Có 20+ tài liệu thuộc chủ đề "hệ thống tuyến tính"
tailieu.vn Xem trực tuyến Tải xuống
Điều chỉnh là một khái niệm hẹp hơn của điều khiển. Cơ sở lí thuyết điều khiển tự động chỉ nghiên cứu các quá trình trong hệ thống điều chỉnh tự động.. Vì vậy hệ thống bù nhiễu còn được gọi là hệ thống điều khiển bất biến.. Trong kĩ thuật thường sử dụng phương thức điều khiển theo sai...
tailieu.vn Xem trực tuyến Tải xuống
Some central keywords of the book are listed in Table 1.1, and the figures. illustrated in Figure 1.1, give an idea of the relative activity in the different areas . Such a search gives a quick idea of the size of the areas. which is directly reflected in the. On some of the rows, the logical. Figure 1.2 reveals the,...
tailieu.vn Xem trực tuyến Tải xuống
Change in the mean model. Change in the variance model. This chapter provides background information and problem descriptions of the applications treated in this book . Most of the applications include real data and many of them are used as case studies examined throughout the book with different algorithms . The fuel consumption application in Examples 1.1, 1.4 and 1.8...
tailieu.vn Xem trực tuyến Tải xuống
Stopping rules and the CUSUM test. For change detection, this will be labeled as a change in the mean model.. The segmentation problem is t o find both the number and locations of the change times in P. 0 In the statistical approaches, it will be assumed that the noise is white and Gaussian et E N(0, R. However, the...
tailieu.vn Xem trực tuyến Tải xuống
Off-line approaches. Off-line global search for optimum. Change point estimation. This chapter surveys off-line formulations of single and multiple change point estimation . This chapter is basically a projection of the more general results in Chapter 7 to the case of signal estimation . some dedicated algorithms for estimating one change point off- line that apply to the current case...
tailieu.vn Xem trực tuyến Tải xuống
G of the acoustic path from disturbance t o listener.. The parameter depen- dence comes from the fact that the regressor is a function of the noise. of the noise. This means that the model can explain roughly half of the energy in the signal.. (5.34) Hence, the estimate is modified in the direction of the negative gradient. Example 5.6...
tailieu.vn Xem trực tuyến Tải xuống
Change detection based on model validation aims at applying a consistency test in one of the following ways:. This may be obtained in one of the following ways:. 0 Q0 is recursively identified from past data, except for the ones in the sliding window. Let us denote the vector of L measurements in the sliding window by Y = (Y....
tailieu.vn Xem trực tuyến Tải xuống
is a good description of the observed signal yt. In this chapter, the measure- ments may be vector valued, and the nominal covariance matrix of the noise is Rt, and X ( i ) is a possibly unknown scaling, which is piecewise constant.. log det of the covariance matrix) and number of data N in each segment, as defined in...
tailieu.vn Xem trực tuyến Tải xuống
The Kalman filter. Kalman filter. The extended Kalman filter. Whiteness based change detection using the Kalman filter. The Kalman filter requires a state space model for describing the signal dynamics. Example 8.7 Target tracking: function of Kalman filter. Figure 8.l(a) illustrates how the Kalman filter makes use of the model.. For simplicity, assume that we have an estimate of the...
tailieu.vn Xem trực tuyến Tải xuống
Marginalization of the noise level. Derivation of the GLR test. LS-based derivation of the MLR test. This formulation of the change detection problem can be interpreted as an input observer or input estimator approach. It should be noted that v and Q both denote the magnitude of the additive change, but the former is seen as an input and the...
tailieu.vn Xem trực tuyến Tải xuống
10.A.Posterior distribution. 1O.A.l.Posterior distribution of the continuous state. The main purpose is to survey multiple model algorithms, and a secondary purpose is to overview and compare the state of the art in different application areas for reducing complexity, where similar algorithms have been developed independently.. Here St is a discrete parameter representing the mode of the system (linearized mode, faulty...
tailieu.vn Xem trực tuyến Tải xuống
The matrices Ai, Bi and vector G are chosen so that the norm of the linear transformation is small when there is no change/fault according to hypothesis Hi, and large when fault Hi has appeared. The distance measure becomes exactly ‘zero’ in the non-faulty case, and any deviation from zero is explained by modeling errors and unmodeled disturbances rather than...
tailieu.vn Xem trực tuyến Tải xuống
Monte Carlo simulations. It might also be the signal component st of the measurement yt = st +ut. The measurements zt consist of the measured outputs yt and, when appropriate, the inputs ut.. (12.2) Here and in the sequel, the super-index O means the true value. 0 A scalar measure of performance is often to prefer when evaluating dif- ferent...
tailieu.vn Xem trực tuyến Tải xuống
Example: derivation of the Kalman filter. The non-causal Wiener filter. The causal Wiener filter. The stationary Kalman smoother as a Wiener filter. 13.1 Proiections 453. 13.1 Proiections 455. The measurement update of the covariance matrix is similar. 13.2 Conditional exDectations 457. From (13.3) we get. 13.2 Conditional expectations 459. The derivation and interpretations of the Wiener filter follows Hayes (1996).....
tailieu.vn Xem trực tuyến Tải xuống
Practically , it is certainly one of the greater discoveries in the history of statistical estimation theory and possibly the greatest discovery in the twentieth century. The purpose of this book is to make you suf®ciently familiar with and pro®cient in the use of the Kalman. Some of the problems encountered in its use arise from the distinction between ®nite...
tailieu.vn Xem trực tuyến Tải xuống
The dependent variables of the differential equations become state variables of the dynamic system. They explicitly represent all the important characteristics of the dynamic system at any time.. This chapter will stick to just those concepts that are essential for that purpose, which is the development of the state- space representation for dynamic systems described by systems of linear differential...
tailieu.vn Xem trực tuyến Tải xuống
The results are models for deterministic mechanics, in which the state of every component of the system is represented and propagated explicitly.. Consequently, this other approach focuses on the ensemble statistical properties of the system and treats the underlying dynamics as a random process. The results are models for statistical mechanics, in which only the ensemble statistical properties of the...
tailieu.vn Xem trực tuyến Tải xuống
Prediction is dif®cultÐespecially of the future.. The objective will be to ®nd an estimate of the n state vector x k represented by x ^ k , a linear function of the measurements z i. Predictors use observations strictly prior to the time that the state of the dynamic system is to be estimated:. Filters use observations up to and...
tailieu.vn Xem trực tuyến Tải xuống
That is, the functional dependences of the measurement or state dynamics on the system state are nonlinear, but approximately linear for small perturbations in the values of the state variables.. Methods of linear estimation theory can be applied to such nonlinear problems by linear approximation of the effects of small perturbations in the state of the nonlinear system from a...
tailieu.vn Xem trực tuyến Tải xuống
Unchecked error propagation in the solution of the Riccati equation is a major cause of degradation in ®lter performance.. The operation of the Kalman ®lter can be speeded up, if necessary, by performing some operations in parallel. 2 The mantissa is the part of the binary representation starting with the leading nonzero bit. Entering ``-log2(eps)''should return the number of bits...