Simultaneous bioelectricity generation and water desalination using Oscillatoria sp. as biocatalyst in photosynthetic microbial desalination cell.

Globally, the scarcity of drinking water has triggered the researchers towards the development of desalination techniques to turn up saline water into potable. Microbial Desalination Cell (MDC) is a novel green technology that shows potential approach for desalination along with electricity generation and wastewater treatment. However, the expensive catholyte/catalyst in the cathode side has limited the MDC for real time application. Hence, the main objective of this work was to investigate the electricity generation during dairy wastewater treatment and desalination efficiency using biocathode (Oscillatoria sp.) in the MDC. The results showed that the maximum open circuit voltage of 652 ± 10 mV, COD removal efficiency of 80.2 ± 0.5% and desalination efficiency of 65.8 ± 0.5%, were achieved respectively. The effect of saline water concentration was investigated and the performance of MDC was compared with real (sea) water. This study demonstrated that Oscillatoria sp. could be used as a potential biocatalyst in the cathode chamber for enhancing salinity removal along with electricity generation and wastewater treatment in the MDC.

Influence of Nickel molybdate nanocatalyst for enhancing biohydrogen production in microbial electrolysis cell utilizing sugar industrial effluent.

Biohydrogen production in Microbial Electrolysis Cell (MEC) had inspired the researchers to overcome the challenges associated towards sustainability. Despite microbial community and various substrates, economical cathode catalyst development is most significant factor for enhancing hydrogen production in the MEC. Hence, in this study, the performance of MEC was investigated with a sugar industry effluent (COD 4200 ± 20 mg/L) with graphite anode and modified Nickel foam (NF) cathode. Nickel molybdate (NiMoO4) coated NF achieved a higher hydrogen production rate 0.12 ± 0.01 L.L-1D-1 as compared to control under favorable conditions. Electrochemical characterizations demonstrated that the improved catalytic activity of novel nanocatalyst with lower impedance favoring faster hydrogen evolution kinetics. The MEC with the novel catalyst performed with 58.2% coloumbic efficiency, 20.36% cathodic hydrogen recovery, 11.96% overall hydrogen recovery and 54.38% COD removal efficiency for a 250 mL substrate during 5 days' batch cycle. Hence, the potentiality of modified cathode was established with the real time industrial effluent highlighting the waste to wealth bio-electrochemical technology.

Optimal controller synthesis for second order time delay systems with at least one RHP pole.

An optimal H2 minimization framework is proposed in this paper for devising a controller of PID in nature, based on a refined IMC filter configuration. The tuning strategy is for controlling time delay system with at least one pole which falls on the right half of the s-plane. An underdamped model based filter is used in place of the unity damping ratio (critically damped) filter available in the literature to improve the reset action. The method has a single adjustable closed loop tuning parameter. Guidelines have been provided for choosing the pertinent tuning parameter based on the sensitivity function. Simulation work has been executed on diverse unstable models to support the advantages of the proposed scheme. The proposed controller yields improved performances over other recently reported tuning techniques in the literature. Experimental implementation is carried out on an inverted pendulum for demonstrating the practical applicability of the present method. The efficacy of the intended controller design is quantitatively analyzed using the time integral performance index.

Enhanced IMC based PID controller design for non-minimum phase (NMP) integrating processes with time delays.

Internal model control (IMC) with optimal H2 minimization framework is proposed in this paper for design of proportional-integral-derivative (PID) controllers. The controller design is addressed for integrating and double integrating time delay processes with right half plane (RHP) zeros. Blaschke product is used to derive the optimal controller. There is a single adjustable closed loop tuning parameter for controller design. Systematic guidelines are provided for selection of this tuning parameter based on maximum sensitivity. Simulation studies have been carried out on various integrating time delay processes to show the advantages of the proposed method. The proposed controller provides enhanced closed loop performances when compared to recently reported methods in the literature. Quantitative comparative analysis has been carried out using the performance indices, Integral Absolute Error (IAE) and Total Variation (TV).

Bioelectricity production from microbial fuel cell using mixed bacterial culture isolated from distillery wastewater.

The effect of various system parameters such as wastewater Chemical Oxygen Demand (COD) concentration, pH, conductivity, membrane size and thickness on efficient energy production using mixed isolated culture from the distillery wastewater in the MFC was studied. The power density increased with increase in the anolyte pH from 6 to 8. The peak power density and COD removal efficiency was observed as 63.8±0.65 mW/m(2) and 63.5±1.5% at pH 8, respectively. The MFC performance increased with increasing COD concentration (800-3200 mg/l), conductivity (1.1-9.7 mS/cm) and membrane area (8-24 cm(2)). The MFC operating with wastewater COD concentration of 3200 mg/l and its conductivity of 9.7 mS/cm produced the highest power density of 202±6 mW/m(2) with a corresponding current density of 412±12 mA/m(2). The results showed that the efficient electricity generation and simultaneous treatment of distillery wastewater can be attained in the MFC.

GOBF-ARMA based model predictive control for an ideal reactive distillation column.

This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC.

Energy efficient model based algorithm for control of building HVAC systems.

Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly.

Soft sensor based composition estimation and controller design for an ideal reactive distillation column.

In this research work, the authors have presented the design and implementation of a recurrent neural network (RNN) based inferential state estimation scheme for an ideal reactive distillation column. Decentralized PI controllers are designed and implemented. The reactive distillation process is controlled by controlling the composition which has been estimated from the available temperature measurements using a type of RNN called Time Delayed Neural Network (TDNN). The performance of the RNN based state estimation scheme under both open loop and closed loop have been compared with a standard Extended Kalman filter (EKF) and a Feed forward Neural Network (FNN). The online training/correction has been done for both RNN and FNN schemes for every ten minutes whenever new un-trained measurements are available from a conventional composition analyzer. The performance of RNN shows better state estimation capability as compared to other state estimation schemes in terms of qualitative and quantitative performance indices.

Performance assessment of PID and IMC tuning methods for a mixing process with time delay.

A flow process with time delay has been considered for modeling and control. A dilute solution of sodium chloride is used as tracer and an online conductivity measurement unit as sensor and recorder. The objective of the current study is to design control algorithms and present corresponding robust control analysis for the process. The control methodologies considered are (i) conventional PID control and (ii) internal model control (IMC). The control structures are comparatively analyzed using standard robustness measures for stability and performance. Of the two control algorithms, conventional PID and IMC, IMC exhibits faster settling time, no overshoot, better set-point tracking and disturbance rejection, and good robust performance than the PID control scheme.

Modeling and optimisation of D-fructose isomerisation using a fluorosensor.

D-Fructose was isomerized in a 1.5 litre Tokyo Rikakikai fermentor using Sweetzyme T at 40 degree Celsius at five different feed concentrations ranging from 0.01 to 1.0 M. The stirrer speed was maintained at 100 rpm. The progress of the reaction was monitored using a Dr. Ingold Fluorosensor. The fluorescence voltage was recorded as a function of time and the maximum noted. It was observed that the maximum fluorescence voltage increased as concentration increased from 0.01 to 0.04 and thereafter decreased indicating an optimum of 0.04 M. The fluorescence voltage time data fitted a first order model with an error of less than 0.8 percent.