A radio base station (RBS) may become overloaded if too many mobile devices communicate with it at the same time. This could happen at for instance sport events or in the case of accidents. To prevent CPU overload, the RBS is provided with a controller that adjusts the acceptance rate, the maximum number of connection requests that can be accepted per time interval. The current controller is tuned in real radio base stations and the procedure is both time consuming and expensive. This, combined with the fact that the mobile data usage is predicted to increase puts more pressure on today's system. Thus, there is a need to be able to simulate the system in order to suggest an alternative controller. In this thesis, an implementation of the system is developed in Matlab in order to simulate the RBS system load control behaviour. A CPU load model is estimated using system identification. The current version of the CPU load controller and an alternative PI CPU load controller are implemented. Both are evaluated on different test cases and this shows that it is possible to increase the performance of the system with the alternative CPU load controller, both in terms of lower amount of rejected connection requests and decreased CPU load overshoot.

As traditional control schemes, open-loop Hysteresis and closed-loop pulse-width-modulation (PWM) have been used for the switched reluctance motor (SRM) current controller. The Hysteresis controller induces large unpleasant audible noises because it needs to vary the switching frequency to maintain constant Hysteresis current band. In contract, the PWM controller is very quiet but difficult to design proper gains and control bandwidth due to the nonlinear nature of the SRM. In this thesis, the ac small signal modeling technique is proposed for linearization of the SRM model such that a conventional PI controller can be designed accordingly for the PWM current controller. With the linearized SRM model, the duty-cycle to output transfer function can be derived, and the controller can be designed with sufficient stability margins. The proposed PWM controller has been simulated to compare the performance against the conventional Hysteresis controller based system. It was found that through the frequency spectrum analysis, the noise spectra in audible range disappeared with the fixed switching frequency PWM controller, but was pronounced with the conventional Hysteresis controller. A hardware prototype is then implemented with digital signal processor to verify the quiet nature of the PWM controller when running at 20 kHz switching frequency. The experimental results also indicate a stable current loop operation. / Master of Science

In this thesis, an optimal multivariable current control method is presented for the highspeed permanent magnet synchronous motor (HS-PMSM). The HS-PMSMs have growing applications in the industry. One of their major challenges is the low switching to fundamental frequency ratio (SFR). At high speed and low SFR, the control time delays including the digital, the PWM, and sensor delays become more pronounced and lead to oscillations and even instabilities. A well-known method for delay compensation is to advance the phase angle of control input for a known amount. In practice, the exact delay is unknown, and mismatch in the compensating angle causes deteriorating effect on the system. In the proposed method, the digital and PWM delays are modelled and integrated with an optimal multivariable controller. This method improves the stability margin and achievable speed margin compared to the traditional phase advancing delay compensation (PADC) method. Combining the proposed delay modeling and the PADC method further improves the response, as the uncertain sensor delays can be compensated greatly. Besides the delay, the cross-coupling between ���� axis affects the dynamic performance of the machine. The proposed multivariable approach considers and directly addresses the coupling. Dynamic performance of the PMSM with the proposed method is thoroughly compared with the conventional delay compensation method. The proposed method is validated through extensive simulation studies on a 2 kW high-speed machine.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2016-02-18T07:02:36Z No. of bitstreams: 2 Dissertação - Márcio Rodrigues da Cunha Reis - 2014.pdf: 19219511 bytes, checksum: 8b91b891ec367ebc7de924c8b641876c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-02-18T07:04:08Z (GMT) No. of bitstreams: 2 Dissertação - Márcio Rodrigues da Cunha Reis - 2014.pdf: 19219511 bytes, checksum: 8b91b891ec367ebc7de924c8b641876c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2016-02-18T07:04:08Z (GMT). No. of bitstreams: 2 Dissertação - Márcio Rodrigues da Cunha Reis - 2014.pdf: 19219511 bytes, checksum: 8b91b891ec367ebc7de924c8b641876c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-10-06 / Financiadora de Estudos e Projetos- Finep / This paper presents a comparative analysis of some methodologies for deterministic and heuristic optimization, applied to a classic problem in control theory. The aim is to determine the parameters tuning Proportional and Integral (PI) controller. The PI controller is used to control the speed of the DC motor. The mathematical model of the DC motor and the independent excitation of the AC-DC converter that is used in driving it is developed. From the mathematical model, the computational model is developed to perform the analysis of a commercial DC motor. In order to validate the computational model, a training bench is built, tests are performed and the results of the comparison between the methods of optimization are presented. / Este trabalho apresenta a an alise comparativa de algumas metodologias de otimiza- c~ao determin stica e heur stica, aplicadas a um problema cl assico da teoria de controle. O intuito e determinar os par^ametros de sintonia do controlador Proporcional e Integral (PI). O controlador PI e utilizado para controlar a velocidade do motor de corrente cont nua. E desenvolvido o modelo matem atico do motor de corrente cont nua de excita c~ao independente e do conversor CA-CC que e utilizado em seu acionamento. A partir do modelo matem atico, e desenvolvido o modelo computacional, para realizar a an alise de um motor CC comercial. A m de validar o modelo computacional, uma bancada did atica e constru da, ensaios s~ao realizados e os resultados da compara c~ao entre os m etodos de otimiza c~ao s~ao apresentados.

