Optimal Control
iman zabbah; Ali Maroosi; Abolfazl Noghandi; zahra Abbasi
Abstract
Optimizing the quality of lime, while using the energy system in the lime baking oven is a great service. Since lime baking is always allowed, you can easily control it. The purpose of this study was to predict the quality of lime during the manufacturing process in a lime baking oven and adjust the ...
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Optimizing the quality of lime, while using the energy system in the lime baking oven is a great service. Since lime baking is always allowed, you can easily control it. The purpose of this study was to predict the quality of lime during the manufacturing process in a lime baking oven and adjust the parameters provided before service delivery. The system variables presented in this study include: input tonnage and parameters of each round. Improper adjustment of these parameters will result in increased fuel consumption, resulting in poor quality lime production. Accordingly, in this paper, artificial neural networks as well as fuzzy neural networks have been used as predictive tools to predict the quality of lime produced during the baking process. These parameters are feeder, idle furnace, preheater, air conditioner, furnace, time and fuel consumption and output of the produced lime quality model. Modeling in matlab software (matlab2017) was performed using 472 samples with 8 properties. Eighty percent of the samples were used for training and 20% for testing. At the end of modeling, artificial neural networks error 0.066 and fuzzy neural network error 0.054 were obtained.
Optimal Control
Hamid Tabatabaee; Mahdi Memari
Abstract
The problem of solving optimal control of Singular problems in the classic method has a complexity that is solved by approximation of the equations in the problem with orthogonal bases instead of solving the dynamic equation system of a set of static problems. In return for a more relaxed solution, it ...
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The problem of solving optimal control of Singular problems in the classic method has a complexity that is solved by approximation of the equations in the problem with orthogonal bases instead of solving the dynamic equation system of a set of static problems. In return for a more relaxed solution, it will face some errors in the computation .however, it has an appropriate precision. Legendre and Fourier series are presented using the specifications of the Fourier transform of Legendre and Fourier series . In this algorithm, the state variables, and the state - derivative variables and the control vector are extended by the orthogonal basis of Legendre and Fourier series with unknown coefficients. in order to compute optimal control vector and optimal path of linear Singular systems with quadratic cost function , we are introduced by using the properties of orthogonal functions introduced by the coefficients and .using the proposed method , the system dynamics are converted into algebraic equations and the problem of dynamic optimization of dynamic space has been mapped to static space optimization problem with quadratic cost function and linear constraints . First, it is used to solve the problem using an orthogonal basis of raw material and then the problem solving with orthogonal basis of Fourier series is repeated. Finally, the application and effectiveness of the proposed method are presented.