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Chapter 4. Explicit/Multi-Parametric MPC Control of PSA Systems 100 99.995 99.99 99.985 99.98 88 86 84 82 80 78 500 1000 1500 2000 2500 3000 3500 4000 Output Response 500 1000 1500 2000 2500 Number of Cycles 3000 3500 4000 Input Pulse Signal, Switching Time = 79 Cycles Figure 4.9: PSA purity response to adsorption time pulse with switching time of 79 cycles cess industry due to their inherent simplicity, and ease of use in complex plant environment, even better reduced models can be obtained when the system is excited persistently [152, 88] over a large frequency band (of interest). Random pulsed inputs like filtered white noise, PRBS, and generalized binary noise (GBN) [152, 182] are ideal from this perspective, and have been used by industry and academia in the past. Keeping this in mind, the inbuilt random number genera- tor rand in MATLAB (2007b, The MathWorks) is employed to design random pulse signals, while taking additional considerations for the proper selection of two critical signal properties, 1. The maximum change to be allowed in signal amplitude from its previ- ous value. A very large change can perturb the PSA system beyond the scope of fitting a single linear model. On the other hand, small changes do not disturb the system sufficiently to reveal its complete dynamic nature, 82 Adsorption Time, Sec Purity, %PDF Image | Operation and Control of Pressure Swing Adsorption Systems
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