Industrial Continuous Stirred Tank Reactor Research Articles

Extended State Observer Based Robust Feedback Linearization Control Applied to an Industrial CSTR

In the chemical and petrochemical industries, the Continuous Stirred Tank Reactor (CSTR) is, without doubt, one of the most popular processes. From a control point of view, the mathematical model describing the temporal evolution of the CSTR has a strongly nonlinear cross-coupled character. Moreover, modeling errors such as external disturbances, neglected dynamics, and parameter variations or uncertainties make its control task a very difficult challenge. This problem has been the subject of a wide number of control strategies. This article attempts to propose a viable, robust nonlinear decoupling control scheme. The idea behind the proposed approach lies in the design of two nested control loops. The inner loop is responsible for the compensation of the nominal model's nonlinear cross-coupled terms via a static nonlinear feedback; while the outer loop, designed around an Extended State Observer (ESO), which the additional state gathers the global effect of modeling errors, is charged with instantaneously estimating and then compensating the ESO extended state. This way, the CSTR complex dynamics are reduced to a series of decoupled linear subsystems easily controllable using a simple Proportional-Integral (PI) linear control to ensure the robust pursuit of reference signals respecting the desired performance. The presented control validation was performed numerically by an objective comparison to a classical PID controller.

Fault‐tolerant controller design for nonlinear systems with multiple input and state delays based on sliding mode algorithm

AbstractIn this article, a novel sliding mode control (SMC) strategy for nonlinear Lipschitz systems with multiple and dissimilar time delays in the states and inputs is proposed. Using linear matrix inequality, a modified integral sliding surface scientifically based on which the innovative SMC approach is developed. Lyapunov–Krasovskii's theory is employed to guarantee asymptotic stability of the closed‐loop system, such that states starting from any arbitrary initial conditions reach the sliding surface in a finite time and stay on it for all subsequent time. It is also proved that the practical effects of the actuator's faults are simultaneously attenuated. An online adaptive tuning law is used to estimate and isolate actuators' possible faults reliably. From the implementation point of view, the controller structure is more straightforward than the most existing recent fault‐tolerant control methods. Simulation results performed on practical nonlinear systems (quadruple tank and industrial continuous stirred tank reactor) verified the outstanding merits of the proposed approach. The operational capabilities of the proposed scheme in the presence of actuators' faults and multiple delays in the states and inputs were also demonstrated.

Biodiesel production using calcium‐based catalyst from venus shell: Modeling of startup production in an industrial reactor

Calcium oxide‐based catalyst was produced from Venus shell by fast fluidized bed calcination for biodiesel synthesis. The kinetics of biodiesel synthesis was found to be a pseudo‐first‐order reaction at the experimental conditions. The obtained kinetic parameters were used for modeling the startup operation of biodiesel production in an industrial continuous stirred tank reactor (CSTR). The model was found to agree well with the reagent concentration and temperature profiles in a real production practice during biodiesel production. The variations of initial temperature, initial reagent concentration in the reactor was investigated. It was found that the reagent concentration and temperature oscillated around the final steady state. From safety operation perspective, the first 4 h were found to be the most unsteady period during continuous production. The initial concentration of waste fry oil (WFO) was also found to be critical to the safe operation of CSTR. A violation of the settings for safe operation of CSTR will be triggered once the initial concentration of WFO in CSTR reaches 500 mol m−3. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13053, 2019

Memory scheduling robust filter‐based fault detection for discrete‐time polytopic uncertain systems over fading channels

A novel memory scheduling robust H ∞ fault detection filter (FDF) is proposed for a class of discrete-time polytopic uncertain systems with fading channel communication networks. The main merit of this filter-based fault detection method is that it can significantly improve the robustness of FDF to attenuate influences from external disturbance, channel fading and model uncertainty on fault detection accuracy. Designing such FDF involves three main stages. First of all, a memory scheduling FDF structure is proposed based on the utilisation of weighted historical filter's states over interval instants, and a residual error system is formulated based on time partition and state augmented approaches. Then, the parameter-dependent Lyapunov method is further utilised to analyse the stochastic stability of the residual error system with the help of Finsler equivalent transformation. In the following, a two-stage optimisation algorithm combined with scalar parameters method is constructed to design memory scheduling FDF in a less conservative linear matrix inequality manner. Finally, a random numerical verification with 300 test systems and a case study of an industrial continuous-stirred tank reactor are exploited to show the effectiveness of obtained results.

