In this article, we introduce a novel framework for the design of multi set-point nonlinear explicit controllers for process systems engineering problems where the set-points are treated as uncertain parameters simultaneously with the initial state of the dynamical system at each sampling instance. To this end, an algorithm for a special class of multi-parametric nonlinear programming problems with uncertain parameters on the right-hand side of the constraints and the cost coefficients of the objective function is presented. The algorithm is based on computed algebra methods for symbolic manipulation that enable an analytical solution of the optimality conditions of the underlying multi-parametric nonlinear program. A notable property of the presented algorithm is the computation of exact, in general nonconvex, critical regions that results in potentially great computational savings through a reduction in the number of convex approximate critical regions.

A multivariable adaptive feedback control for highly uncertain continuous anaerobic digestion processes is proposed to regulate the volatile fatty acids (VFA) concentration, the strong ions concentrations, and the total and intermediate alkalinities. The multivariable control scheme includes a Luenberger observer to estimate both the unmeasured variables (i.e., VFA) and unknown microbial growth kinetics. The control approach is designed using an exponential Lyapunov function to resemble the typical exponential biological growth of the involved microbial consortia. Taking into account physicochemical equilibrium, alkalinities are represented as a function of the state variables. As a result, the control problem becomes a regulation problem on alkalinities, and in turn, a tracking control problem on the state variables, with two manipulated variables—the dilution rate and the feed rate of a strong alkali solution—while the state variables’ set-points are given as a function of pH. The im... [more]

Predictive functional control (PFC) is a fast and effective controller that is widely used in preference to PID for single-input single-output processes. Nevertheless, the core advantages of simplicity and low cost come alongside weaknesses in tuning efficacy. This paper summarises and consolidates the work of the past decade, which has focused on proposing more effective tuning approaches while retaining the core attributes of simplicity and low cost. The paper finishes with conclusions on the more effective approaches and links to context.

As the extension of traditional linear (or X) inverted pendulum (IP), X-Z IP is a multiple-input multiple-output (MIMO), underactuated, open-loop unstable, and nonlinear system. In the tracking control of the X-Z IP, the equilibrium point changes with the pivot position of the pendulum. This makes linear control theories have difficulties in realization of the tracking control for the pendulum. The underactuated feature of the pendulum makes the feedback linearization unsuitable to simplify the control design. With the present model of the X-Z IP, there is no way to realize the backstepping design. This paper gives a novel state transformation method for the X-Z IP. Through the state transformation, the block backstepping can be easily deployed in the controller design of the X-Z IP. The proposed controller can achieve the tracking control in the vertical plane. Simulation results certify the rightness and effectiveness of the proposed tracking controller.

As renewable energy technologies decrease in cost and become more prevalent, there is an increasing trend towards electrification of many energy systems [...]

The purpose of this study is to analyze how managers of sections that belong to the chemical industry make use of management control systems (MCS) in order to facilitate relationships between the labor force of the owner enterprise and employees of outsourced companies, through collaboration and daily bases of coworking. It intends to consider how they allocate their available resources to the contractor characteristics and how, together, they confront external factors. The research strategy is based on a case study in which the uses of MCS by the most relevant Spanish chemical contractor influence the relationship with subcontractors in terms of strategic goals, trust, risk management or performance evaluation. Findings derived from four semi-structured interviews conducted with the central contractor and three subcontractors belonging to each of the three separate activities’ categories suggest that using MCS as controlling or enabling, in this setting, can have lasting and deep effe... [more]

An electron-donating−accepting (D−A) molecule, namely, 4-(1-(4-(9H-carbazol-9-yl)phenyl)-1H-1,2,3-triazol-4-yl)benzo[c][1,2,5]thiadiazole (BT-SCC) containing carbazole as the donor moiety and benzothiadiazole as the acceptor moiety is prepared. Single-crystal X-ray structure analysis elucidated the multiple intermolecular interactions, such as hydrogen bonds, CH…π, and π…π interplays. Interestingly, the aggregation-induced emission phenomenon is observed for BT-SCC featured with enhanced fluorescent quantum yield from diluted solution of CH2Cl2 (Φ = ca. 0.1) to CH2Cl2/hexane mixed solutions or solid states (Φ = ca. 0.8). Finally, aggregates of BT-SCC are obtained through precipitating from hot and saturated solutions or solvent-vapor methods and the aggregating morphologies could be easily controlled through different preparation methods. Fabulous cube-like micro-crystals and nanospherical structures are obtained, which is established by the synergistic effects of the multiple non-cova... [more]

