Improving efficiency of pH control by balance-based adaptive control application

Abstract

This paper deals with the efficient control of the pH process. Considering the PI + gain scheduling (PI+GS) controller as the benchmark and its control performance as the base, we investigate experimentally the overall improvement in the control performance obtained by the application of the Balance-Based Adaptive Controller (B-BAC), which requires only the measurement data of the flow rates and pH values. The improvement of the control efficiency is investigated not only in terms of the controlled variable performance but also in terms of the manipulated variable performance considered as the considerable control cost. The application of the B-BAController can ensure lower controlled pH variability at the price of the control effort similar to the PI+GS approach and thus it can improve the overall efficiency of pH control. The second important contribution is the experimental validation of the very simple and intuitive tuning procedure for the B-BAController.

Geometrical scaling in charm structure function ratios

“…The parameters (σ 0 , x 0 ) were obtained from a fit to the HERA data [21][22]. We take λ c = 0.558±0.038, which is an optimal value of the parameter λ in charm production for m c = 1.3 GeV (as accompanied with statistical error ) [13]. We set the running coupling constant to Λ = 0.224 GeV , and the theoretical uncertainties in our result are based on the renormalization scales µ 2 = 4m 2 c and µ 2 = 4m 2 c + Q 2 .…”

“…where f is a universal, dimensionless function of the scaling variable [13]. The constant Q 2 0 sets the dimension, and it can be extracted from the data.…”

“…To determine this function, one should know the cross section σ dp (u) describing the interaction of the qq color dipole with the proton and doing the respective integration for the σ γ * p . Because σ dp is not calculable, some models [13], such as 1 − exp(−u 2 ), are used, where those values in this model are compared with the experimental data. In contrast, there exist some parameterizations of F cc 2 whereby the function f can be calculated by dividing the parameterization F cc 2 by Q 2 [12].…”

“…where τ = Q 2 Q 2 s is called a scaling variable [13]. This scaling is a border between dense and dilute gluonic systems.…”

“…In charm production, geometrical scaling is expected to be violated due to the large quark mass m c ≃1.3GeV . Therefore, the scaling variable for charm production can be obtained by [13]…”