Chemical Process Control Research Articles

Spatial and temporal control of chemical processes

Controlling the where and when of a chemical reaction, rather than just the if, can be an essential component in the successful development of applications. There are a large number of situations in which a predetermined sequence of chemical reaction events might be highly beneficial. In this Review, we examine the development of such spatiotemporal control of chemical reactions. We classify the means of control into either passive or active approaches. The passive approach relies on characteristics inherent to the chosen chemical system in order to predict where and when a reaction will occur. The active strategy, on the other hand, relies on the input of an external stimulus to remotely control the onset of a chemical reaction. Among active methods, we distinguish two different strategies — either remote activation of a reaction or controlled release of chemicals. This versatile toolbox allows spatiotemporal control to be achieved in myriad situations and thus to address some key challenges in chemistry, such as drug delivery. Achieving precise control over when and where a chemical reaction takes place can open the way to a plethora of new applications. This Review gives an overview of progress made in this quest for high spatial and temporal molecular control.

(Invited) Sonoelectrochemistry: A Powerful Tool for Elucidating Mechanisms and for Accelerating Electrochemical Processes

Surface irradiation by power ultrasound has proven to offer beneficial effects not only for surface cleaning, but also for the modification of functional properties of metallic and organic coatings. However, the process scale-up has failed to match laboratory observations and data, in particular for the design of industrial sono-(electro)chemical reactor systems. To solve this major problem, electrochemical systems have been developed and employed as effective “sensors” for probing ultrasonic activity, in turns allowing numerous useful quantitative information to aid designing better sono-(electro)chemical reactor and process control. Indeed, it is possible to use electrochemistry as a tool to investigate phenomena occurring at the electrode surface and at a given location in the sono-(electro)chemical reactor. From a process accelerated by power ultrasound, electrochemistry becomes a very useful tool to quantify the ultrasonic energy (and power) scattered at the immediate working electrode surface vicinity. The electro-diffusional method is of great help, as it consists of measuring limiting currents generated by Linear Sweep Voltammetry (LSV) experiments. This approach has turned out to be extremely efficient and useful for the determination of acoustic intensity at various locations in the sono-(electro)chemical reactor [1]. By systematically moving a working electrode in an ultrasonic field, it is possible to map out the acoustic activity, especially in the zone close to the ultrasonic transducer where the most intense cavitation activity takes place. Then, to demonstrate the ‘portability’ of our generated data, i.e. to allow relevant comparisons between experiments performed using different ultrasonic and electrochemical equipment, we have proposed to convert the raw electrochemical values into equivalent velocities U, corresponding to normal flows directed towards the working electrode surface resulting in the same electrochemical signal than in the presence of power ultrasound [2]. Comparisons with ‘real fluid motion’ at a given location with the help of Particle Image Velocimetry (PIV) technique allows separation of the respective contributions of cavitational events occurring at the working electrode surface to the convection flow called ultrasonic wind [3]. This approach has been extended to several electrochemical systems. Moreover, new types of ultrasonic transducers (for example, focalized ultrasonic transducers) and new progress in the modulation of ultrasonic transducer excitation have pave the way to industrialization of sono-(electro)chemical reactors [4]. [1] Hihn J.-Y., Doche M.L, Mandroyan A., Hallez L. and Pollet B.G., Chapter 23 "Ultrasound and Better Reactor design" in Handbook on Applications of Ultrasound: Sonochemistry for sustainaibility by CRC Press Taylor & Francis, 2011, p599-622 [2] Pollet B.G., Hihn J.-Y., Doche M.L, Mandroyan A., Lorimer J.P., Mason T.J “Transport limited currents close to an ultrasonic horn: equivalent flow velocity determination”, Journal of Electrochemistry Society, 2007, 154(10), p E131-E138 [3] J.Y. Hihn, M.L. Doche, A. Mandroyan, L. Hallez, B.G. Pollet, "Respective contribution of cavitation and convective flow to local stirring in sonoreactors" Ultrasonics Sonochemistry 18(4), 881-887, (2011) [4] Hallez L., Lee J., Touyeras F., Nevers A., Ashokkumar M., Hihn J.-Y., “Enhancement and Quenching of HIFU Cavitation Activity via Short Frequency Sweep Gaps”, Ultrasonics Sonochemistry, 2016, 29, p. 194-197 Figure 1

