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To solve the problems of nonlinearity, complex reaction mechanism, high energy consumption, etc. of continuous stirred tank reactor (CSTR) in chemical production, this paper combines real-time optimization (RTO) with artificial neural network (ANN) and ...

This paper proposes a particle swarm optimization (PSO) tuned novel proportional integral derivative (PID) like neural network (PSO-PID-NN), to control the temperature of a nonlinear jacketed continuous stirred tank reactor (CSTR). The nonlinear ...

• ANN outnumbered other standalone AI models (single models) applied to WWTPs.
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Increasing energy efficiency in wastewater treatment plants (WWTPs) is becoming more important. An emerging approach to addressing this issue is to exploit development in data science and modelling. Deployment of sensors to measure ...

Controlling concentration and temperature of continuously stirred tank reactor (CSTR) is an extremely challenging task in chemical process industries. This is because conventional unity feedback schemes do not guarantee stable operating conditions ...

Control of unstable process is challenging owing to its dynamic nature, output multiplicities and stability issues. This research work focuses to develop a generic data driven modified Proximal Policy Optimization (m-PPO) reinforcement ...

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• Model free data driven controller is proposed for unstable systems.
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This paper presents a novel design technique of H-infinity based temperature and molar concentration controller for the highly non-linear system, namely continuous stirred tank reactor (CSTR). Model uncertainties and perturbation in CSTR ...

This paper discusses dynamically weighted model predictive control based on two-timescale neurodynamic optimization. Minimax optimization problems with dynamic weights in objective functions are used in the model predictive control. The minimax ...

Continuous Stirred Tank Reactor (CSTR), as one of the core equipment in chemical production, has typical nonlinear characteristics. Aiming at the problem that traditional control methods are difficult to meet its temperature control requirements, a ...

A fractional‐order PID controller is a generalization of a standard PID controller using fractional calculus. Compared with the standard PID controller, two adjustable variables, “differential order” and “integral order”, are added to the PID ...

In this paper, a new algorithm is proposed for fault detection and identification (FDI) in a class of nonlinear systems by combining the extended Kalman filter (EKF) and neuro-fuzzy networks (NFNs). There is an abundance of the literature on fault ...

This simulation study is a fuzzy model-based neural network control method. The basic idea is to consider the application of a special type of neural networks based on radial basis function, which belongs to a class of associative memory neural ...

This paper proposes a new factorized f-step radial basis function network (FS-RBF) model for model predictive control (MPC). The strategy is to develop a f-step predictor for nonlinear dynamic systems and implement it with a RBF network. In contrast to ...

Irreversible port-Hamiltonian systems (IPHS) have recently been proposed for the modelling of irreversible thermodynamic systems. On the other hand, a classical result on the use of the second law of thermodynamics for the stabilization of irreversible ...

The paper presents the application of numerical solver H-infinity fixed order optimisation HIFOO, for structured and fixed-order controller design to a feedback linearised continuous stirred tank reactor CSTR. This solver constitutes a practical ...

Ethernet, a popular technology in IT industry, with high transmission rate, simple maintenance, and compatibility with different types of links was invented for local and small-scale computer networks. However, current spanning tree-based Ethernet ...

This work presents a sequential modular approach to solve a generic network of reactors with a population balance model using a stochastic numerical method. Full-coupling to the gas-phase is achieved through operator-splitting. The convergence of the ...

This paper deals with the control of simple process models where multiple delays appear. These delays can be input, output or state delays. For the case of input/output delays, a general solution is provided. For state delays, some restrictions in the ...

This study presents a methodology for on-line identification of the nonlinear reaction process in presence of measurement noise and uncertainty, for accurate simulation of this process, a link between HYSYS (chemical software) and MATLAB was generated ...

In order to solve the difficulty in complicated system control, a new direct inverse model control strategy is proposed based on a new improved CMAC (Cerebellar Model Articulation Controller) neural network to control a kind of nonlinear system with ...

This paper is dedicated to complex system diagnosis. Therefore, a Kalman filter has been proposed to cope with external disturbances and unpredictable faults that are associated with chemical processes. The Continuous Stirred Tank Reactor (CSTR) model ...