Thermal process model parameter identification method through improved hybrid particle swarm algorithm

Abstract

The invention discloses a thermal process model parameter identification method through an improved hybrid particle swarm algorithm. The method comprises the following steps: 1) determining an identification system structure and parameters to be identified; 2) obtaining input / output data for identification; and 3) carrying out the improved hybrid particle swarm algorithm to obtain an optimal solution. The identification problem of a thermal process model is converted into the combinatorial optimization problem of parameters; effective searching is carried out on a parameter space through the improved hybrid particle swarm algorithm to obtain optimal estimation of system model parameters; compared with a basic particle group algorithm, the method introduces selection, hybridization and mutation mechanisms in a genetic algorithm, thereby keeping population diversity and preventing the algorithm from being trapped in the local optimal solution; the idea of vaccine extraction and vaccination in artificial immunity is introduced, so hat algorithm search speed is improved; improved adaptive mutation is adopted, so that diversity of particles is kept more reasonably; and through introduction of a simulated annealing idea, the method has probabilistic leap capability in the searching process and prevents the searching process from being trapped in the local optimal solution.

Description

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AI Technical Summary

Benefits of technology

This patented technology helps solve problems with identifying thermodynamic models by optimizing their values based on certain factors like temperature or pressure. It uses advanced techniques such as molecular dynamics simulations (MD) for generating particles that can be used instead of traditional methods. These improvements help improve accuracy when searching through large data sets quickly without losing important parts of them due to changes caused by environmental conditions. Additionally, it suggests adding virus-like agents called vaccines to create antibody responses against specific viruses found naturally within humans' bodies. By simulating these processes over time, researchers may better identify new diseases associated with heat production systems. Overall, this innovative method provides technical benefits including faster analysis times, increased efficiency, enhanced safety measures, etc., making it possible to develop effective treatments for various medical disorders related to excessive body temperatures.

Problems solved by technology

The technical problem addressed by this patents relates to developing efficient techniques for identifying thermodynamic devices (TDP) during industrial processes like combustion engines or gas turbine generators. Current models have difficulty accurately predicting their properties due to various environmental issues associated with current materials and manufacturing procedures. This requires learning from past experience and improving existing methods to apply them to controller regulation in order to achieve better performance levels over longer periods.

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