Time-optimal symbolic control of a changeover process based on an approximately bisimilar symbolic model

Many process control problems with complex qualitative specifications cannot be addressed via conventional control design methods. Examples of such specifications include logic specifications expressed in the design of start-up, shut-down, changeover, and emergency shutdown operating procedures. In recent years, it has been shown in the control systems and computer science communities that symbolic models provide convenient and powerful mechanisms to synthesize controllers enforcing such qualitative specifications. The use of symbolic models reduces the synthesis of the controllers to a fixed-point computation problem over a finite-state abstract system. In this paper, after explaining the notion of approximate bisimulation for incrementally globally asymptotically stable (δ-GAS) nonlinear control systems, the construction of approximately bisimilar symbolic models for such systems is presented. Then synthesis of time-optimal symbolic controller for this class of systems is performed based on results from the computer science literature. As a benchmark chemical process control problem, an approximately bisimilar symbolic model is constructed for a safe changeover process. Then a symbolic controller is designed and it is refined to a controller to be applied to the original process. Simulation results show the effectiveness of the symbolic controller. Although the construction of the symbolic model may be complex, the synthesis of the controller in a finite-state space is fast and most importantly the error bounds are adjustable as design parameters.

Temperature and concentration control of exothermic chemical processes in continuous stirred tank reactors

Exothermic chemical reaction taking place in continuous stirred tank reactor is considered. Heat release from the chemical reaction, non-linear dynamic behavior of the process and uncertainty in parameters are the main factors motivating the use of robust control design. Viewing temperature and molar concentration as variables both accessible in real time, PI and optimal state-feedback controllers driven by temperature and concentration error signals are proposed to regulate the system over reactor’s steady-state working points by counteracting undesired disturbances. Since access to concentration value has proved beneficial for the reactor’s performance, estimation techniques are examined to compensate for the problematic nature of the concentration’s measurement. A linear reduced-order observer is first proposed to estimate the concentration value using temperature measurements. In addition, assuming concentration measurement is available with a relatively short delay via sample analysis, a linear and non-linear discrete-time predictor is constructed to estimate the concentration’s real-time value. A linear combination of the two estimation schemes (observer, predictor) is proposed resulting in a combined estimator, in which the emphasis between the two individual schemes can be controlled via a scalar parameter. The work presented in this paper was supported by the GLOW project – New weather-stable low gloss powder coatings based on bifunctional acrylic solid resins and nanoadditives – as part of the development of novel and efficient processing technologies regarding the production of new families of powder coatings, responding to industrial requirements for quality improvement at lower cost and shorter development cycles.

Recent Advances in Materials, Parameters, Performance and Technology in Ammonia Sensors: A Review

Importance of ammonia sensors is increasing significantly worldwide in environmental monitoring, control of chemical processes, agricultural, and medical applications. Particularly, the detection of ammonia gas is very important for many industries due to its toxicity and environmental hazards. The hybrid nanostructures formed by blending of nanoparticles of metal/metal-oxides with polymer or its derivatives have been explored which showed improved gas sensing ability and selectivity at room temperature. This article reviews ammonia gas sensors based on semiconducting materials like metals, metal oxides, metal oxide-polymers and carbon nanotubes (CNT’s) based hybrid nanostructures for different level of detection of ammonia in various applications. The characteristic performance parameters of these sensors, such as measuring range, sensitivity, selectivity, response/recovery time and the latest technological developments are discussed with detailed analysis in this article.

Nowatorskie metody neuronowej rekonstrukcji obrazów tomograficznych w eksploatacji zbiornikowych reaktorów przemysłowych

The article presents an innovative concept of improving the monitoring and optimization of industrial processes. The developed method is based on a system of many separately trained neural networks, in which each network generates a single point of the output image. Thanks to the elastic net method, the implemented algorithm reduces the correlated and irrelevant variables from the input measurement vector, making it more resistant to the phenomenon of data noises. The advantage of the described solution over known non-invasive methods is to obtain a higher resolution of images dynamically appearing inside the reactor of artifacts (crystals or gas bubbles), which essentially contributes to the early detection of hazards and problems associated with the operation of industrial systems, and thus increases the efficiency of chemical process control.

