Browsing by Author "Pinho, Tatiana M."
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- Comparative analysis between LDR and HDR images for automatic fruit recognition and countingPublication . Pinho, Tatiana M.; Coelho, João Paulo; Oliveira, Josenalde; Boaventura-Cunha, JoséPrecision agriculture is gaining an increasing interest in the current farming paradigm. This new production concept relies on the use of information technology (IT) to provide a control and supervising structure that can lead to better management policies. In this framework, imaging techniques that provide visual information over the farming area play an important role in production status monitoring. As such, accurate representation of the gathered production images is amajor concern, especially if those images are used in detection and classification tasks.Real scenes, observed in natural environment, present high dynamic ranges that cannot be represented by the common LDR (Low Dynamic Range) devices. However, this issue can be handled by High Dynamic Range (HDR) images since they have the ability to store luminance information similarly to the human visual system. In order to prove their advantage in image processing, a comparative analysis between LDR and HDR images, for fruits detection and counting, was carried out.The obtained results show that the use of HDR images improves the detection performance to more than 30% when compared to LDR.
- Controller system design using the coefficient diagram methodPublication . Coelho, João Paulo; Pinho, Tatiana M.; Boaventura-Cunha, JoséCoefficient diagram method is a controller design technique for linear time-invariant systems. This design procedure occurs into two different domains: an algebraic and a graphical. The former is closely paired to a conventional pole placement method and the latter consists on a diagram whose reading from the plotted curves leads to insights regarding closed-loop control system time response, stability and robustness. The controller structure has two degrees of freedom and the design process leads to both low overshoot closed-loop time response and good robustness performance regarding mismatches between the real system and the design model. This article presents an overview on this design method. In order to make more transparent the presented theoretical concepts, examples in Matlab®code are provided. The included code illustrates both the algebraic and the graphical nature of the coefficient diagram design method. © 2016, King Fahd University of Petroleum & Minerals.
- Forest-based supply chain modelling using the SimPy simulation frameworkPublication . Pinho, Tatiana M.; Coelho, João Paulo; Boaventura-Cunha, JoséProper management of supply chains is fundamental in the overall system performance of forestbased activities. Usually, efficient management techniques rely on a decision support software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains’ nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forestbased supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event systems using operations such as events, processes and resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic behaviours of processing and driving times were simulated. The obtained results validate the SimPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.
- FPGA implementation of a multi-population PBIL algorithmPublication . Coelho, João Paulo; Pinho, Tatiana M.; Boaventura-Cunha, JoséEvolutionary-based algorithms play an important role in finding solutions to many problems that are not solved by classical methods, and particularly so for those cases where solutions lie within extreme non-convex multidimensional spaces. The intrinsic parallel structure of evolutionary algorithms are amenable to the simultaneous testing of multiple solutions; this has proved essential to the circumvention of local optima, and such robustness comes with high computational overhead, though custom digital processor use may reduce this cost. This paper presents a new implementation of an old, and almost forgotten, evolutionary algorithm: the population-based incremental learning method. We show that the structure of this algorithm is well suited to implementation within programmable logic, as compared with contemporary genetic algorithms. Further, the inherent concurrency of our FPGA implementation facilitates the integration and testing of micro-populations.
- Hidden Markov models: theory and Implementation using MATLAB®Publication . Coelho, João Paulo; Pinho, Tatiana M.; Boaventura-Cunha, JoséThis book presents, in an integrated form, both the analysis and synthesis of three different types of hidden Markov models. Unlike other books on the subject, it is generic and does not focus on a specific theme, e.g. speech processing. Moreover, it presents the translation of hidden Markov models’ concepts from the domain of formal mathematics into computer codes using MATLAB®. The unique feature of this book is that the theoretical concepts are first presented using an intuition-based approach followed by the description of the fundamental algorithms behind hidden Markov models using MATLAB®. This approach, by means of analysis followed by synthesis, is suitable for those who want to study the subject using a more empirical approach.
- Model predictive control applied to a supply chain management problemPublication . Pinho, Tatiana M.; Coelho, João Paulo; Moreira, António Paulo G. M.; Boaventura-Cunha, JoséSupply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions. © Springer International Publishing Switzerland 2017
- Modelling a biomass supply chain through discrete-event simulationPublication . Pinho, Tatiana M.; Coelho, João Paulo; Moreira, António Paulo G. M.; Boaventura-Cunha, JoséThe organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided
- A multilayer model predictive control methodology applied to a biomass supply chain operational levelPublication . Pinho, Tatiana M.; Coelho, João Paulo; Veiga, Germano; Moreira, António Paulo G. M.; Boaventura-Cunha, JoséForest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs further optimization to become more competitive in the current energetic market. In this sense and taking into consideration the fact that the transportation is the process that accounts for the higher parcel in the biomass supply chain costs, this work proposes a multilayer model predictive control based strategy to improve the performance of this process at the operational level. The proposed strategy aims to improve the overall supply chain performance by forecasting the system evolution using behavioural dynamic models. In this way, it is possible to react beforehand and avoid expensive impacts in the tasks execution. The methodology is composed of two interconnected levels that closely monitor the system state update, in the operational level, and delineate a new routing and scheduling plan in case of an expected deviation from the original one. By applying this approach to an experimental case study, the concept of the proposed methodology was proven. This novel strategy enables the online scheduling of the supply chain transport operation using a predictive approach.
- A new brain emotional learning simulink toolbox for control systems designPublication . Coelho, João Paulo; Pinho, Tatiana M.; Boaventura-Cunha, José; Oliveira, JosenaldeThe brain emotional learning (BEL) control paradigm has been gathering increased interest by the control systems design community. However, the lack of a consistent mathemat- ical formulation and computer based tools are factors that have prevented its more widespread use. In this article both features are tackled by providing a coherent mathematical framework for both the continuous and discrete-time formulations and by presenting a Simulink R computational tool that can be easily used for fast prototyping BEL based control systems.
- Optimized fractional order sliding mode controller for water level in irrigation canal poolPublication . Oliveira, Josenalde; Pinho, Tatiana M.; Coelho, João Paulo; Boaventura-Cunha, JoséWater level regulation of irrigation canals represents a major challenge for control systems design. Those systems exhibit large dynamic variations in their operating conditions. To overcome this fact, robust controllers should be applied. The sliding mode control paradigm reveals this ability which make it a suitable candidate to be incorporated in the irrigation canal control loop. Moreover, its exibility can be further potentiated by extending the ordinary formulation by adding fractional-order integro-di erential operations. In this work, fractionalorder sliding mode control is applied to the above mentioned problem. This application represents a novelty and, according to the obtained simulation results, leads to an accurate and proper performance when compared to its integer-order counterpart and to a fractional proportional-integrative controller, recently proposed for this problem.