Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: A mineral concentrate drying process consisting of a hot gas generator, a flash dryer and a feeding section is found to be the bottleneck in the platinum concentrate smelting process. This operation is used as a case study for system identification and model-based control of dryers. Based on the availability of a month's worth of dryer data obtained from a historian, a third party modelling and control software vendor is interested in the use of this data for data driven model construction and options for dryer control. The aimed contribution of this research is to use only data driven techniques and attempt an SID experiment and use of this model in a controller found in literature to be applicable to the dryer process. No first principle model was available for simulation or interpretation of results. Data were obtained for the operation from the plant historian, reduced, cleaned and investigated for deterministic information through surrogate data comparison – resulting in usable timeseries from the plant data. The best datasets were used for modelling of the flash dryer and hot gas generator operations individually, with the hot gas generator providing usable results. The dynamic, nonlinear autoregressive models with exogenous inputs were identified by means of a genetic programming with orthogonal least squares toolbox. The timeseries were reconstructed as a latent variable set, or “pseudo-embedding”, using the delay parameters as identified by average mutual information, autocorrelation and false nearest neighbours. The latent variable reconstruction resulted in a large solution space, which need to be investigated for an unknown model structure. Genetic Programming is capable of identifying unknown structures. Freerun prediction stability and sensitivity analysis were used to assess the identified best models for use in model based control. The best two models for the hot gas generator were used in a basic model predictive controller in an attempt to only track set point changes. One step ahead modelling of the flash dryer outlet air temperature was unsuccessful with the best model obtaining a validation R2 = 43%. The lack of process information contained in the available process variables are to blame for the poor model identification. One-step ahead prediction of the hot gas generator resulted in a top model with validation R2 = 77.1%. The best two hot gas generator models were implemented in a model predictive controller constructed in a real time plant data flow simulation. This controller's performance was measured against set point tracking ability. The MPC implementation was unsuccessful due to the poor freerun prediction ability of the models. The controller was found to be unable to optimise the control moves using the model. This is assigned to poor model freerun prediction ability in one of the models and a too complex freerun model structure required. It is expected that the number of degrees of freedom in the freerun model is too much for the optimiser to handle. A successful real time simulation architecture for the plant dataflow could however be constructed in the supplied software. It is recommended that further process measurements, specifically feed moisture content, feed temperature and air humidity, be included for the flash dryer; closed loop system identification be investigated for the hot gas generator; and a simpler model structure with smaller reconstructed latent variable regressor set be used for the model predictive controller. / AFRIKAANSE OPSOMMING: 'n Drogings proses vir mineraal konsentraat bestaan uit drie eenhede: 'n lug verwarmer-, 'n blitsdroeër- en konsentraat toevoer eenheid. Hierdie droeër is geïdentifiseer as die bottelnek in die platinum konsentraat smeltingsproses. Die droeër word gebruik as 'n gevallestudie vir sisteem identifikasie asook model-gebasseerder beheer van droeërs. 'n Maand se data verkry vanaf die proses databasis, het gelei tot 'n derde party industriële sagteware en beheerstelsel maatskappy se belangstelling in data gedrewe modelering en beheer opsies vir die drogings proses. Die doelwit van hierdie studie is om data gedrewe modeleringstegnieke te gebruik en die model in 'n droeër-literatuur relevante beheerder te gebruik. Geen eerste beginsel model is beskikbaar vir simulasie of interpretasie van resultate nie. Die verkrygde data is gereduseer, skoon gemaak en bestudeer om te identifiseer of die tydreeks deterministiese inligting bevat. Dit is gedoen deur die tydreeks met stochastiese surrogaat data te vergelyk. Die mees gepaste datastelle is gebruik vir modellering van die blitsdroeër en lugverwarmer afsonderlik. Die nie-liniêre, dinamiese nie-linieêre outeregressie modelle met eksogene insette was deur 'n genetiese programmering algoritme, met ortogonale minimum kwadrate, identifiseer. Die