A new scheme of fuzzy optimal control for the temperature of an Agriculture Greenhouse is presented. The proposed method is based on the Pontryagin’s Minimum Principle (PMP) that is used to train an adaptive fuzzy inference system to estimate values for the optimal co-state variables. This work shows that it is possible to successfully control a greenhouse by using these techniques. A method is presented to con...
Nowadays, a substantial part of the agricultural production takes place in greenhouses, which enable to tune the crop growing by modifying, artificially, the environmental conditions and the plant’s nutrition. The main goal is to optimise the balance between the production economic return and the operation costs of the climate actuators. Severe environment and market restrictions jointly with an increasing tend...
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 pa...
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 par...
In the past decade, evolutionary based algorithms have been a popular research theme in many disciplinary areas like control systems. Although, due to the computational load required, this type of algorithms usually are applied off-line. In this paper, a stochastic search algorithm known as particle swarm is used as an optimisation tool for on-line control of a custom made laboratory thermodynamic system.
Main adaptive control design approaches assume that a suitable dynamic model of the controlled process can be computed. In this way, recursive parameter estimation algorithms play can important role in tracking the time variant parameters of the process dynamic model. Thois paper describes the major algorithms used to compute the ttransfer function parameters of time varying ssssystems. The advantages and limit...
This paper describes two implementation approaches for modelling the air temperature of an automated greenhouse located in the campus of the University of Trás-os- Montes e Alto Douro. Linear models, based in the discretization of the heat transfer physical laws, and non-linear neural networks models are used. These models are describes as functions of the outside climate and control actions performed for heati...
Neste artigo abordam-se duas metodologias de desenvolvimento e implementação de modelos dinâmicos da temperatura do ar em estufas para aplicação em sistemas de gestão e controlo ambiental. O estudo é restrito a modelos lineares baseados na discretização das leis físicas de transferência de calor e em modelos não lineares baseados em redes neuronais. Os modelos são descritos como funções do clima exterior e das ...
The particle swarm optimisation algorithm is proposed as a new method to design a model based predictive controller subject to restrictions. Its performance is compared with the one obtained by using a genetic algorithm for the environmental temperature control of a greenhouse. Controller outputs are computed in order to optimise future behaviour of the greenhouse environment, regarding set-point tracking and m...
Particle swarm optimization is proposed as an alternative technique to the controller design for single-imput single-output systems.
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