Detailed modeling and advanced control for chemical disinfection of secondary effluent wastewater by peracetic acid

Advanced control of chemical disinfection processes is becoming increasingly important in view of balancing under-treatment (low pathogen inactivation) and over-treatment (excessive consumption of disinfectant and disinfection byproducts formation) thereby providing considerable environmental and economic benefits. Conventional control strategies such as flow pacing or residual trim ignore chemical demand/decay, inactivation kinetics, and other factors governing disinfection performance in continuous-flow reactors such as reactor hydraulics and process variability. This study presents the development, verification, and pilot-scale validation of a novel CT-based real-time disinfection control strategy, derived from first principles, and applied to peracetic acid disinfection of municipal secondary effluent wastewater. Validation experiments were carried out using a 3-m3 pilot contact basin of which the hydraulic performance was first characterized by means of tracer tests and then mathematically modeled using the well-established theoretical framework of continuous stirred-tank reactors in series. The analytical model describing hydraulic performance was subsequently extended to take into account disinfectant demand/decay and microbial inactivation kinetics. The integrated model was successfully used to predict, and control, residual peracetic acid as well as microbial concentration in the pilot effluent. Validation studies conclusively supported that the novel CT-based control strategy was superior in maintaining constant disinfection performance, desired microbial counts, and low residual disinfectant under variable flow and wastewater quality. When compared with flow pacing, the CT-based control required two times less the amount of chemical for the same treatment objective (<100 cfu/100 mL). Remarkably, the CT-based control strategy could be extended to other chemical disinfection processes such as chlorination and ozonation, alone or in combination with physical treatment technologies such as membranes and ultraviolet irradiation.

Continuous control of a polymerization system with deep reinforcement learning

Reinforcement learning is a branch of machine learning, where the machines gradually learn control behaviors via self-exploration of the environment. In this paper, we present a controller using deep reinforcement learning (DRL) with Deep Deterministic Policy Gradient (DDPG) for a non-linear semi-batch polymerization reaction. Several adaptations to apply DRL for chemical process control are addressed in this paper including the Markov state assumption, action boundaries and reward definition. This work illustrates that a DRL controller is capable of handling complicated control tasks for chemical processes with multiple inputs, non-linearity, large time delay and noise tolerance. The application of this AI-based framework, using DRL, is a promising direction in the field of chemical process control towards the goal of smart manufacturing.

Data‐Driven Approximated Optimal Control for Chemical Processes with State and Input Constraints

Input and state constraints widely exist in chemical processes. The optimal control of chemical processes under the coexistence of inequality constraints on input and state is challenging, especially when the process model is only partially known. The objective of this paper is to design an applicable optimal control for chemical processes with known model structure and unknown model parameters. To eliminate the barriers caused by the hybrid constraints and unknown model parameters, the inequality state constraints are first transformed into equality state constraints by using the slack function method. Then, adaptive dynamic programming (ADP) with nonquadratic performance integrand is adopted to handle the augmented system with input constraints. The proposed approach requires only partial knowledge of the system, i.e., the model structure. The value information of the model parameters is not required. The feasibility and performance of the proposed approach are tested using two nonlinear cases including a continuous stirred‐tank reactor (CSTR) example.

Mutual Information-Weighted Principle Components Identified From the Depth Features of Stacked Autoencoders and Original Variables for Oil Dry Point Soft Sensor

In modern chemical process control, the application of data-driven soft sensor has become increasingly extensive. Feature extraction is an important step in soft sensor. A novel feature extraction and integration method based on stacked autoencoders (SAE) and mutual information (MI)-weighted principle component analysis (PCA) was proposed to solve the loss of information on shallow depth features and original variables in neural network models. First, an SAE model was trained to extract the features of the original variables with varying depths. Second, through an MI indicator, the original variables and features with strong dependency on the outputs were selected. Then, MI was used to assign varied weights to the features and original variables, and the PCA method was used to remove any possible redundancy between the original variables and features of varying depths to obtain the principle components. Finally, the principle components were used to construct a regressor, such as a neural network. The model was first tested using the Boston housing dataset as a benchmark and then applied to the soft sensor of a constant top oil dry point. The proposed model achieved optimal results in terms of the root mean squared error and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> indicators in the experiments and was thus proved feasible and useful.