betrokke tydreeks is omskep in 'n hulp-veranderlike stel deur gebruik te maak van vertragings-parameters wat deur gemiddelde gemeenskaplike inligting, outokorrelasie en vals naaste buurman metodes verkry is. Die GP algoritme is daartoe in staat om the groot oplossings ruimte wat deur hierdie hulp-veranderlike rekonstruksie geskep word, te bestudeer vir 'n onbekende model struktuur. Die vrye vooruitskattings vermoë, asook die model sensitiwiteit is inag geneem tydens die analiese van die resultate. Die beste modelle se gepastheid tot model voorspellende beheer is gemeet deur die uitkomste van 'n sensitiwiteits analise, asook 'n vrylopende voorspelling, in oënskou te neem. Die een-stap vooruit voorspellende model van die droeër was onsusksesvol met die beste model wat slegs 'n validasie R2 = 43% kon behaal. Die gebrekkige meet instrumente in die droeër is te blameer vir die swak resultate. Die een-stap vooruit voorspellende model van die lug verwarmer wat die beste gevaar het, het 'n validasie R2 = 77.1% gehad. 'n Basiese model voorspellende beheerder is gebou deur die 2 beste modelle van slegs die lugverwarmer te gebruik in 'n intydse simulasie van die raffinadery data vloei struktuur. Hierdie beheerder se vermoë om toepaslike beheer uit te oefen, is gemeet deur die slegs die stelpunt te verander. Die beheerder was egter nie daartoe in staat om die insette te optimeer, en so die stelpunt te volg nie. Hierdie onvermoë is as gevolg van die kompleks vrylopende model struktuur wat oor die voorspellingsvenster optimeer moet word, asook die onstabiele vryvooruitspellings vermoë van die modelle. Die vermoede is dat die loslopende voorspelling te veel vryheids grade het om die insette maklik genoeg te optimeer. Die intydse simulasie van die raffinadery se datavloei struktuur was egter suksesvol. Beter meting van noodsaaklike veranderlikes vir die droër, o.a. voginhoud van die voer, voer temperatuur, asook lug humiditeit; geslotelus sisteem identifikasie vir die lugverwarmer; asook meer eenvoudige model struktuur vir gebruik in voorspellende beheer moontlik vermag deur 'n kleiner hulp veranderlike rekonstruksie te gebruik.

A novel electromechanical brake (EMB) based on the eddy current principle is proposed for application in electrical vehicles. The proposed solution is a feasible replacement for the current conventional hydraulic brake (CHB) systems. Unlike CHBs eddy current brakes (ECBs) use eddy currents and their interaction with an externally applied magnetic field to generate braking torque. Due to their pure electrically controllable and contact free nature, ECBs have multiple advantages over the current CHB systems, such as faster response, reduced weight and number of components, ease of implementing various controllers (e.g., anti-lock braking), and reduced noise levels. However, the torque generated by a typical ECB at low speeds is insufficient to effectively and completely stop a moving vehicle. Therefore, an ECB is commonly used as an assistive brake to the CHB system in heavy vehicles, i.e. trains and trucks In order to overcome this shortcoming, the use of AC magnetic fields is proposed to realize a stand-alone ECB system in which sufficient braking torque can be generated at low speeds. To this end, eddy currents are modeled analytically using the governing Maxwell’s equations with the consideration of time varying field application. The analytical model was validated using finite element analysis. Results show that the braking torque increases with the application of a time varying field. Various forms of time varying fields have been studied. It was found that the frequency-modulated applied field in triangular waveform results in the highest braking torque. Next, the design was optimized to maximize the braking torque and an optimum configuration was obtained using multiple pole projection areas (PPAs). Optimization results show that the braking torque significantly increases with the introduction of additional PPAs to the configuration, and the braking torque generation for an optimum four-PPA ECB configuration exceeds the braking requirements for current passenger vehicles. For control purposes, a dynamic model for a novel stand-alone ECB system using AC fields for automotive applications has been successfully designed and evaluated. Also, a model-based predictive controller has been developed for the optimum ECB configuration. Finally an experimental test-bed has been designed for experimentation of both DC and AC field application on ECB. / Graduate

