolution (not to be confused with multiplication, as is frequently employed by the symbol in computer languages). What's more, there are systematic methods for solving any such system (determining ), whereas systems not meeting both properties are generally more difficult (or impossible) to solve analytically. A good example of an LTI system is any electrical circuit consisting of resistors, capacitors, inductors and linear amplifiers. Linear time-invariant system theory is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Matrix Exponential
In mathematics, the matrix exponential is a matrix function on square matrices analogous to the ordinary exponential function. It is used to solve systems of linear differential equations. In the theory of Lie groups, the matrix exponential gives the exponential map between a matrix Lie algebra and the corresponding Lie group. Let be an real or complex matrix. The exponential of , denoted by or , is the matrix given by the power series e^X = \sum_^\infty \frac X^k where X^0 is defined to be the identity matrix I with the same dimensions as X. The above series always converges, so the exponential of is well-defined. If is a 1×1 matrix the matrix exponential of is a 1×1 matrix whose single element is the ordinary exponential of the single element of . Properties Elementary properties Let and be complex matrices and let and be arbitrary complex numbers. We denote the identity matrix by and the zero matrix by 0. The matrix exponential satisfies the following ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
