Baran Özyurt

Self-Tuning GMV Control of Glucose Concentration in Fed-Batch Baker’s Yeast Production

A detailed system identification procedure and self-tuning generalized minimum variance (STGMV) control of glucose concentration during the aerobic fed-batch yeast growth were realized. In order to determine the best values of the forgetting factor (λ), initial value of the covariance matrix (α), and order of the Auto-Regressive Moving Average with eXogenous (ARMAX) model (na, nb), transient response data obtained from the real process wereutilized. Glucose flow rate was adjusted according to the STGMV control algorithm coded in Visual Basic in an online computer connected to the system. Conventional PID algorithm was also implemented for the control of the glucose concentration in aerobic fed-batch yeast cultivation. Controller performances were examined by evaluating the integrals of squared errors (ISEs) at constant and random set point profiles. Also, batch cultivation was performed, and microorganism concentration at the end of the batch run was compared with the fed-batch cultivation case. From the system identification step, the best parameter estimation was accomplished with the values λ = 0.9, α = 1,000 and na = 3, nb = 2. Theoretical control studies show that the STGMV control system was successful at both constant and random glucose concentration set profiles. In addition, random effects given to the set point, STGMV control algorithm were performed successfully in experimental study.

Biological hydrogen production: effects of inoculation and production media

In this work inoculation media are selected as potato, glycerine and milk to investigate the best storage condition that is important to maintain microorganism activity and stable hydrogen production performance. Cheese whey, potato and enriched potato (with additional glucose and CaCO3) are used as the production media and their hydrogen production results are compared in order to determine the best biohydrogen production media. Batch growth of anaerobic Clostridium butyricum for biohydrogen production is performed in 500 ml screw-capped bottles at 28°C. It is noted that both the inoculation and the production media are highly effective on hydrogen production. Results show that the highest hydrogen production yield is obtained as 50.50 ml H2/g COD using milk as inoculation medium and enriched potato as production medium. Another important production factor is the production rate and when the results of three different inoculation media are compared for different production media, milk inoculation and enriched potato production media give the highest results as 41.9291 mL/L.h.

Application of response surface methodology as a New PID tuning method in an electrocoagulation process control case

In this work the application of response surface methodology (RSM) to proportional-integral-derivative (PID) controller parameter tuning for electrocoagulation (EC) treatment of pulp and paper mill wastewater was researched. Dynamic data for two controlled variables (pH and electrical conductivity) were obtained under pseudo random binary sequence (PRBS) input signals applied to manipulated variables (acid and supporting electrolyte flow rates). Third order plus time delay model parameters were evaluated through System Identification Toolbox™ in MATLAB®. Four level full factorial design was applied to form a design matrix for three controller tuning parameters as factors and to evaluate statistical analysis of the system in terms of integral of square error (ISE), integral of absolute error (IAE), integral of time square error (ITSE) and integral of time absolute error (ITAE) performance criteria as response. Numerical values of the responses for the runs in the design matrices were determined using closed-loop PID control system simulations designed in Simulink®. Optimum proportional gain, integral action and derivative action values for electrical conductivity control were found to be 1,500 s, 0 s and 16.4636 s respectively. Accordingly, the same optimization scheme was followed for pH control and optimum controller parameters were found to be -8.6970 s, 0.0211 s and 50 s, respectively. Theoretically optimized controller parameters were applied to batch experimental studies. Chemical oxygen demand (COD) removal efficiency and energy consumption of pulp and paper mill wastewater treatment by EC under controlled action of pH at 5.5 and electrical conductivity at 2.72 mS/cm was found to be 85% and 3.87 kWh/m3 respectively. Results showed that multi input-multi output (MIMO) control action increased removal efficiency of COD by 15.41% and reduced energy consumption by 6.52% in comparison with treatment under uncontrolled conditions.