The control of complex robotic platforms is a challenging task, especially in designs with high levels of kinematic redundancy. Novel variable impedance actuators (VIAs) have recently demonstrated that, by allowing the ability to simultaneously modulate the output torque and impedance, one can achieve energetically more efficient and safer behaviour. However, this adds further levels of actuation redundancy, making planning and control of such systems even more complicated. VIAs are designed with the ability to mechanically modulate impedance during movement. Recent work from our group, employing the optimal control (OC) formulation to generate impedance policies, has shown the potential benefit of VIAs in tasks requiring energy storage, natural dynamic exploitation and robustness against perturbation. These approaches were, however, restricted to systems with smooth, continuous dynamics, performing tasks over a predefined time horizon. When considering tasks involving multiple phases of movement, including switching dynamics with discrete state transitions (resulting from interactions with the environment), traditional approaches such as independent phase optimisation would result in a potentially suboptimal behaviour. Our work addresses these issues by extending the OC formulation to a multiphase scenario and incorporating temporal optimisation capabilities (for robotic systems with VIAs). Given a predefined switching sequence, the developed methodology computes the optimal torque and impedance profile, alongside the optimal switching times and total movement duration. The resultant solution minimises the control effort by exploiting the actuation redundancy and modulating the natural dynamics of the system to match those of the desired movement. We use a monopod hopper and a brachiation system in numerical simulations and a hardware implementation of the latter to demonstrate the effectiveness and robustness of our approach on a variety of dynamic tasks. The performance of model-based control relies on the accuracy of the dynamics model. This can deteriorate significantly due to elements that cannot be fully captured by analytic dynamics functions and/or due to changes in the dynamics. To circumvent these issues, we improve the performance of the developed framework by incorporating an adaptive learning algorithm. This performs continuous data-driven adjustments to the dynamics model while re-planning optimal policies that reflect this adaptation. The results presented show that the augmented approach is able to handle a range of model discrepancies, in both simulation and hardware experiments using the developed robotic brachiation system.

The first essay formulates a dynamic general equilibrium optimal control model of an energy crop as part of a country's planned resource use over a period of time. The model attempts to allocate consumption, production, and factors of production to achieve the country's sustainable development goal. A Cobb-Douglas specification is used for both utility and production functions in the model. We calibrate the model with Thailand data. The selected model is used to generate the stationary state solution and to simulate the optimal policy function and optimal time paths. Two methods are used: a linear approximation method and the Runke-Kutta reverse shooting method. The model provides numerical results that can be used as information for decision makers and stakeholders to devise an economic plan to achieve sustainable development goals. The second essay studies the effect of international trade and changes in labor supply, land supply, and the price of imported energy on energy crop production for bio fuel and food, as well as impacts on social welfare. We develop a dynamic general equilibrium model to describe two baseline scenarios, a closed economy and an open economy. We find that international trade increases welfare and decreases the energy price. Furthermore, resources are allocated to produce more food under the open economy scenario than the quantities produced under a closed economy assumption. An increase in labor supply and land supply result in an increase in social welfare. An increase in imported energy price leads to a welfare loss, higher energy production, and lower food production. The third essay develops a partial equilibrium econometric model to project the impacts of an increase in ethanol production on the Thai agriculture sector over the next ten years. The model is applied to three scenarios for analyzing the effect of government ethanol production targets. The results from the baseline model and scenario analysis indicate that an expansion in ethanol production will result in a significant increase in cassava production, price, and land use. The increase in cassava production will shift land use from maize and sugar cane, thus increasing in price of maize.

Submitted by Caroline Falcao (caroline.rfalcao@ufpe.br) on 2017-06-05T16:18:45Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Tamires Taís.pdf: 9141530 bytes, checksum: dab991dd87283a9e223705028b80d093 (MD5) / Made available in DSpace on 2017-06-05T16:18:45Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Tamires Taís.pdf: 9141530 bytes, checksum: dab991dd87283a9e223705028b80d093 (MD5) Previous issue date: 2013-04-04 / Esta dissertação apresenta um panorama do sistema de saúde brasileiro, com ênfase no caso do Estado de Pernambuco. A gestão de sistemas de saúde se manifesta sob a forma geral de longas filas de espera, que são analisados neste contexto, incluindo algumas abordagens que têm sido propostas e implementadas em Pernambuco, a fim de resolver o problema. Um modelo de crescimento econômico ótimo destacando o setor de saúde, e, em seguida, operando em conjunto, os setores de saúde e educação é proposto. Os resultados do princípio do máximo de Pontryagin aplicado a este modelo mostram os benefícios mútuos para ambos os setores e os seus efeitos no bem-estar da sociedade. Um estudo de caso de filas de espera no Hospital da Restauração, em Recife, Pernambuco, é apresentado. / An overview of the Brazilian health care system is presented, with an emphasis in the Pernambuco state case. One central issue concerning health systems management manifests itself under the general form of long waiting lines, which are then here analyzed in this context, including some approaches that have been proposed and implemented in Pernambuco in order to tackle the problem. An optimal economic growth model highlighting the health sector, and then, operating jointly, the health and education sectors, is proposed. The results of the Pontryagin Maximum Principle applied to this model show the mutual benefits for both sectors and their effects in the community welfare. A case study of queueing systems in Hospital da Restaura¸c˜ao (an emergency hospital) in Recife, Pernambuco, is presented.

To reduce fossil fuel consumption and carbon emission in the building sector, renewable and low carbon energy technologies are integrated in building energy systems to supply all or part of the building energy demand. In this research, an optimal supervisory controller is designed to optimize the operational cost and the CO2 emission of the integrated energy systems. For this purpose, the building energy system is defined and its boundary, components (subsystems), inputs and outputs are identified. Then a mathematical model of the components is obtained. For mathematical modelling of the energy system, a unified modelling method is used. With this method, many different building energy systems can be modelled uniformly. Two approaches are used; multi-period optimization and hybrid model predictive control. In both approaches the optimization problem is deterministic, so that at each time step the energy consumption of the building, and the available renewable energy are perfectly predicted for the prediction horizon. The controller is simulated in three different applications. In the first application the controller is used for a system consisting of a micro-combined heat and power system with an auxiliary boiler and a hot water storage tank. In this application the controller reduces the operational cost and CO2 emission by 7.31 percent and 5.19 percent respectively, with respect to the heat led operation. In the second application the controller is used to control a farm electrification system consisting of PV panels, a diesel generator and a battery bank. In this application the operational cost with respect to the common load following strategy is reduced by 3.8 percent. In the third application the controller is used to control a hybrid off-grid power system consisting of PV panels, a battery bank, an electrolyzer, a hydrogen storage tank and a fuel cell. In this application the controller maximizes the total stored energies in the battery bank and the hydrogen storage tank.