Co-design of event generator and quantized fault detection for time-delayed networked systems with sensor saturations

This paper investigates the problem of fault detection for the time-delayed networked systems. Different from the traditional fault detection systems, the considered system has the following feature: (i) the measured output of system is subject to sensor saturations; (ii) the system considers the influence of transmission delay and disturbance, which are two common phenomenon under the network environment; (iii) an output-dependent triggered scheme and measurement quantization are introduced in order to reduce the network bandwidth burden and improve communication efficiency. Considering aforementioned characteristics, a new type of fault detection filter model is builded. By constructing a Lyapunov functional, some new sufficient conditions for both the existence of above filter and the mean square stability of networked systems are obtained in terms of linear matrix inequalities (LMIs). Moreover, the suitable fault detection filter and the event generator can be co-designed simultaneously. Finally, a simulation example and an industrial continuous stirred tank reactor system are employed to verify the effectiveness and usefulness of the proposed method.

Stochastic Stability and Stabilization of Semi-Markov Jump Linear Systems with Uncertain Transition Rates

This paper investigates the problems of robust stochastic stability and stabilization for a general class of continuous-time semi-Markovian jump linear systems (S-MJLSs). The main contribution of the research is to eliminate the limitations of the traditional S-MJLSs with precisely available information by introducing a system with uncertain, time-varying transition rates (TRs) of the jump process, in addition to the imperfect information on the system dynamic matrices. The new system is called the general uncertain semi-Markov jump linear system (GUS-MJLS); it does not contain certain values of the transition rates, but includes nominal time-dependent values in addition to bounded deviations. It is suitable to describe a broader class of dynamical systems with estimated information and modeling errors and also covers the concepts of Markov jump linear system (MJLSs) with time-constant and certain TRs. For this system, the stability is firstly analyzed through the multiple stochastic Lyapunov function approach. Then, based on the stability results, a robust state-feedback controller is formulated. To deal with the time-dependent TRs, a sojourn-time fractionizing technique is used and numerically testable conditions are developed. Finally, discussions on reducing the conservativeness of the robust theorems are provided. The theoretical results are successfully tested on an industrial continuous stirred tank reactor (CSTR) subject to stochastically varying environmental conditions. Comparative simulations are also provided to show the superiority of the presented framework and design method to the existing ones.DOI: http://dx.doi.org/10.5755/j01.itc.46.1.13881

Development of a Free Radical Kinetic Model for Industrial Oxidation of p-Xylene Based on Artificial Neural Network and Adaptive Immune Genetic Algorithm

A novel kinetic model based on the free radical mechanism is used to simulate the oxidation of p-xylene (PX) in a continuous stirred-tank reactor (CSTR) under industrial operating conditions. Because this kinetic model cannot provide appropriate prediction of the influence of the reaction factors, such as catalyst concentrations, water concentrations, and temperatures, on the kinetic parameters for oxidation of PX in the laboratory semibatch reactor (SBR), the kinetic parameters that are highly nonlinear of the reaction factors are estimated by a back-propagation neural network (BPNN). Furthermore, correction coefficients are introduced to accurately evaluate the kinetic parameters based on Adaptive Immune Genetic Algorithm (AIGA) due to the significant difference between the nature of PX oxidation conducted in the laboratory SBR and in the industrial CSTR. The model with the evaluated optimum kinetic parameters is obtained, and its efficiency is validated via comparison with industrial data.

Optimization of industrial CSTR for vinyl acetate polymerization using novel shuffled frog leaping based hybrid algorithms and dynamic modeling

Industrial scale continuous stirred tank reactor (CSTR) for production and grade transitions of poly vinyl acetate (PVAc) at the different reactor sizes was investigated. Such reactor is known to show oscillatory behavior and to have periodic limit points, particularly at high molecular weights. Four efficient novel hybrid optimization methods which use variable population size genetic algorithm (VPGA), bacterial optimization algorithm (BO) and shuffled frog leaping method (SFL) were introduced for this kind of reactors. These algorithms can reliably find dynamically stable points with desired conditions for PVAc production. The dynamic modeling combined with the new hybrid optimization methods were used to obtain the optimal operating conditions which increased the outlet flow rate by 17%.