The atmospheric corrosion of weathering steels varies as a function of geographic zone, season, and other environmental variables related to that region which the experiments have been done. Meanwhile, rusting is a continuous process, and it is the main corrosion product of atmospheric corrosion. The current study investigates the effects of rust on weathering steel in the localized region of Digha, a sea resort of West Bengal, India. The investigations have been performed by purposely accelerating the rusting of weathering steel in a laboratory within one week in order to simulate approximately 18 months of actual rusting that can be achieved at field exposure. Anodic polarization of weathering steel comparable to potentiostatic passivation is obtained by shorting weathering steel with nobler metals, such as copper or graphite. The effect of rust formation on corrosion resistance after being immersed in 0.01 M KCl solutions for polished and unpolished samples has been investigated usi... [more]

With the widespread use of substations around the world, oil jet fire accidents from transformer oil-filled equipment in substations caused by faults have occurred from time to time. In this paper, a series of transformer oil jet fire experiments are carried out by changing the external heat source (30 cm and 40 cm) and the inner diameter of the container (5 cm, 8 cm and 10 cm) to study the axial centerline temperature distribution of the transformer oil jet fire plume of the transformer oil-filled equipment in the substation. The experiment uses K-type thermocouple, electronic balance and CCD to measure and assess the temperature distribution of the axial centerline of the fire plume of the transformer oil jet. The result demonstrates that the axial centerline temperature of the fire plume increases with the external heat release rate and the inner diameter of the container. In addition, a novel axial temperature distribution prediction model of the transformer oil jet fire plume is e... [more]

Today, real-time fault detection and predictive maintenance based on sensor data are actively introduced in various areas such as manufacturing, aircraft, and power system monitoring. Many faults in motors or rotating machinery like industrial robots, aircraft engines, and wind turbines can be diagnosed by analyzing signal data such as vibration and noise. In this study, to detect failures based on vibration data, preprocessing was performed using signal processing techniques such as the Hamming window and the cepstrum transform. After that, 10 statistical condition indicators were extracted to train the machine learning models. Specifically, two types of Mahalanobis distance (MD)-based one-class classification methods, the MD classifier and the Mahalanobis−Taguchi system, were evaluated in detecting the faults of rotating machinery. Their performance for fault detection on rotating machinery was evaluated with different imbalanced ratios of data by comparing with binary classification... [more]

A novel delay-dependent stability criterion for Takagi-Sugeno (T-S) fuzzy systems with multiplicative noise is addressed in this paper subject to passivity performance. The general case of interval time-varying delay is considered for the practical control issue. For the criterion, an integral Lyapunov-Krasovskii function is proposed to derive some sufficient relaxed conditions and to avoid the derivative of the membership function. Moreover, a free-matrix inequality is adopted to deal with the delay terms such that the available derivative of time-varying delay is bigger than one. In order to employ a convex optimization algorithm to find the control gain, a projection lemma is applied to acquire the Linear Matrix Inequality (LMI) form of the sufficient conditions. With the obtained gains, a fuzzy controller is designed by the concept of Parallel Distributed Compensation (PDC) such that the delayed T-S fuzzy systems with multiplicative noise are asymptotically stable and passive in th... [more]

Anaerobic digestion is associated with various crucial variables, such as biogas yield, chemical oxygen demand, and volatile fatty acid concentration. Real-time monitoring of these variables can not only reflect the process of anaerobic digestion directly but also accelerate the efficiency of resource conversion and improve the stability of the reaction process. However, the current real-time monitoring equipment on the market cannot be widely used in the industrial production process due to its defects such as expensive equipment, low accuracy, and lagging analysis. Therefore, it is essential to conduct soft sensor modeling for unmeasurable variables and use auxiliary variables to realize real-time monitoring, optimization, and control of the an-aerobic digestion process. In this paper, the basic principle and process flow of anaerobic digestion are first briefly introduced. Subsequently, the development history of the traditional soft sensor is systematically reviewed, the latest dev... [more]

The present work investigated the effects of bending the outlet nozzles of fluidic oscillators installed on the NACA0015 airfoil with a flap on the flow control performance and, thus, the aerodynamic performance of the airfoil. The effects of bending on fluidic oscillators have not been reported so far in previous works. The aerodynamic analysis was performed numerically using unsteady Reynolds-averaged Navier-Stokes equations. Three different cases were considered: Case 1 changes only the bending angle with a fixed pitch angle, Case 2 changes only the pitch angle without bending, and Case 3 changes both the bending and pitch angles. Although the bending of the oscillators was introduced inevitably due to a geometrical limitation in the installation, the results indicated that the bending rather improved the lift coefficient and lift-to-drag ratio of the airfoil by improving the characteristics of the fluidic oscillators, such as the jetting angle and peak velocity ratio.

