A SURVEY ON CONTROL TECHNIQUES OF A BENCHMARKED CONTINUOUS STIRRED TANK REACTOR

The study carried out in this paper unveils a survey on issues related to modelling problems control strategies of a Continuous Stirred Tank Reactor (CSTR), a highly nonlinear plant containing numbers of stable and unstable operating points is considered. The issues discussed are categorised into regulation, feedback linearization, flatness, observation and estimation as well as challenges related to equilibrium points concerning CSTR. In this study, the limited capability of a conventional PID controller is discussed based on preliminary description and a dynamic modelling of the nonlinear plant. Moreover, the limitations of the conventional PID is illustrated through a simulation using nonlinear model of CSTR carried out under input constraint and the presence of bounded disturbances. The result shows that a fixed PID will not guarantee consistent performance throughout operating set points. The feedback linearization formalism is presented to prove that only regulation in the neighbourhood of operating point is possible. Non-minimum phase property exhibited by a CSTR is investigated as well. Flatness control is demonstrated as one of the possible linearization control technique achieving the objective of the trajectory trackin

Adaptive sampled-data tracking for input constrained exothermic chemical reaction models

We consider digital input-constrained adaptive output feedback control of a class of nonlinear systems which arise as models for controlled exothermic chemical reactors.Our objective is set-point control of the temperature of the reaction, with prespecified asymptotic tracking accuracy set by the designer. Our approach is based on. Our objective is set-point control of the temperature of the reaction, with prespecified asymptotic tracking accuracy set by the designer. Our approach is based on lamda-tracking controllers, but we introduce a piecewise constant sampled-data output feedback strategy with adapted sampling period. The approach does not require any knowledge of the systems parameters, does not invoke an internal model, is simple in its design, copes with noise corrupted output measurements, and requires only a feasibility assumption in terms of the reference temperature and the input constraints

Combined wet milling crystallisation methods for particle engineering

Recent advances in pharmaceutical manufacturing for consistent supply of medicines with the required physical properties has emphasised the need for robust crystallisation processes which is a critical separation and purification technique. Mechanical milling is employed post crystallisation as an offline unit operation usually in a separate dry solids processing facility for adjusting the particle size and shape attributes of crystalline products for downstream processing. An emerging and increasingly applied technology is high shear wet milling in crystalline slurries for inline size and shape modification during particle formation. This potentially avoids the need for multiple crystallisation trials and offline milling saving time, costs and powder handling. Similarly, sonication is a powerful particle engineering tool through immersing ultrasound probes directly in solution. This PhD project is focused on the investigation and process integration of wet milling and indirect ultrasound for enhancing crystallisation processes and engineering particle attributes. The experimental study combined a cooling and isothermal crystallisation (seeded & unseeded) process with wet milling and indirect sonication. Results from the combined method provides the ability to modify and selectively achieve a range of product outcomes including particle sizes with tight spans, equant shapes and low surface energies as well as increased nucleation rates.;High shear from wet milling is also implemented as a seeding protocol configured to a mixed-suspension mixed-product removal continuous crystalliser which proved to be an adequate seed generation strategy.Deploying accurate quantitative analysis of size and shape attributes for solid particles is further explored. A multi-sensor measurement approach was employed using inline sensors, computational tools and offline techniques. The performance of these tools were vigorously tested for strengths and limitations which was proven to be beneficial for characterising the breakage of crystalline materials as well as overall process understanding and opportunities for process control.Recent advances in pharmaceutical manufacturing for consistent supply of medicines with the required physical properties has emphasised the need for robust crystallisation processes which is a critical separation and purification technique. Mechanical milling is employed post crystallisation as an offline unit operation usually in a separate dry solids processing facility for adjusting the particle size and shape attributes of crystalline products for downstream processing. An emerging and increasingly applied technology is high shear wet milling in crystalline slurries for inline size and shape modification during particle formation. This potentially avoids the need for multiple crystallisation trials and offline milling saving time, costs and powder handling. Similarly, sonication is a powerful particle engineering tool through immersing ultrasound probes directly in solution. This PhD project is focused on the investigation and process integration of wet milling and indirect ultrasound for enhancing crystallisation processes and engineering particle attributes. The experimental study combined a cooling and isothermal crystallisation (seeded & unseeded) process with wet milling and indirect sonication. Results from the combined method provides the ability to modify and selectively achieve a range of product outcomes including particle sizes with tight spans, equant shapes and low surface energies as well as increased nucleation rates.;High shear from wet milling is also implemented as a seeding protocol configured to a mixed-suspension mixed-product removal continuous crystalliser which proved to be an adequate seed generation strategy.Deploying accurate quantitative analysis of size and shape attributes for solid particles is further explored. A multi-sensor measurement approach was employed using inline sensors, computational tools and offline techniques. The performance of these tools were vigorously tested for strengths and limitations which was proven to be beneficial for characterising the breakage of crystalline materials as well as overall process understanding and opportunities for process control

