Pseudorandom binary sequence

A very popular sequence of inputs is the pseudorandom binary sequence (PRBS). It is easy to generate and has some attractive statistical properties. See System Identification For Self-Adaptive Control, W. D. T. Davies, London, Wiley-Iflterscience, 1970. 

Fig. 2. Generation and properties of pseudorandom binary sequence waveforms.

Stochastic identification techniques, in principle, provide a more reliable method of determining the process transfer function. Most workers have used the Box and Jenkins [59] time-series analysis techniques to develop dynamic models. An introduction to these methods is given by Davies [60]. In stochastic identification, a low amplitude sequence (usually a pseudorandom binary sequence, PRBS) is used to perturb the setting of the manipulated variable. The sequence generally has an implementation period smaller than the process response time. By evaiuating the auto- and cross-correlations of the input series and the corresponding output data, a quantitative model can be constructed. The parameters of the model can be determined by using a least squares analysis on the input and output sequences. Because this identification technique can handle many more parameters than simple first-order plus dead-time models, the process and its related noise can be modeled more accurately. 

A binary pseudorandom, excitation is the simplest to generate signal [7]. It can be formed directly from a clock signal with frequency /elk using the sequence of k trigger circuits (oo to flk i) constituting a shift register... 

Such a solution similar to Fig. 33c has been in use in the Southampton University, UK [7]. Excitation signal used in [7] is a pseudorandom sequence of binary pulses - the maximum length sequence MLS, see Fig. 27, enabling to perform fast and wide band impedance spectroscopy. The response signal is processed using a... 

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