An Improved Fuzzy Predictive Control Algorithm and Its Application to an Industrial CSTR Process

A finite horizon predictive control algorithm, which applies a saturated feedback control law as its localcontrol law, is presented for nonlinear systems with time-delay subject to input constraints. In the algorithm, N free control moves, a saturated local control law and the terminal weighting matrices are solved by a minimization problem based on linear matrix inequality (LMI) constraints online. Compared with the algorithm with a nonsaturated local law, the presented algorithm improves the performances of the closed-loop systems such as feasibilityand optimality. This model predictive control (MPC) algorithm is applied to an industrial continuous stirred tank reactor (CSTR) with explicit input constraint. The simulation results demonstrate that the presented algorithm is effective.

Data mining macrokinetic approach based on ANN and its application to model industrial oxidation of p-xylene to terephthalic acid

Considering that kinetics and thermodynamics are coupled with heat and mass transfer effects being present in the liquid-phase catalytic oxidation of p-xylene to terephthalic acid (OXTA) in an industrial type of continuous stirred tank reactor (CSTR) and that the time evolution of the concentration of all the interest intermediate and final products of OXTA in the industrial CSTR cannot be obtained to estimate macrokinetic parameters, a novel data mining macrokinetic approach based on artificial neural network (ANN) was proposed to develop the macrokinetic model of OXTA in the industrial CSTR, which mines intrinsic kinetics and transport phenomena information from the sample data collected from OXTA in the industrial CSTR. Firstly, the reaction orders of OXTA are estimated by the mass transfer-free experiment data in the laboratory semi-batch stirred tank reactor. The kinetics of OXTA in the industrial CSTR is assumed to be zeroth-order with respect to gaseous reactants, 0.65-order with respect to p-xylene, and first-order with respect to the other liquid reactants, respectively. Secondly, ANN is employed to model the influence of the reaction parameters on the rate constants of OXTA in the industrial CSTR. Based on the sample data collected from OXTA in the industrial CSTR, heuristic differential evolution algorithm is employed to adjust the weights and thresholds of the rate constant ANN in such a way that it minimizes the prediction error of the macrokinetic model, and thus the optimal weights and thresholds are obtained and the macrokinetic model of OXTA in the industrial CSTR is developed. The reliability of the macrokinetic model was investigated and the satisfactory results were obtained. Further, a generalized macrokinetic approach for multi-phase reaction in industrial reactor was suggested too.

Development of a kinetic model for industrial oxidation of p‐xylene by RBF‐PLS and CCA

AbstractA novel lumped kinetic model for the liquid‐phase oxidation of p‐xylene to terephthalic acid (OXTA) catalyzed by cobaltic, manganic, and bromide salts in industrial continuous stirred‐tank reactor (CSTR) was proposed. First, the radial basis functions (RBF) coupled with partial least squares (PLS) approach was used to model the influence of the reaction factors on the rate constants of the lumped kinetic scheme for OXTA in the laboratory semibatch reactor (SBR). Second, to indicate the difference between OXTA in the industrial CSTR and that in the laboratory SBR, the correction coefficients were proposed and introduced into the obtained rate constants models to describe the influence of the reaction factors on OXTA in the industrial CSTR. Third, the kinetics of each of the lumped reactions is assumed to be zeroth‐order with respect to gaseous reactants, 0.65‐order with respect to p‐xylene, and first‐order with respect to the other liquid reactants, respectively. Based on the lumped kinetic model with unknown correction coefficients and the data obtained in the industrial CSTR, a modified genetic algorithm containing a chaotic variable, designated chaos‐genetic algorithm (CGA), was used to obtain the optimum correction coefficients, and the lumped kinetic model for OXTA in the industrial CSTR was developed. Further, the reliability of the model was investigated and the satisfactory results were obtained. © 2004 American Institute of Chemical Engineers AIChE J, 50: 1169–1176, 2004

LMI-based robust model predictive control and its application to an industrial CSTR problem

In this paper, robust model predictive control (MPC) is studied for a class of uncertain linear systems with structured time-varying uncertainties. This general class of uncertain systems is useful for nonlinear plant modeling in many circumstances. The controller design is characterizing as an optimization problem of the “worst-case” objective function over infinite moving horizon, subject to input and output constraints. A sufficient state-feedback synthesis condition is provided in the form of linear matrix inequality (LMI) optimizations, and will be solved on-line. The stability of such a control scheme is determined by the feasibility of the optimization problem. To demonstrate its usefulness, this robust MPC technique is applied to an industrial continuous stirred tank reactor (CSTR) problem with explicit input and output constraints. Its relative merits to conventional MPC approaches are also discussed.