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This paper considers the problem of pruning recurrent neural models of perceptron type with one hidden layer which may be used for modelling of dynamic system. In order to reduce the number of model parameters (i.e. the number of weights), the Optimal Brain Damage (OBD) pruning algorithm is adopted for the recurrent neural models. Efficiency of the OBD algorithm is demonstrated for pruning neural...
An effective approach to implement control algorithms using code auto-generation is presented. Using MATLAB and C languages as input, an optimised pure C code is generated using a custom transcompiler. The considered solution is focused on microcontrollers from the STM32 family but any other can be used due to flexibility of the presented system. Controller development for a laboratory thermal process...
This paper presents a new approach to automatic code generation of advanced control algorithms, primarily model predictive control schemes, for microcontroller-based embedded systems. The main part of the developed tools, the transcompiler, makes it possible to effectively translate the algorithms described in a high-level language (MATLAB) into C language code for the chosen hardware platform. Implementation...
This paper presents an original multiple-input multiple-output laboratory stand for process control education developed in the Institute of Control and Computation Engineering, Warsaw University of Technology. It may be used as a benchmark process to test control algorithms, including fault tolerant ones, and to compare effectiveness of model identification algorithms. Mechanical and electronic details...
This paper describes a Model Predictive Control (MPC) algorithm in which a Radial Basis Function (RBF) neural network is used as a dynamic model of the controlled process and it reports training and selection of the RBF model of the benchmark system for MPC. In order to obtain a computationally uncomplicated control scheme, the RBF model is successively linearised on-line, which leads to an easy to...
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