Made available in DSpace on 2016-12-12T20:27:38Z (GMT). No. of bitstreams: 1 Resumo - Eduardo Cavalca.pdf: 79555 bytes, checksum: 90f9b6daaa60256b513924a9a0d2ecdd (MD5) Previous issue date: 2013-07-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Model-based predictive control (MPC) approaches has been studied in a wide range of areas, as petrochemical and aerospace, mainly due to its capability of easily deal with physical and operational constraints. Moreover, such approaches can be extended for the application in control loops with nonlinear and time-variant systems. At this context, the objective of this work is to study some MPC techniques in order to evaluate their applicability to control a three-phase induction motor. More specifically, it was analyzed a Dynamic Matrix Control (DMC) approach, as well as two MPC techniques that uses state space modeling. The control algorithms in question and the nonlinear mathematical model of the motor in study were programmed using the free computing environment Scilab-Xcos®. The models of the threephase motor used in the MPC were obtained by a system identification method (based on the step response of the classical non-linear motor model) and by a phenomenological three-phase modeling approach. Multiple simulations have been performed considering variations in load and speed reference. Besides, some discussions are made related to the influence of the control parameters and about the computational cost. Finally, the results showed that the use of MPC techniques in induction machines has great potential. / Abordagens de controle preditivo baseado em modelo (MPC, do inglês model-based predictive control) têm sido estudadas em diversas áreas, como petroquímica e aeroespacial, principalmente devido à capacidade que apresentam em tratar restrições físicas e operacionais de forma simples. Além disso, tais abordagens podem ser estendidas para aplicação em malhas de controle de sistema não lineares e variantes no tempo. Nesse contexto o objetivo desse trabalho é estudar algumas técnicas de MPC a fim de avaliar sua aplicabilidade no controle de um motor de indução trifásico. Mais especificamente, é analisada a técnica DMC (do inglês Dynamic Matrix Control) bem como duas técnicas de MPC que utilizam modelos no espaço de estados. Os algoritmos de controle em questão e o modelo matemático não linear do motor estudado foram programados utilizando o Scilab-Xcos®, um ambiente de processamento de código livre. Os modelos do motor de indução trifásico utilizados no MPC foram obtidos por meio de um método de identificação de sistemas (baseado na resposta ao degrau do modelo clássico não linear do motor) e por uma abordagem de modelagem fenomenológica trifásica. Múltiplas simulações foram realizadas, considerando variações de carga e referência de velocidade, sendo então apresentadas algumas discussões sobre a influência dos parâmetros de controle e custo computacional. Finalmente, os resultados obtidos demonstraram que a aplicação de técnicas MPC em máquinas de indução apresenta um grande potencial.

Submitted by Erika Demachki (erikademachki@gmail.com) on 2018-01-10T15:49:59Z No. of bitstreams: 2 Dissertação - Rafael Nunes Hidalgo Monteiro Dias - 2017.pdf: 14690145 bytes, checksum: d12e70a2cd0ee1087a184468c55f0b08 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-01-11T11:02:36Z (GMT) No. of bitstreams: 2 Dissertação - Rafael Nunes Hidalgo Monteiro Dias - 2017.pdf: 14690145 bytes, checksum: d12e70a2cd0ee1087a184468c55f0b08 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-01-11T11:02:36Z (GMT). No. of bitstreams: 2 Dissertação - Rafael Nunes Hidalgo Monteiro Dias - 2017.pdf: 14690145 bytes, checksum: d12e70a2cd0ee1087a184468c55f0b08 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-11-27 / This work presents a comparison between Fuzzy and dynamic matrix controllers. These controllers are applied to the direct current (DC) motor speed control, triggered by fully controlled three-phase rectifier. The construction of the real system and the development and validation of the computational model are described. The controllers’ parameters are obtained through an optimization process. Both control techniques are compared and results indicate better performance of the optimized controllers, which suggest their promise in nonlinear systems’ control, in which seeks out control without error, that fulfills well its duty and its able to resist the fatigues. / Este trabalho apresenta o comparativo entre os controladores Fuzzy e matriz dinâmica. Estes controladores são aplicados ao controle de velocidade do motor de corrente contínua, acionado por retificador trifásico totalmente controlado. A metodologia parte da construção do sistema real e do desenvolvimento e validação do modelo computacional. A obtenção dos parâmetros dos controladores é realizada através do processo de otimização. Realiza-se análise comparativa entre as técnicas de controle e os resultados apontam para a proeminência de controladores sintonizados via processo de otimização como técnica promissora a ser empregada em controle de sistemas não lineares, nos quais buscam-se controle em que não há erro, que cumpra bem o seu dever e apto para resistir às fadigas.