For the purpose of designing a reasonable control strategy for DOC-assisted DPF regeneration, a mathematical model that describes the thermal phenomenon both in a diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) during regeneration is developed. All boundary conditions of this model are obtained by experiments. The effects of the main exhaust parameters such as exhaust mass flow rate, exhaust temperature, oxygen concentration and emission of reactants are investigated comprehensively. The effects of two main parameters of control strategy, DOC-out temperature and soot loading, are analyzed as well. To quantify the effects of relevant parameters, the fuzzy grey relational analysis method is utilized to evaluate the correlation coefficient of all factors to key indexes of DPF regeneration such as maximum temperature, maximum rate of temperature increase and regeneration duration. The results of this work will greatly reduce the complexity of analysis and enable more ra... [more]

Backlash is a commonly non-linear phenomenon, which can directly degrade the control accuracy of a pneumatic control valve. To explain the cause and law of backlash error, and to propose an effective method, many research works on the modeling of a pneumatic control valve system have been carried out. The currently model of a control valve system can be classified as a physical model, data-driven model, and semi-physical model. However, most models only consider the force-displacement conversion process of a pneumatic diagram actuator in a pneumatic control valve system. A physical model based on the whole workflow of the pneumatic control valve system is established and a control method to eliminate the backlash error is proposed in this paper. Firstly, the physical model of the pneumatic control valve system is established, which is composed of three parts: pneumatic diaphragm actuator model, nozzle-flapper structure model and electromagnetic model. After that, the input−output relat... [more]

The traditional perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm of a structure is simple and low-cost. However, the P&O algorithm is prone to divergence under solar radiation when the latter varies rapidly and the P&O algorithm cannot track the maximum power point (MPP) under partial shading conditions (PSCs). This study proposes an algorithm from the P&O algorithm combined with the solar radiation value detection scheme, where the solar radiation value detection is based on the solar photovoltaic (SPV) module equivalent conductance threshold control (CTC). While the proposed algorithm can immediately judge solar radiation, it also has suitable control strategies to achieve the high efficiency of MPPT especially for the rapid change in solar radiation and PSCs. In the actual test of the proposed algorithm and the P&O algorithm, the MPPT efficiency of the proposed algorithm could reach 99% under solar radiation, which varies rapidly, and under PSCs. Howe... [more]

Electrochemically mediated atom transfer radical polymerization (eATRP) of styrene was studied in detail by using CuBr2/TPMA (TPMA = tris(2-pyridylmethyl)amine) as a catalyst. Redox properties of various Cu(II) species were investigated in CH3CN, dimethylformamide (DMF), and dimethyl sulfoxide (DMSO) both in the absence and presence of 50% (v/v) styrene. This investigation together with preliminary eATRP experiments at 80 °C indicated DMF as the best solvent. The effects of catalyst, monomer, and initiator concentrations were also examined. The livingness of the polymerization was studied by chain extension and electrochemical temporal control of polymerization.

The goal of this study was to determine the feasibility of the large-scale cultivation of locally isolated Tetraselmis striata in different open ponds in Gran Canaria. The biomass productivities were 24.66 ± 0.53 kgDW in 32 days (28.9 t/ha/year) for 8000 L indoors, 42.32 ± 0.81 kgDW in 43 days (38.8 t/ha/year) for an 8000 L pond outdoors, and 54.9 ± 0.58 kgDW in 28 days (19.6 t/ha/year) for a 45,000 L pond outdoors. The photosynthetic efficiencies were 1.45 ± 0.03% for an 8000 L pond indoors, 1.95 ± 0.04% for 8000 L outdoors. and 1.10 ± 0.01% for a 45,000 L pond outdoors. The selected strain was fast-growing (µ = 0.21 day−1) and could be rapidly scaled up to 45,000 L; it formed healthy cultures that maintained high photosynthetic activity during long-term cultivation and provided stable biomass productivities, able to grow on urea, which acted as a cheap and effective grazer control. The obtained biomass is a good source of proteins and has an FA profile with a high content of some nut... [more]

