In the last two decades, evolutionary based algorithms have proved to be an important tool in solving optimisation problems in many disciplinary areas namely in control system design. However one of its limitations, for some type of applications, is the usually high computational load required, which restricts its use for on-line control. This paper proposes the use of a stochastic search algorithm, known as particle swarm, as an optimisation tool for an on-line predictive control of a custom made thermodynamic system. Preliminary results are presented
Genetic Algorithms (GA), Simulated Annealing (SA) and Particle Swarm Optimisation (PSO) are populati...
The general motivation of our work is to meet the main time constraint when implementing a control l...
Every possible problem can be considered to have a set of possible states by which amongst them, som...
In the last two decades, evolutionary based algorithms have proved to be an important tool in solvin...
In the past decade, evolutionary based algorithms have been a popular research theme in many discip...
The particle swarm optimisation algorithm is proposed as a new method to design a model based predi...
Particle Swarm Optimization (PSO) is an evolutionary computation technique, which has been inspired ...
Abstract:- Several Evolutionary Algorithms (EAs) are applied in the design and optimization of digit...
Despite the large number of existent design and tunig techniques, adequate PID controller tuning by ...
The particle swarm optimization (PSO) algorithm is a stochastic, population-based optimization techn...
During the last three decades there has been a growing interest in algorithms which rely on analogie...
Real-time implementations of controllers require optimization algorithms which can be performed quic...
This thesis investigates the hybrid application of stochastic and heuristic algorithms, in particula...
Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophistic...
ISBN: 978-1-84821-590-0The classic approach in Automatic Control relies on the use of simplified mod...
Genetic Algorithms (GA), Simulated Annealing (SA) and Particle Swarm Optimisation (PSO) are populati...
The general motivation of our work is to meet the main time constraint when implementing a control l...
Every possible problem can be considered to have a set of possible states by which amongst them, som...
In the last two decades, evolutionary based algorithms have proved to be an important tool in solvin...
In the past decade, evolutionary based algorithms have been a popular research theme in many discip...
The particle swarm optimisation algorithm is proposed as a new method to design a model based predi...
Particle Swarm Optimization (PSO) is an evolutionary computation technique, which has been inspired ...
Abstract:- Several Evolutionary Algorithms (EAs) are applied in the design and optimization of digit...
Despite the large number of existent design and tunig techniques, adequate PID controller tuning by ...
The particle swarm optimization (PSO) algorithm is a stochastic, population-based optimization techn...
During the last three decades there has been a growing interest in algorithms which rely on analogie...
Real-time implementations of controllers require optimization algorithms which can be performed quic...
This thesis investigates the hybrid application of stochastic and heuristic algorithms, in particula...
Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophistic...
ISBN: 978-1-84821-590-0The classic approach in Automatic Control relies on the use of simplified mod...
Genetic Algorithms (GA), Simulated Annealing (SA) and Particle Swarm Optimisation (PSO) are populati...
The general motivation of our work is to meet the main time constraint when implementing a control l...
Every possible problem can be considered to have a set of possible states by which amongst them, som...