Metodología de Ajuste de un NMPC con Sistema de Inferencia Borrosa Takagi Sugeno y Conjuntos Borrosos Multidimensionales para Aplicaciones en Procesos Químicos no Lineales

&lt;p&gt;En este artículo se presenta una metodología para la sintonización de los parámetros de un controlador predictivo no lineal basado en modelo (NMPC) basado en una técnica de optimización, aplicado en el control de procesos químicos no lineales, con el propósito de facilitar la etapa de determinación de los valores de ajuste de este tipo de estrategias de control. Los resultados permiten determinar el desempeño de los NMPC sintonizados con la propuesta metodológica planteada y se validan los resultados con sintonizaciones desarrolladas mediante otras estrategias. La metodología propuesta se aplica al control de la concentración de un reactivo en un tanque reactor continuamente agitado (CSTR).&lt;/p&gt;

Steering electron correlation time by elliptically polarized femtosecond laser pulses.

Electron correlation is ubiquitous across diverse physical systems from atoms and molecules to condensed matter. Observing and controlling dynamical electron correlation in photoinduced processes paves the way to the coherent control of chemical reactionsand photobiological processes. Here, we experimentally investigate dynamics of electron correlation in double ionization of neon irradiated by intense elliptically polarized laser pulses. We find a characteristic, ellipticity-dependent, correlated electron emission along the minor axis of the elliptically polarized light. This observation is well reproduced by a semi-classical ensemble model simulation. By tracing back the corresponding electron trajectories, we find that the dynamical energy sharing during the electron emission process is modified by the ellipticity of the laser light. Thus, our work provides evidence for a possible ultrafast control of the energy sharing between the correlated electrons by varying the light ellipticity.

Use of Cyber Attacks as a Case Study for Design Projects in an Undergraduate Process Control Course

Cyberattacks on process control systems are a new phenomenon. A new, simplified, and constrained design project was tested in a third year chemical engineering process control class. This design project was assigned to self-selected, small (3-4) student groups, who were tasked to produce five reports in series. The first report provided a preliminary identification and description of a cyberattack on a chemical process control system. The second report described a more detailed and technical analysis of the cyberattack, using a block diagram. The third report was a proposal of how an engineer on duty during the attack could have mitigated the effects of the cyberattack. The design component was the goal of the fourth report: create a strategy for preventing future, similar cyberattacks. The fifth report was a summary report of the first four reports, with edits made to improve the content and quality of technical writing. After the course was completed, an on-line survey was offered to the students. The results revealed the students’ inexperience with generating a solution to open problems, solving problems with few available resources, and the need for technical writing improvement.46 % of the student survey respondents reported that the project increased their understanding of the relevance of process control to their education; 32 % reported a neutral effect, and 21 % a negative effect. An overall positive recommendation favoured repeating improved iterations of this project

Influence of enzyme production dynamics on the optimal control of a linear unbranched chemical process

In this paper we consider the classic kinetic problem of the minimization of the operation time in which a substrate is transformed into a product in multi-step enzymatic reactions. We propose a realistic formulation that incorporates the enzyme dynamics, and present a method for obtaining the solution for an unbranched scheme and bi-linear kinetic model in an almost exclusively analytical way. The solution, which involves the exponential integral, is illustrated with several examples.

Simultaneous Design and Control of a Ternary Reactive Distillation Column with Inert Material

AbstractProcess integration means significant challenges in operating a chemical process dynamically due to its complexity. One example is the ternary reactive distillation with inert material. Based on the heuristic approach, chemical process design and process control are performed independently one after another. This may lead to infeasible solutions either in process design and control or in both. The application of simultaneous design and control, formulated as mixed‐integer dynamic optimization (MIDO) problems, increased rapidly in the last decade. Simultaneous process design and control, including control structure selection and control parameters, is devised for the challenging benchmark problem of a ternary reactive distillation with inert material. The improved process design and control is obtained by solving the MIDO problem.