There are many forms of speed control for an autonomous ground vehicle currently in development. Most use a simple PID controller to achieve a speed specified by a higher-level motion planning algorithm. Simple controllers may not provide a desired acceleration profile for a ground vehicle. Also, without extensive tuning the PID controller may cause excessive speed overshoot and oscillation. This paper examines an approach that was designed to allow a greater degree of control while reducing the computing load on the motion planning software. The SpAM+PI (Speed-based Acceleration Map + Proportional Integral controller) algorithm outlined in this paper uses three inputs: current velocity, desired velocity and desired maximum acceleration, to determine throttle and brake commands that will allow the vehicle to achieve its correct speed. Because this algorithm resides on an external controller it does not add to the computational load of the motion planning computer. Also, with only two inputs that are needed only when there is a change in desired speed or maximum desired acceleration, network traffic between the computers can be greatly reduced. The algorithm uses splines to smoothly plan a speed profile from the vehicle's current speed to its desired speed. It then uses a lookup table to determine the correct pedal position (throttle or brake) using the current vehicle speed and a desired instantaneous acceleration that was determined in the splining step of the algorithm. Once the pedal position is determined a PI controller is used to minimize error in the system. The SpAM+PI approach is a novel approach to the speed control of an autonomous vehicle. This academic experiment is tested using Odin, Team Victor Tango's entry into the 2007 DARPA Urban Challenge which won 3rd place and a $500,000 prize. The evaluation of the algorithm exposed both strengths and weaknesses that guide the next step in the development of a speed control algorithm. / Master of Science

Constrained optimization is pivotal in deep learning for enforcing predefined operational, ethical, and regulatory constraints in models. This thesis explores iterative gradient-based methods for solving constrained optimization. These methods are preferred for their adaptability in the non-convex, stochastic, and high-dimensional learning landscape of neural networks. Lagrangian methods, which integrate constraints directly into the objective function using Lagrange multipliers, are particularly effective. This formulation facilitates a unified approach to handle both the model's performance and its adherence to constraints simultaneously. However, the min-max problems inherent in Lagrangian frameworks often suffer from unstable oscillatory dynamics. Solving them using traditional gradient descent-ascent methods potentially leads to suboptimal convergence and prolonged training times. To mitigate these issues, this thesis introduces the νPI algorithm, a novel algorithm that integrates Proportional-Integral (PI) control theory into the optimization of Lagrange multipliers. The νPI algorithm is designed to stabilize the optimization process by adjusting the updates to the Lagrange multipliers based on the current and past constraint violations, effectively dampening the oscillations typically observed with gradient descent-ascent methods. Experimental validations across various deep learning applications demonstrate that νPI not only stabilizes the learning process but also accelerates convergence to optimal or near-optimal solutions, outperforming traditional methods in terms of reliability and speed. Through its application, νPI proves to be a robust tool in managing the dynamics of constrained optimization, enhancing the capability of deep learning models to meet stringent external constraints. / L’optimisation contrainte est essentielle dans l’apprentissage profond pour faire respecter les contraintes opérationnelles, éthiques et réglementaires prédéfinies dans les modèles. Cette thèse explore les méthodes itératives basées sur le gradient pour résoudre l’optimisation contrainte. Ces méthodes sont privilégiées pour leur adaptabilité dans le paysage d’apprentissage non convexe, stochastique et de haute dimension des réseaux neuronaux. Les méthodes lagrangiennes, qui intègrent directement les contraintes dans la fonction objectif à l’aide de multiplicateurs de Lagrange, sont particulièrement efficaces. Cette formulation facilite une approche unifiée pour gérer simultanément la performance du modèle et son adhérence aux contraintes. Cependant, les problèmes min-max inhérents aux cadres lagrangiens souffrent souvent de dynamiques oscillatoires instables. Leur résolution à l’aide des méthodes traditionnelles de descente de gradient-ascent peut potentiellement conduire à une convergence sous-optimale et à des temps de formation prolongés. Pour atténuer ces problèmes, cette thèse introduit l’algorithme νPI, un nouvel algorithme qui intègre la théorie de contrôle Proportionnel-Intégral (PI) dans l’optimisation des multiplicateurs de Lagrange. L’algorithme νPI est conçu pour stabiliser le processus d’optimisation en ajustant les mises à jour des multiplicateurs de Lagrange en fonction des violations de contraintes actuelles et passées, atténuant efficacement les oscillations typiquement observées avec les méthodes de descente de gradient-ascent. Les validations expérimentales à travers diverses applications d’apprentissage profond démontrent que νPI stabilise non seulement le processus d’apprentissage mais accélère également la convergence vers des solutions optimales ou quasi-optimales, surpassant les méthodes traditionnelles en termes de fiabilité et de vitesse. Grâce à son application, νPI se révèle être un outil robuste pour gérer les dynamiques de l’optimisation contrainte, améliorant la capacité des modèles d’apprentissage profond à répondre à des contraintes externes strictes.

