http://hdl.handle.net/11422/90 Tue, 07 Apr 2026 03:40:05 GMT 2026-04-07T03:40:05Z http://hdl.handle.net/11422/27534 Title: Monitoring strategies in adaptive sliding mode control and event-triggered extremum seeking Author(s)/Inventor(s): Rodrigues, Victor Hugo Pereira Advisor: Hsu, Liu Abstract: This thesis proposes monitoring strategies for adaptive sliding mode controllers and event-triggered extremum seeking. The new adaptive sliding mode and unit vector controllers use output feedback for a class of nonlinear systems and can deal with parametric uncertainties and (un)matched disturbances with unknown upper bounds. Finite-time convergence of the tracking error to a predefined neighborhood of the origin of the closed-loop system is proved with guaranteed transient and steady-state performance. The novelty of our result lies on two important adaptation tools: monitoring and barrier functions. Simulation results including the application to Anti-lock Braking System and Overhead-crane to illustrate the advantages of the proposed adaptive control strategies. Finally, based on static maps, this thesis proposes event-triggered schemes for both scalar and multivariable extremum seeking. While the extremum seeking allows the output of a nonlinear map to be held within a vicinity of its extremum, the eventtriggered strategy is responsible to execute the control task aperiodically by using a monitoring mechanism. Static and dynamic triggering condition are developed. Integrating Lyapunov and averaging theories for discontinuous systems, a systematic design procedure and stability analysis are developed. Illustration of the benefits of the new control method are presented using consistent simulation results, which compare the static and the dynamic triggering approaches.Também disponível on-line. Publisher: Universidade Federal do Rio de Janeiro Type: Tese Wed, 01 Jun 2022 00:00:00 GMT http://hdl.handle.net/11422/27534 2022-06-01T00:00:00Z http://hdl.handle.net/11422/27533 Title: Avaliação de topologias de inversores para aplicação em sistemas fotovoltaicos Author(s)/Inventor(s): Ribeiro, Verônica Dias Gallotti Advisor: Suemitsu, Walter Issamu Abstract: Due to the trend of advancing photovoltaic energy in the coming years, both on account of the economy and the environment, the choice of which inverter to use becomes relevant, due to its importance in this energy generation. Therefore, it is essential to study and compare different topologies to analyze which one best respects certain requirements and conditions that one wants to obtain. To work with PV it is important that the inverters are buck and boost, however many inverters are just buck needing transformers or being two-stage to perform the function boost as well, but these two solutions have disadvantages. Therefore, the present work presents the study of two more recent inverters, which still do not have much literature on them, in which they do not need a transformer and are considered almost one-stage, in addition to being buck-boost. In this context, the performance of these inverters is verified, working as buck and as boost and their characteristics. Therefore, the approach used in this work showed two efficient inverters to be used in photovoltaic generation. The two inverters can work in a wide voltage range, in addition to not needing transformers, reducing cost and increasing efficiency. In addition to showing in the topology a reduction in the number of switches, volume of capacitors and less voltage stress, being great alternatives to be used in the future of photovoltaics and that people have more knowledge about these two inverters: TSTS-ZSI and ABI. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação Tue, 01 Feb 2022 00:00:00 GMT http://hdl.handle.net/11422/27533 2022-02-01T00:00:00Z http://hdl.handle.net/11422/27532 Title: Uso de redes neurais no cálculo da probabilidade de compra no cenário de comércio eletrônico brasileiro Author(s)/Inventor(s): Lourenço, Raphael Oliveira Advisor: Caloba, Luiz Pereira Abstract: Nowadays, the evolution in data processing makes machines become much more agile and e cient when collecting, manipulating and generating information data. Associated with this, with the spread of the use of digital media such as the internet, smartphones and mobile devices, there is a great ease in the exchange of information between people around the world. In addition, essentially, any internet browsing generates usage traces, which are recorded by the servers of several companies interested in understanding more about the behavior of individuals. On the other hand, the e-commerce landscape is extremely challenging from a sales generation point of view. On average, one purchase is made for every one hundred visits registered on the main online sales platforms in Brazil. However, with so much information available to be used, within the context of Marketing 3.0, it is possible to associate the use of Neural Networks within the context of sales optimization. Using real data from a large sales platform, this work proposed to explore the scenario of the Calculation of Probability of Purchase within e-commerce, thinking about using this information to in uence the purchase journey of individuals and, using a Feed-forward neural network with one hidden layer, obtained results interesting both from a quantitative point of view, with 0.904 of accuracy, 0.903 of recall, 0.906 of precision and 0.905 of F1, and from a qualitative point of view, where the distributions of purchase and non-purchase probabilities were quite consistent with the reality of the events. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação Tue, 01 Feb 2022 00:00:00 GMT http://hdl.handle.net/11422/27532 2022-02-01T00:00:00Z http://hdl.handle.net/11422/27531 Title: A contribution to model predictive controllers with fixed switching frequency and low computational cost Author(s)/Inventor(s): Tricarico, Thiago Cardoso Advisor: Aredes, Mauricio Abstract: This thesis proposes a new Model Predictive Control (MPC) technique for powerconverter applications, based on a recent meta-heuristic algorithm, called the Jaya algorithm, as the optimizer of MPC. The proposed solution presents three bene ts: simple implementation, viable computational cost, and xed switching frequency. The proposed MPC strategy, referred to as Jaya-MPC, stands out as an alternative to the classical Finite-Control-Set Model Predictive control (FCS-MPC), which presents a variable switching frequency. In addition, this work proposes a secondary contribution: a new metric, which assesses the spread of the switching frequency pro- le of power converters, i.e., it evaluates the variability of the switching frequency produced by MPC. This work uses this metric to investigate the switching frequency pro le of FCS-MPC. A straightforward parameter-setting method of the proposed algorithm rises from a parametric analysis, resulting in a high-power-quality solution. Also, this work compares the computational cost, based on the number of predictions, of both the proposed controller and the paradigm of MPC in power electronics. Experimental outcomes prove that Jaya-MPC is a simple-implementation technique with viable computational cost and high power quality. Publisher: Universidade Federal do Rio de Janeiro Type: Tese Fri, 01 Jul 2022 00:00:00 GMT http://hdl.handle.net/11422/27531 2022-07-01T00:00:00Z