Current Trends in the Development of Microwave Reactors for the Synthesis of Nanomaterials in Laboratories and Industries: A Review

Microwave energy has been in use for many applications for more than 50 years, from communication, food processing, and wood drying to chemical reactions and medical therapy. The areas, where microwave technology is applied, include drying, calcination, decomposition, powder synthesis, sintering, and chemical process control. Before the year 2000, microwaves were used to produce ceramics, semiconductors, polymers, and inorganic materials; in next years, some new attempts were made as well. Nowadays, it has been found that microwave sintering can also be applied to sintered powder and ceramics and is more effective than conventional sintering. Particularly interesting is its use for the synthesis of nanomaterials. This review identifies the main sources of microwave generation, the delivery mechanisms of microwave energy, and the typical designs and configurations of microwave devices, as well as the measurement and construction material problems related to microwave technology. We focus our attention on the configurations, materials, optimized geometries, and solvents used for microwave devices, providing examples of products, especially nanoparticles and other nanomaterials. The identified microwave devices are divided into four groups, depending on the scale, the maximum pressure developed, the highest temperature for sintering, or other special multi-functions. The challenges of using microwave energy for the synthesis of nanopowders have been identified as well. The desirable characteristics of microwave reactors in the synthesis of nanostructures, as well as their superiority over conventional synthetic methods, have been presented. We have also provided a review of the commercial and self-designed microwave reactors, digestors, and sintering furnaces for technology for synthesis of nanomaterials and other industries.

Detecting and Handling Cyber-Attacks in Model Predictive Control of Chemical Processes

Since industrial control systems are usually integrated with numerous physical devices, the security of control systems plays an important role in safe operation of industrial chemical processes. However, due to the use of a large number of control actuators and measurement sensors and the increasing use of wireless communication, control systems are becoming increasingly vulnerable to cyber-attacks, which may spread rapidly and may cause severe industrial incidents. To mitigate the impact of cyber-attacks in chemical processes, this work integrates a neural network (NN)-based detection method and a Lyapunov-based model predictive controller for a class of nonlinear systems. A chemical process example is used to illustrate the application of the proposed NN-based detection and LMPC methods to handle cyber-attacks.

Insights into Noncovalent Binding Obtained from Molecular Dynamics Simulations

AbstractThe key to nanoscale control of physical, chemical, and biological processes lies in well‐founded models of noncovalent binding. Atomistic simulations probe the free‐energy surface underlying molecular assembly processes in solution. Two examples of noncovalent binding studied by molecular dynamics simulations are discussed, the dimerization of a water‐soluble perylene bisimide derivative in aqueous solution with a focus on the influence of solvent composition on the aggregation strength and the binding of 1‐butanol to α‐cyclodextrin at infinite dilution with the focus on the determination of method‐independent binding free energies.

Dynamic Optimization Using Local Collocation Methods and Improved Multiresolution Technique

Dynamic optimization has wide applications in scientific and industrial researches. Multiresolution techniques provide an efficient way to solve dynamic optimization problems but have some disadvantages. An improved multiresolution technique is developed in this paper to overcome these disadvantages. The proposed technique consists of local collocation methods and a multiresolution-based mesh refinement method. New, generalized dyadic meshes are proposed to overcome the dyadic limitation, and the mesh refinement method is improved so that it can start with the coarsest generalized dyadic mesh. Additionally, the proposed technique involves a mesh refinement algorithm to remove the redundant mesh points in the constant control regions by analyzing the control slopes. The technique is applied to three chemical process control optimization problems and compared with other methods to demonstrate its effectiveness. Numerical results show that the proposed technique can solve chemical process control optimization problems accurately and efficiently and has advantages over other methods.

A switched dynamical system approach towards the optimal control of chemical processes based on a gradient-based parallel optimization algorithm

This paper considers an optimal control problem of chemical processes with a novel piecewise state-feedback controller. Firstly, the chemical process optimal control problem is formulated as a switched dynamical system optimal control problem, which can be transformed into a parameter optimization problem. Next, to achieve rapid convergence from remote starting points, we propose a novel gradient-based optimization algorithm, which is suitable to a parallel implementation because the step is improved by updating its direction as well as its length simultaneously before moving to the next iteration, and the step computation involves only the inner products of vectors. Then, the convergent properties of the parameter optimization problem to the original optimal control problem are discussed. Finally, the numerical simulation results show that the gradient-based parallel optimization algorithm is an effective alternative method for solving the chemical process optimal control problems.