Baigiamojo magistro darbo tiriamasis objektas – intelektinė tiesiaeigė elektros pavara. Tyrimo tikslas – ištirti tiesiaeigę elektros pavarą, valdoma neraiškiuoju reguliatoriumi. Uždaviniai – sudaryti intelektinės tiesiaeigės pavaros kompiuterinį modelį gauti ir ištirti imitacijos rezultatus, juos palyginti su tokia pačia PI reguliatoriumi valdoma pavara. Literatūros analizės dalyje išnagrinėtas neraiškiosios logikos panaudojimas valdant elektros pavaras. Pateikiami straipsniai, kuriose aprašomos elektros pavarų valdymo galimybės panaudojant neraiškiosios logikos reguliatorius. Teorinėje dalyje išnagrinėjamos tiesiaeigės pavaros, pateikiamos jų taikymo apžvalga ir panaudojimo galimybės. Taip pat išanalizuojamos neraiškiosios valdymo sistemos, jų sudarymo principai ir panaudojimas reguliatoriuose. Aptariami tiesiaeigių elektros pavarų valdymo būdai. Tiriamojoje dalyje sukurtas tiesiaeigės pavaros kompiuterinis modelis, suprojektuotas neraiškusis reguliatorius, gauti imitacijos rezultatai. Rezultatams palyginti sudarytas pavaros modelis naudojant PI reguliatorių. Gauti rezultatai ištirti ir palyginti. Išnagrinėjus tiesiaeigės asinchroninės pavaros imitavimo rezultatus pateikiamos išvados ir pasiūlymai. Darbą sudaro 7-ios dalys: įvadas, literatūros analizė, tyrimo tikslas ir uždaviniai, teorinė dalis, tiriamoji dalis, apibendrinančioji dalis, naudotos literatūros šaltinių sąrašas. Darbo apimtis – 65 psl. teksto be priedų, 43 iliustr., 2 lent., 37 bibliografiniai šaltiniai, iš jų... [toliau žr. visą tekstą] / Research subject of master thesis is intelligent linear electric drive. Objective of the study - to investigate linear electric actuator, controlled with Fuzzy controller. Tasks - create computer model of intellectual linear drive, to investigate the simulation results and compare them with the same drive which controlled with PI controller. In the literary analysis part usage of Fuzzy logic in the electric drives control has been examined. Articles with description of the electric drive control features using Fuzzy logic controller have been given. In the theoretical part the linear actuators are analyzed, the review of the application and their usability was given. Also are analyzed Fuzzy control systems, their creation principles and usage in the regulators. The linear electric drive control methods are discussed. In the research part computer model of the linear drive has developed, designed Fuzzy controller, analyzed simulation results. For results comparing the model with PI controller has designed. The results obtained are examined and compared. After examination results of the linear induction drive simulation the conclusions and recommendations are given. The work consists of seven parts: introduction, literature review, the study aims and objectives, the theoretical part, research, generalization and used references. Thesis volume - 65 pages text without appendixes, 43 pictures, 2 tables, 37 bibliographical sources, including internet links 10. Appendixes are... [to full text]

Os processos de fermentação em estado sólido (FES) existem há muitos séculos nas civilizações orientais, onde têm sido amplamente utilizados na produção de gêneros alimentícios. No ocidente, a indústria tem trabalhado preferencialmente com os processos de Fermentação Submersa (FS) porque, devido ao meio ser aquoso, existem facilidades para se controlar esse tipo de processo. No entanto, novas demandas (tais como o tratamento de resíduos sólidos) não são inteiramente contempladas pela FS. Por outro lado, os processos de FES podem ser descritos como o crescimento de microorganismos em substratos sólidos na ausência de água livre, podendo suprir essas demandas. Entretanto, também devido a essa característica, a maior dificuldade encontrada é o controle das variáveis internas do biorreator (como, por exemplo, a remoção do calor produzido pela atividade biológica). As pesquisas nesse campo mostram que essa remoção é mais fácil através das trocas pelo ar, por causa das dificuldades de condução térmica em meio sólido. Portanto, torna-se necessário o desenvolvimento de sistemas de controle da aeração que permitam a avaliação dos processos em escala de bancada, diminuindo assim o número de incertezas na modelagem e simulação do processo. Com melhores modelos do processo em escala de bancada, torna-se mais fácil o controle da temperatura no leito de um biorreator de maior escala. Esse trabalho tem por objetivo aplicar uma técnica de controle robusto que seja capaz de garantir os índices de desempenho do sistema em toda a faixa operacional do fluxo e da temperatura ar do biorreator. A planta do sistema foi modelada em nove diferentes condições de temperatura e aeração através de modelos de primeira ordem sem atraso. Esses índices são: tempo de acomodação inferior a 12000 segundo e sobressinal inferior a 10%. O controlador utilizado foi do tipo Proporcional