Reliable operation of lab-on-a-chip systems depends on user-friendly, precise, and predictable fluid management tailored to particular sub-tasks of the microfluidic process protocol and their required sample fluids. Pressure-driven flow control, where the sample fluids are delivered to the chip from pressurized feed vessels, simplifies the fluid management even for multiple fluids. The achieved flow rates depend on the pressure settings, fluid properties, and pressure-throughput characteristics of the complete microfluidic system composed of the chip and the interconnecting tubing. The prediction of the required pressure settings for achieving given flow rates simplifies the control tasks and enables opportunities for automation. In our work, we utilize a fast-running, Kirchhoff-based microfluidic network simulation that solves the complete microfluidic system for in-line prediction of the required pressure settings within less than 200 ms. The appropriateness of and benefits from this... [more]

Process fault is one of the main reasons that a system may appear unreliable, and it affects the safety of a system. The existence of different degrees of noise in the industry also makes it difficult to extract the effective features of the data for the fault diagnosis method based on deep learning. In order to solve the above problems, this paper improves the deep belief network (DBN) and iterates the optimal penalty term by introducing a penalty factor, avoiding the local optimal situation of a DBN and improving the accuracy of fault diagnosis in order to minimize the impact of noise while improving fault diagnosis and process safety. Using the adaptive noise reduction capability of an adaptive lifting wavelet (ALW), a practical chemical process fault diagnosis model (ALW-DBN) is finally proposed. Then, according to the Tennessee−Eastman (TE) benchmark test process, the ALW-DBN model is compared with other methods, showing that the fault diagnosis performance of the enhanced DBN com... [more]

In this paper, a control strategy combining the feedback linearization theory and sliding mode variable structure theory is proposed to solve various nonlinear factors, uncertainty of external disturbance and high-precision pressure control problems in the Direct-Drive Volume Control (DDVC) electro-hydraulic servo system. The nonlinear mathematical model of the DDVC electro-hydraulic servo system is established, and the nonlinear factors in the system are accurately linearized by the feedback linearization theory. The uncertainty of external disturbance in the system is compensated by the sliding mode control variable structure theory. The feedback-linearized sliding mode control algorithm proposed in this paper is verified using the DDVC electro-hydraulic servo system experimental platform. The experimental results show that, compared with the classical PID control, the proposed control algorithm can effectively improve the pressure output precision, as well as the dynamic response ch... [more]

This paper proposes a neural network-based process fault diagnosis system with Andrews plot for information pre-processing to enhance the performance of online process fault diagnosis. By using features extracted from Andrews plot as the inputs to a neural network, as a classifier, the diagnosis speed and reliability are improved. A method for determining the important features in the Andrews function is proposed. The proposed fault diagnosis system is applied to a simulated continuous stirred tank reactor process and is compared with two conventional neural network-based fault diagnosis systems: scheme B where the monitored measurements are directly fed to a neural network after scaling and scheme C where the monitored measurements are converted to qualitative trend data before feeding to a neural network. Of all the considered faults, the proposed fault diagnosis system diagnosed the abrupt faults on average 5.45 s and 2.66 s earlier than schemes B and C, respectively and diagnosed t... [more]

In this study, a case study to produce microcellular foam of a commercial thermoplastic polyurethane (TPU) through the supercritical carbon dioxide (CO2) foaming process is presented. To explore the feasibility of TPU in medical device and biomedical application, a soft TPU with Shore hardness value of 70A was selected as the model compound. The effects of saturation temperature and saturation pressure ranging from 90 to 140 °C and 90 to 110 bar on the expansion ratio, cell size and cell density of the TPU foam were compared and discussed. Regarding the expansion ratio, the effect of saturation temperature was considerable and an intermediate saturation temperature of 100 °C was favorable to produce TPU microcellular foam with a high expansion ratio. On the other hand, the mean pore size and cell density of TPU foam can be efficiently manipulated by adjusting the saturation pressure. A high saturation pressure was beneficial to obtain TPU foam with small mean pore size and high cell de... [more]

Quantitative determination of most economic valuable metals in waste is the first fundamental operation of evaluating the feasibility of recycling processes. Field-portable X-ray fluorescence spectrometers (FPXRFs) represent a more practical, efficient, and economic tool in determining the elemental composition of samples with respect to conventional analytical techniques, such as atomic absorption spectrometry (AAS) and inductively coupled plasma emission spectrometry (ICP). In this paper, quick and smart determination of gold content in printed circuit boards (PCBs) of waste mobile phones was studied. The aim of the research was to combine the practicality of FPXRFs with the reliability of quantitative spectrometry analysis and evaluate the error between the two techniques. Several samples (33) of PCBs were ground to a size below 0.5 mm, and then, the powders were analyzed by FPXRFs at different acquisition times with five replications for each sample. The same analyzed samples then... [more]

The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-mo... [more]