Search Results - (( developing control prediction algorithm ) OR ( java implication based algorithm ))

Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

“…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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Formulation of model predictive control algorithm for nonlinear processes by Mohd. Yusof, Khairiyah, Hassim, Mimi Haryani, Tan, Sook Li, Ab. Rashid, Siti Rafidah

“…The most significant feature that distinguishes MPC from other control algorithms is its long range prediction concept. …”
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Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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Implementation of generalized predictive control (GPC) for a real-time process control using labview by Mohd. Faudzi, Ahmad 'Athif

“…In this research, a predictive algorithm namely Generalized Predictive Control will be evaluated in real-time by applying LabVIEW software as tools for algorithm implementation. …”
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Design of Simplified Model Predictive Controller by Borhan, Mohd Ikram Solehuddin

“…SMPC control algorithm is an efficient and simple method for multivariable control. …”
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Model predictive control of vaporizer in vinyl acetate monomer process by Mohd Sharizan, Md Sarip

“…A Model Predictive Control (MPC) algorithm is developing on the Vinyl Acetate Monomer process provided by Luyben and Tyreus. …”
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Attitude Control System for InnoSAT by Anon

“…To develop attitude control algorithms software; ACS is the part of the ADCS payload. …”
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Model predictive control on fed-batch penicillin fermentation process by Chew, Li Mei

“…To facilitate the study, model predictive control (MPC) based on unstructured model for penicillin production in a fed-batch fermentor has been developed. …”
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Model Predictive Control Design for f Nonlinear Four-Tank System by Ansarpanahi, Shadi

“…Since linear model predictive control is used instead of nonlinear model predictive control; these problems are avoided to be appeared in this work. …”
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Maximum Power Prediction for PV System based on P&O Algorithm by Mushtaq, Al-Duliamy, Hojabri, Mojgan, Hamdan, Daniyal, Ali Mahmood, Humada

“…This research presents a maximum power point tracking (MPPT) controller for PV systems is proposed. The developing of the proposed controller is based on conventional P&O algorithm and an Artificial Neural Network. …”
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SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS by SETYO WIBOWO, TRI CHANDRA

“…A simple set of guidelines for tuning the model predictive controller is proposed. Several important issues in the identification process and real-time implementation of model predictive control algorithm are also discussed. …”
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Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail by Ismail, Muhammad Sirajuddin

“…This study aims to investigate the requirements of utilizing the Artificial Neural Network algorithm for prediction of dengue outbreak. The objective is to develop Dengue Outbreak Prediction System using Artificial Neural Network algorithm and evaluate its performance. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Performance Analysis of a Real-Time Adaptive Prediction Algorithm for Traffic Congestion by Nadeem, Khodabacchus Muhamad, Fowdur, Tulsi Pawan

“…The performance of the prediction algorithms was analysed, and it was observed that the proposed schemes provide the best prediction results with a lower Mean Square Error than all other prediction algorithms when compared with the actual traffic congestion states.…”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Real-time implementation of model predictive control for flow control application by Rosli, N.S., Ibrahim, R.

“…Therefore MPC is highlighted as advanced process control for dynamic model system. A control algorithm is focused on developing MPC using MATLAB/Simulink Toolboxes. …”
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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

“…In doing so, Multi-Parametric Programming technique is used to develop the computer algorithm; whereas Model-Based Predictive Control (MPC) is adopted for the design of the controller. …”
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Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity by N. Narayanasamy, Anand

“…The objective of this paper is to develop a model based compensation algorithm using optimization approach of MIQP based MPC backlash compensator for control valve stiction nonlinearity. …”
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DC motor control using LQR algorithm by Adezeno, Sagoli Olid

“…The LQR controller will act as a benchmark for the algorithm performance of the overall control system.…”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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