nÃo hà / O uso racional de recursos à pauta recorrente nas discussÃes acerca do desenvolvimento sustentÃvel e tem estimulado o projeto de equipamentos mais eficientes quanto ao consumo de energia elÃtrica. Agentes regulamentadores e certificadores estabelecem regras para o funcionamento e para a classificaÃÃo de eletrodomÃsticos quanto ao consumo de energia elÃtrica a fim de formalizar a relaÃÃo entre o desempenho dos mesmos e a manutenÃÃo indefinida dos recursos. Nesse contexto, lanÃa-se mÃo do projeto de um controlador preditivo baseado em modelo aplicado à regulaÃÃo da temperatura do reservatÃrio de Ãgua gelada de um refrigerador termoelÃtrico obedecendo as especificaÃÃes da norma internacional ANSI18 que determina condiÃÃes funcionais para bebedouros com refrigeraÃÃo mecÃnica incorporada, concomitantemente buscando atender aos requisitos para a certificaÃÃo ENERGY STAR quanto ao critÃrio de eficiÃncia energÃtica. Para tanto foram realizadas as etapas de i) Modelagem e IdentificaÃÃo do Processo: foi desenvolvido um modelo em termos de funÃÃo de transferÃncia do sistema de refrigeraÃÃo termoelÃtrico de fluidos atravÃs de modelagem fenomenolÃgica; foram realizados experimentos para a identificaÃÃo de parÃmetros de modelos discretos pelo mÃtodo caixa branca; foi desenvolvido critÃrio de seleÃÃo de modelo baseado na capacidade de simulaÃÃo e caracterÃsticas do resÃduo de simulaÃÃo; ii) Estudo do Controlador Preditivo Baseado em Modelo: foi projetado e implementado na planta um controlador preditivo baseado em um dos modelos parametrizados para regulaÃÃo da temperatura do reservatÃrio interno; foi analisado o desempenho do controlador segundo a norma regulamentadora; iii) Estudo da EficiÃncia do Controlador: foi analisado o desempenho do controlador quanto a capacidade do protÃtipo em atender aos requisitos que o qualificam à obtenÃÃo de certificado segundo critÃrio de eficiÃncia energÃtica para regulaÃÃo da temperatura interna do reservatÃrio e, por fim, realizado um estudo comparativo entre a estratÃgia de controle biestÃvel aplicada atualmente ao processo e a estratÃgia proposta. / The rational use of resources is a recurring theme in sustainable development discussions and has stimulated the development of more efficient electrical power consumption appliances. Regulators and Certifiers agencies set standards for the functionality requirements and for the electric power consumption classification of devices in order to formalize the relationship between performance and maintenance of these resources indefinitely. Thus a model based predictive controller was applied to a thermoelectric cooler to attain the international standard ANSI18 specifications for water cooler dispensers and to meet ENERGY STAR$ iny^{ extregistered}$ energy efficiency requirements. A phenomenological linear model was obtained and the respective parameters were identified by using least squares algorithm; experiments were performed to identify the parameters of the discrete transfer functions; a model criterion selection based on simulation capabilities and residue characteristics was developed; a model based predictive controller was designed and applied using one of the models identified; the controller performance was analyzed attending to the ANSI18 standard and according to energy performance certificates; a comparative study between the bistable control and the proposed strategy was made for performance analysis. Simulation and experimental tests have shown compromise between the simulation capability and residue characteristic criterion. The closed loop system behavior allowed energy saving in standby temperature regulating compared to thermostat control mode. The new control strategy achieved ENERGY STAR energy-efficiency criteria certification requirements infeasible for traditional regulation.

