Browsing by Author "Oliveira, Paulo de Moura"
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- Algoritmos para a previsão da carga térmica solar em estufas agrícolasPublication . Coelho, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de MouraO desenvolvimento de modelos matemáticos que descrevam eficazmente a dinâmica do comportamento ambiental de estufas agrícolas tem vindo, nos últimos anos, a merecer cada vez mais atenção. A razão desta orientação passa pela necessidade de desenvolver estratégias de controlo mais evoluídas que garantam condições óptimas para o crescimento das plantas e propiciem um uso mais racional da energia despendida na regulação Ambiental.
- Automation and control of the SORTEGEL wastewater plantPublication . Araújo, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de Moura; Pires, Eduardo S.; Coelho, João PauloFood Processing Industries produce large amounts of wastewater with high environmental impact. Due to the high content of suspended matter and inadequate pH value of the wastewater, national laws prohibit direct discharges of the influent to the environment. This work describes the design and operation of a wastewater treatment plant installed in the Sortegel food-processing company located in Sortes, Portugal. This industry uses the water collected from groundwater wells to process raw materials and to wash the equipments, being the volume of wastewater produced season dependent (80 to 300m3/day). Results show that the implemented wastewater treatment plant and the automation solutions generate treated effluents that comply with the Portuguese legislation.
- Design of PID controllers using the particle swarm algorithmPublication . Coelho, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de MouraParticle swarm optimization is proposed as an alternative technique to the controller design for single-imput single-output systems.
- Experimental setup for turbocharger controlPublication . Coelho, João Paulo; Giernacki, Wojciech; Cunha, José Boaventura; Oliveira, Paulo de MouraThe way people travel is about to change. Since the early beginning of the twentieth century, two nowadays, the automobile has become the most prolific transportation form. The propulsion is done by an internal combustion engine which converter thermal energy, by burning diesel or petrol, into mechanical energy. However, due to several reasons reasons such as economical, envoronmental among others, there is a tendency to replace the i9nternal combustion engine by electrically powered motors. Electrical motors have many properties. One of them is its efficiency. An electric motor can easily reach an efficiency above 80% against to average 40% for internal combustion engines. Nevertheless, at the present, there are serious limitations regarding electric engine cars proliferation. There acquisition cost and autonomy are still two major restrictions. Even if the former aspect can be attenuated by proper tax reduction policies, the is strongly dependent of technical issues i.e. the development of faster methods, longer life batteries, etc.
- Extended stability conditions for CDM controller designPublication . Coelho, João Paulo; Boaventura-Cunha, José; Oliveira, Paulo de MouraThe coefficient diagram method (CDM) is one of the easiest methods for model based control system design. Its core is based on an algebraic method but it also encompasses a graphical analysis diagram that helps the user to evaluate the three main closed-loop system requirements: dynamic behaviour, robustness and stability. This later characteristic is analysed by a set of stability conditions derived from the previous work of Lipatov and Sokolov on sufficient conditions for stability. However, in CDM, only a fraction of the total conditions are considered. This work will show that this fact increases the inconclusive area within the stability space. Moreover an extended set of CDM stability conditions, in conjunction with its graphical interpretation, will be presented
- Greenhouse air temperature control using the particle swarm optimisation algorithmPublication . Coelho, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de MouraThis work presents a scheme for temperature control of a greenhouse located in the North of China. Since the treated greenhouse is a nonlinear system and subjects to strong external disturbances, a nonlinear model predicative control algorithm based on particle swarm optimization (PSO) is applied to solve the constrained nonlinear optimization problem. Its performance is compared with the ones obtained by using sequential quadratic programming (SQP) algorithm. PSO can get the global minimum quickly while SQP is going to be trapped in local minimum point. Simulations with the proposed method to design the model predictive temperature controller are presented and the result of it shows the effectiveness.
- Greenhouse air temperature control using the particle swarm optimisation algorithmPublication . Coelho, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de MouraThe 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 minimisation of the control effort over a prediction horizon of one hour with a one-minute sampling period.
- Greenhouse air temperature modellingPublication . Cunha, José Boaventura; Oliveira, Paulo de Moura; Coelho, João PauloThis 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 heating and cooling. Results are presented to illustrate the performance of each model in the simulation and prediction of the greenhouse air temperature. The data used to compute the simulation models was collected with a PC-based acquisition and control system using a sampling time interval of 1 minute.
- Greenhouse heat load prediction using a support vector regression modelPublication . Coelho, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de Moura; Pires, Eduardo S.Modern greenhouse climate controllers are based on models in order to simulate and predict the greenhouse environment behaviour. These models must be able to describe indoor climate process dynamics, wchich are a function of the both the control actions taken and the outside climate. Moreover, if predictive or feedforward control techniques are to be applied, it is necessary to employ models to describe and predict the weather. From all the climate variables, solar radiation is the one with greater impact in the greenhouse heat load. Hence, making good predictions of this physical quantity is of extreme importance. In this paper, the solar radiation is represented as a time-series and a support vector regression model is used to make long term predictions. Results are compared with the ones achieved by using other type of models, both linear and non-linear.
- Hardware-in-the-loop control using the particle swarm optimisationPublication . Coelho, João Paulo; Cunha, José Boaventura; Oliveira, Paulo de MouraIn 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.
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