Integrativo (PI). Esse controlador foi sintonizado utilizando a metodologia LMI (do inglês Linear Matrix Inequalities) ou Desigualdades Matriciais Lineares, através das restrições elaboradas no algoritmo iterativo V-K. Os resultados da implementação mostram que as restrições utilizadas no algoritmo são capazes de sintonizar o controlador, mesmo não se conhecendo todas as dinâmicas do sistema de aeração. / The solid-state fermentation (SSF) processes have existed for centuries in Eastern civilizations and have been widely used in the production of foodstuffs. In Western, the industry has worked preferably with the submerged fermentation (SF) processes, because it occurs in aqueous medium and it facilitates the bioreactor control. However, new demands, such as solid waste management, are not fully covered by FS. On the other hand, the processes of FES can be described as the growth of microorganisms on solid substrates in the absence of free water, which can meet this demand. But because of this characteristic, the greater difficulty is the bioreactors internal variables control and the major one the removal of the heat produced by biological activity. Researches in this field show that removal is easier through air exchange, because of the difficulties of thermal conduction in a solid medium. Therefore, it becomes necessary to develop an aeration control system that allows processes evaluation in bench scale, thereby reducing the number of uncertainties in modeling and simulation process. Thus, facilitating the temperature control of a larger-scale bioreactors bed. The aim of this work is to apply a robust control technique that guarantees the systems performance indexes throughout the air flow and temperature operational range. The plant was modeled on a first-order system without delay, at nine different conditions of temperature and aeration. These indixes are: settling time less than 12000 seconds and overshoot less than 10%. The controller used was a Proportional Integrative (PI) type. This controller was tuned using the LMI methodology (Linear Matrix Inequalities) through the V-K iterative algorithm restrictions. The implementation results show that the restrictions used in the algorithm are able to tune the controller, even not knowing all the dynamics of the aeration system.

Orientador: Prof. Dr. Alfeu J. Sguarezi Filho / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2014. / O Controle Direto de Torque é uma das técnicas mais avançadas em acionamentos para motores de indução trifásicos, pois tem como característica principal uma resposta rápida as exigências de torque eletromagnético o que permite um controle com maior precisão da velocidade. Este trabalho apresenta o Controle Direto de Torque baseado no controle do ângulo da carga com a utilização de controladores do tipo proporcional-integral (PI). Esta estratégia baseia-se na análise do erro encontrado entre torque eletromagnético de referência e torque eletromagnético estimado que é processado por um controlador que gera um ângulo de carga. O fluxo do estator em coordenadas estacionárias é calculado a partir de sua magnitude e com o ângulo, gerado pelo controlador PI mencionado, é somado ao ângulo do rotor. O fluxo do estator de referencia é comparado ao fluxo do estator estimado e um controlador PI processa o erro de forma a gerar a tensão de estator em coordenadas estacionárias de forma que as referências de torque e fluxo sejam atendidas. Com base em um modelo computacional foram realizadas simulação para validar a eficiência da estratégia proposta, resultados obtidos demonstram o comportamento transitório e em regime das correntes, torque eletromagnético e velocidade do motor. Também foram realizados testes em bancada para validar o controlador proposto. / The Direct Torque Control is one of the most advanced techniques for three-phase induction motors drives, due its main characteristic in which it has a quick response to requirements electromagnetic torque which allows a control of the speed with greater precision. This work presents the direct torque control based on load angle control with the use proportional-integral (PI) controllers. This strategy is based on the analysis of an error found between the reference of electromagnetic torque and the measured torque that is processed by a controller that generates an electromagnetic torque load angle. The stator flux in stationary coordinates is calculated from the magnitude and the angle generated by a PI controller that is added to the rotor angle. The stator flux reference is compared to the estimated stator flux and a PI controller processes this error an calculates the stator voltage in stationary stator coordinates so that the flux and torque references are attended. The study is made using computer simulations of the proposed controller and experimental results are carried out to validate the estrategy.