Soft sensor development and process control of anaerobic digestion

This thesis focuses on soft sensor development based on fuzzy logic used for real time online monitoring of anaerobic digestion to improve methane output and for robust fermentation. Important process parameter indicators such as pH, biogas production, daily difference in pH and daily difference in biogas production were used to infer alkalinity, a reliable indicator of process stability. Additionally, a fuzzy logic and a rule-based controller were developed and tested with single stage anaerobic digesters operating with cow slurry and cellulose. Alkalinity predictions from the fuzzy logic algorithm were used by both controllers to regulate the organic loading rate that aimed to optimise the biogas process. The predictive performance of a software sensor determining alkalinity that was designed using fuzzy logic and subtractive clustering and was validated against multiple linear regression models that were developed (Partner N° 2, Rothamsted Research 2010) for the same purpose. More accurate alkalinity predictions were achieved by utilizing a fuzzy software sensor designed with less amount of data compared to a multiple linear regression model whose design was based on a larger database. Those models were utilised to control the organic loading rate of a twostage, semi-continuously fed stirred reactor system. Three 5l reactors without support media and three 5l reactors with different support media (burst cell reticulated polyurethane foam coarse, burst cell reticulated polyurethane foam medium and sponge) were operated with cow slurry for a period of seven weeks and twenty weeks respectively. Reactors with support media were proven to be more stable than the reactors without support media but did not exhibit higher gas productivity. Biomass support media were found to influence digester recovery positively by reducing the recovery period. Optimum process parameter ranges were identified for reactors with and without support media. Increased biogas production was found to occur when the loading rates were 3-3.5g VS/l/d and 4-5g VS/l/d respectively. Optimum pH ranges were identified between 7.1-7.3 and 6.9-7.2 for reactors with and without support media respectively, whereas all reactors became unstable at ph<6.9. Alkalinity levels for system stability appeared to be above 3500 mg/l of HCO3 - for reactors without media and 3480 mg/l of HCO3 - for reactors with support media. Biogas production was maximized when alkalinity was 3 between 3500-4500 mg/l of HCO3 - for reactors without support media and 3480- 4300 mg/l of HCO3 - for reactors with support media. Two fuzzy logic models predicting alkalinity based on the operation of the three 5l reactors with support media were developed (FIS I, FIS II). The FIS II design was based on a larger database than FIS I. FIS II performance when applied to the reactor where sponge was used as the support media was characterized by quite good MAE and bias values of 466.53 mg/l of HCO3- and an acceptable value for R2= 0.498. The NMSE was close to 0 with a value of 0.03 and a slightly higher FB= 0.154 than desired. The fuzzy system robustness was tested by adding NaHCO3 to the reactor with the burst cell reticulated polyurethane foam medium and by diluting the reactor where sponge was used as the support media with water. FIS I and FIS II were able to follow the system output closely in the first case, but not in the second. FIS II functionality as an alkalinity predictor was tested through the application on a 28l cylindrical reactor with sponge as the biomass support media treating cow manure. If data that was recorded when severe temperature fluctuations occurred (that highly impact digester performance), are excluded, FIS II performance can be characterized as good by having R2= 0.54 and MAE=Bias= 587 mg/l of HCO3-. Predicted alkalinity values followed observed alkalinity values closely during the days that followed NaHCO3 addition and water dilution. In a second experiment a rulebased and a Mamdani fuzzy logic controller were developed to regulate the organic loading rate based on alkalinity predictions from FIS II. They were tested through the operation of five 6.5l reactors with biomass support media treating cellulose. The performance indices of MAE=763.57 mg/l of HCO3-, Bias= 398.39 mg/l of HCO3-, R2= 0.38 and IA= 0.73 indicate a pretty good correlation between predicted and observed values. However, although both controllers managed to keep alkalinity within the desired levels suggested for stability (>3480 mg/l of HCO3-), the reactors did not reach a stable state suggesting that different loading rates should be applied for biogas systems treating cellulose.New Generation Biogas (NGB

Treatment wetlands

Treatment Wetlands is the seventh volume in the Biological Wastewater Treatment series, which gives a state-of-the-art presentation of the science and technology of sewage treatment. The major variants of wetland systems are covered in this volume, namely: (i) horizontal flow wetlands; (ii) vertical flow wetlands; (iii) French vertical flow wetlands; (iv) intensified wetlands; (v) free water surface wetlands; (vi) other applications of treatment wetlands. The book presents in a clear and didactic way the main concepts, working principles, expected performance, design criteria, design examples, construction aspects and operational guidelines. The book has been written by an international team of top experts in the field of treatment wetlands.Postprint (published version

Treatment Wetlands

Overview of Treatment Wetlands; Fundamentals of Treatment Wetlands; Horizontal Flow Wetlands; Vertical Flow Wetlands; French Vertical Flow Wetlands; Intensified and Modified Wetlands; Free Water Surface Wetlands; Other Applications; Additional Aspects