Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

Appendix F

MATLAB Toolboxes Used

Apart from the PRTools toolbox,¹ this book has used the following standard MATLAB toolboxes:

• Control System Toolbox

  This toolbox contains many functions and data structures for the modelling and design of control systems. However, the linear time invariant cases are emphasized. As such, the toolbox contains a number of functions that are of interest for state estimation. But, unfortunately, the scope of these functions is limited to the steady state case.

• Signal Processing Toolbox

  This toolbox is a collection of processing operations. Much attention is paid to the realization aspect of filters, i.e. how to build a filter with given properties, e.g. a given cut-off frequencies, constrained phase characteristics and so on. This aspect is of less importance for the design of state estimators. Nevertheless, the toolbox contains a number of functions that are of interest with respect to the scope of this book:

  • correlation and covariance estimation
  • spectral analysis, e.g. the periodogram
  • estimation of parameters of random processes, e.g. the AR coefficients based on, for instance, the Yule–Walker equations
  • some various tools, such as waveform generation and resampling functions.
• Optimization Toolbox

  This toolbox contains many functions for optimization problems including constrained or unconstrained, linear or nonlinear minimization. The toolbox also contains functions for curve fitting.

• Statistics Toolbox

  This toolbox includes functions for the following ...