Os processos de fermentação em estado sólido (FES) existem há muitos séculos nas civilizações orientais, onde têm sido amplamente utilizados na produção de gêneros alimentícios. No ocidente, a indústria tem trabalhado preferencialmente com os processos de Fermentação Submersa (FS) porque, devido ao meio ser aquoso, existem facilidades para se controlar esse tipo de processo. No entanto, novas demandas (tais como o tratamento de resíduos sólidos) não são inteiramente contempladas pela FS. Por outro lado, os processos de FES podem ser descritos como o crescimento de microorganismos em substratos sólidos na ausência de água livre, podendo suprir essas demandas. Entretanto, também devido a essa característica, a maior dificuldade encontrada é o controle das variáveis internas do biorreator (como, por exemplo, a remoção do calor produzido pela atividade biológica). As pesquisas nesse campo mostram que essa remoção é mais fácil através das trocas pelo ar, por causa das dificuldades de condução térmica em meio sólido. Portanto, torna-se necessário o desenvolvimento de sistemas de controle da aeração que permitam a avaliação dos processos em escala de bancada, diminuindo assim o número de incertezas na modelagem e simulação do processo. Com melhores modelos do processo em escala de bancada, torna-se mais fácil o controle da temperatura no leito de um biorreator de maior escala. Esse trabalho tem por objetivo aplicar uma técnica de controle robusto que seja capaz de garantir os índices de desempenho do sistema em toda a faixa operacional do fluxo e da temperatura ar do biorreator. A planta do sistema foi modelada em nove diferentes condições de temperatura e aeração através de modelos de primeira ordem sem atraso. Esses índices são: tempo de acomodação inferior a 12000 segundo e sobressinal inferior a 10%. O controlador utilizado foi do tipo Proporcional Integrativo (PI). Esse controlador foi sintonizado utilizando a metodologia LMI (do inglês Linear Matrix Inequalities) ou Desigualdades Matriciais Lineares, através das restrições elaboradas no algoritmo iterativo V-K. Os resultados da implementação mostram que as restrições utilizadas no algoritmo são capazes de sintonizar o controlador, mesmo não se conhecendo todas as dinâmicas do sistema de aeração. / The solid-state fermentation (SSF) processes have existed for centuries in Eastern civilizations and have been widely used in the production of foodstuffs. In Western, the industry has worked preferably with the submerged fermentation (SF) processes, because it occurs in aqueous medium and it facilitates the bioreactor control. However, new demands, such as solid waste management, are not fully covered by FS. On the other hand, the processes of FES can be described as the growth of microorganisms on solid substrates in the absence of free water, which can meet this demand. But because of this characteristic, the greater difficulty is the bioreactors internal variables control and the major one the removal of the heat produced by biological activity. Researches in this field show that removal is easier through air exchange, because of the difficulties of thermal conduction in a solid medium. Therefore, it becomes necessary to develop an aeration control system that allows processes evaluation in bench scale, thereby reducing the number of uncertainties in modeling and simulation process. Thus, facilitating the temperature control of a larger-scale bioreactors bed. The aim of this work is to apply a robust control technique that guarantees the systems performance indexes throughout the air flow and temperature operational range. The plant was modeled on a first-order system without delay, at nine different conditions of temperature and aeration. These indixes are: settling time less than 12000 seconds and overshoot less than 10%. The controller used was a Proportional Integrative (PI) type. This controller was tuned using the LMI methodology (Linear Matrix Inequalities) through the V-K iterative algorithm restrictions. The implementation results show that the restrictions used in the algorithm are able to tune the controller, even not knowing all the dynamics of the aeration system.