Dans un objectif conjoint d'identification paramétrique en ligne, les méthodes développées dans cette thèse permettent de concevoir en ligne et en boucle fermée les entrées optimales qui enrichissent les informations contenues dans l'expérience en cours. Ces méthodes reposent sur des mesures en temps réel du procédé, sur un modèle dynamique non linéaire (ou linéaire) multi-variable choisi du procédé, sur un modèle de sensibilité des mesures par rapport aux paramètres à estimer et sur un observateur non linéaire. L'analyse de l'observabilité et des techniques de commande prédictive permettent de définir la commande optimale qui est déterminée en ligne par optimisation sous contraintes. Des aspects de stabilisation sont également étudiés (via un apport de contraintes fictives ou via une technique de Lyapunov). Enfin, une loi de commande explicite pour le cas particulier du système d'ordre un est développée. Des exemples illustratifs sont traités via le logiciel ODOE4OPE : un bioréacteur, un réacteur continu parfaitement agité et une aile delta. Ces exemples permettent de voir que l'estimation des paramètres peut être réalisée avec une bonne précision, et à moindre coût expérimental en une expérience / For online parameter identification, the developed methods here allow to design online and in closed loop optimal inputs that enrich the information in the current experience. These methods are based on real-time measurements of the process, on a dynamic nonlinear (or linear) multi-variable model, on a sensitivity model of measurements with respect to the parameters to be estimated and a nonlinear observer. Analysis of observability and predictive control techniques are used to define the optimal control which is determined online by constrained optimization. Stabilization aspects are also studied (by adding fictitious constraints or by a Lyapunov technique). Finally, for the particular case of a first order linear system, the explicit control law is developed. Illustrative examples are processed via the ODOE4OPE software : a bio-reactor, a continuous stirred tank reactor and a delta wing. These examples help to see that the parameter estimation can be performed with good accuracy in a single and less costly experiment

Bien que la commande prédictive fasse appel à des paramètres ayant une signification concrète, la valeur de ces derniers impacte fortement les performances obtenues du système à contrôler. Leur réglage n’étant pas trivial, la littérature fait état d’un nombre conséquent de méthodes de réglage. Celles-ci ne garantissent cependant pas des valeurs optimales. L’objectif de cette thèse est de proposer une approche analytique et originale de réglage de ces paramètres. Initialement applicable aux systèmes MIMO linéaires, l’approche proposée a été étendue aux systèmes non linéaires avec ou sans contraintes et pour lesquels il existe un modèle Takagi-Sugeno (T-S). La classe des systemès non linéaires considérés ici est écrite sous la forme quasi-linéaire paramétrique (quasi-LPV). Sous l’hypothese que le système soit commandable et observable, la méthode proposée garantit la stabilité optimale de ce système en boucle fermée. Pour ce faire, elle s’appuie, d’une part, sur une technique d’amélioration du conditionnement de la matrice hessienne et, d’autre part, sur le concept de rang effectif. Elle présente également l’avantage de requérir une charge calculatoire moindre que celle des approches identifiées dans la littérature. L’intérêt de l’approche proposée est montré à travers l’application en simulation à différents systèmes de complexité croissante. Les travaux menés ont permis d’aboutir à une stratégie de commande prédictive auto-adaptative dénommée "ATSMPC" (Adaptive Takagi-Sugeno Model-based Predictive Control). / Even though predictive control uses concrete parameters, the value of these latter has a strong impact on the obtained performances from the system to be controlled. Their tuning is not trivial. That is why the literature reports a number of adjustment methods. However, these ones do not always guarantee optimal values. The goal of this thesis is to propose an analytical and original tuning tuning approach of these parameters. Initially applicable to linear MIMO systems, the proposed approach has been extended to non-linear systems with or without constraints and for which a Takagi-Sugeno (T-S) model exists. The class of nonlinear systems considered here is written in quasi-linear parametric form (quasi-LPV). Assuming that the system is controllable and observable, the proposed method guarantees the optimal stability of this closed-loop system. To do this, it relies, on the one hand, on a conditioning improving technique of the Hessian matrix and, on the other hand, on the concept of effective rank. It also has the advantage of requiring a lower computational load than the approaches identified in the literature. The interest of the proposed approach is shown through the simulation on different systems of increasingcomplexity. The work carried out has led to a self-adaptive predictive control strategy called "ATSMPC" (Adaptive Takagi-Sugeno Model-based Predictive Control).

Continuous casting is a dominant production technology of steelmaking which is currently used for more that 95% of the world steel production. Mathematical modelling and optimal control of casting machine are crucial tasks in continuous steel casting which directly influence productivity and quality of produced steel, competitiveness of steelworks, safety of casting machine operation and its impact on the environment. This thesis concerns with the development and implementation of the numerical model of temperature field for continuously cast steel billets and its use for optimal control of the casting machine. The numerical model was developed and implemented in MATLAB. Due to computational demands the model was parallelized by means of the computation on graphics processing units NVIDIA with the computational architecture CUDA. Validation and verification of the model were performed with the use of operational data from Trinecke zelezarny steelworks. The model was then utilized as a part of the developed model-based predictive control system for the optimal control of dynamic situations in the casting machine operation. The behaviour of the developed control system was examined by means of dynamic model situations that have confirmed the ability of the implemented system to optimally control dynamic operations of the continuous casting machine. Both the numerical model of the temperature field and the model-based predictive control system have been implemented so that they can be modified for any casting machine and this allows for their prospective commercial applications.

[pt] A crescente demanda por sistemas de transporte autônomos e inteligentes exige o desenvolvimento de técnicas avançadas de controle e estimativa, visando garantir operações seguras e eficientes. Devido à natureza não linear da dinâmica veicular e seus fenômenos característicos, os métodos clássicos de estimativa e controle podem não alcançar resultados adequados, o que incentiva a pesquisa de novos algoritmos. Por algumas contribuições, a primeira parte deste trabalho trata de algoritmos de estimação, tanto para identificação de parâmetros invariantes no tempo, quanto para estimação de estados e parâmetros variantes no tempo. Especial destaque é dados aos algoritmos de Estimação de Estados por Horizonte Móvel (MHSE), que se apresenta como robusto e preciso, devido ao problema de otimização com restrição em que se baseia. Este algoritmo é avaliado em dinâmica longitudinal de veículos, para estimativa de deslizamento longitudinal e coeficiente de atrito pneu-estrada. Apesar de sua eficiência, o alto custo computacional torna necessária a busca por alternativas sub-ótimas, e o emprego de Redes Neurais que mapeiam os resultados da otimização é uma solução promissora, que é tratada como Estimação por Horizonte Móvel com Redes Neurais (NNMHE). O NNMHE é avaliado em uma estimativa do estado de carga (SOC) de baterias para veículos elétricos, demonstrando, através de dados experimentais, que o NNMHE emula com precisão o problema de otimização e a literatura indica sua aplicação efetiva em hardwares embarcados. Por fim, é apresentada uma contribuição sobre o controle preditivo baseado em modelo não linear (NMPC). É proposto e avaliado seu uso compondo uma nova estrutura de controle hierárquica para veículos elétricos com motores independentes nas rodas, através do qual é possível controlar adequadamente o veículo em tarefas de rastreamento de velocidade e trajetória, com reduzido esforço computacional. O controle é avaliado usando dados experimentais de pneus obtidos, que aproximam a simulação de situações reais. / [en] The rising demand of autonomous and intelligent transportation systems requires the development of advanced control and estimation techniques, aiming to ensure safety and efficient operations. Due to the nonlinear nature of vehicle dynamics and its characteristic phenomena, classical estimation and control methods may not achieve adequate results, which encourages the research of novel algorithms. By some contributions, the first part of this work deals with estimation algorithms, both for identification of time invariant parameters and for estimation of states and time varying parameters. Special emphasis is given to Moving-Horizon State Estimation (MHSE), which is presented to be robust and accurate, due to the constrained optimization problem on which it is based. This algorithm is evaluated in vehicle longitudinal dynamics, for slip and tire-road friction estimation. Despite its efficiency, the high computational cost makes it necessary to search for suboptimal alternatives, and the employ of a Neural Networks that maps the optimization results is a promising solution, which is treated as Neural Networks Moving-Horizon Estimation (NNMHE). The NNMHE is evaluated on a state-of-charge (SOC) estimation of batteries for electric vehicles, demonstrating, through experimental data, that the NNMHE emulates accurately the optimization problem, and the literature indicates its effectively application on embedded hardware. Finally, a contribution about Nonlinear Model-based Predictive Control (NMPC) is presented. It is proposed and evaluated its use compounding a novel hierarchical control framework for electric vehicles with independent in-wheel motors, through which it is possible to adequately control the vehicle on velocity and path tracking tasks, with reduced computational effort. The control is evaluated using experimental obtained tire data, which approaches the simulation to real situations.