Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.

Browsing by Subject "Nonlinear Optimal Control"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Advanced Optimal Control Strategies for Nonlinear Systems with Application to Wind Energy
    (2021-06) Paul, Sudipta
    The research in this Master’s thesis presents the theory and application of the existing and simplified version of the Finite-Horizon State-Dependent Riccati Equation (SDRE) nonlinear optimal control techniques. SDRE technique for closed-loop optimal control of nonlinear systems has been an active research area during the last decade. Although SDRE provides great advantages to the control systems designers by providing design flexibility on the state matrices, the existing technique for finite-horizon control is approximate and involves several steps which makes it computationally complex. The SDRE technique for finite-horizon optimal problem involves first representing any given dynamical system in the state-dependent coefficient (SDC) form and then solving the SDRE at each small time interval during the givenfinite-horizon period. The process then is to assume that during the small intervals the Riccati coefficient and vector coefficient are constant and hence use the algebraic Riccati equation and algebraic vector equation. This assumption makes the solution suboptimal. In this research, without the assumption of SDRE coefficients being constant during each small interval, a simplified SDRE technique is presented by employing the analytic solution for the matrix differential Riccati equation and vector differential equation, hence avoiding the suboptimality and eliminating the several steps associated with the existing SDRE technique. The validity of the proposed simplified SDRE method is illustrated and compared with the existing SDRE for both regulation and tracking problems by implementing them in a nonlinear, sixth-order model of a permanent magnet synchronous generator-based wind energy system. The research conducted in this thesis resulted in the publication of three international conferences and one journal article (under preparation).
  • Thumbnail Image
    Item
    Practical strategies of wind energy utilization for uninhabited aerial vehicles in loiter flights.
    (2008-12) Singhania, Hong Yang
    Uninhabited Aerial Vehicle (UAV) is becoming increasingly attractive in missions where human presence is undesirable or impossible. Agile maneuvers and long endurance are among the most desired advantages of UAVs over aircraft that have human pilots onboard. Past studies suggest that the performance of UAVs may be considerably improved by utilizing natural resources, especially wind energy, during flights. The key challenge of exploiting wind energy in practical UAV operations lies in the availability of reliable and timely wind field information in the operational region. This thesis presents a practical onboard strategy that attempts to overcome this challenge, to enable UAVs in utilizing wind energy effectively during flights, and therefore to enhance performance. We propose and explore a strategy that combines wind measurement and optimal trajectory planning onboard UAVs. During a cycle of a loiter flight, a UAV can take measurements of wind velocity components over the flight region, use these measurements to estimate the local wind field through a model-based approach, and then compute a flight trajectory for the next flight cycle with the objective of optimizing fuel. As the UAV follows the planned trajectory, it continues to measure the wind components and repeats the process of updating the wind model with new estimations and planning optimal trajectories for the next flight cycle. Besides presenting an onboard trajectory planning strategy of wind energy exploration, estimation, and utilization, this research also develops a semi-analytical linearized solution to the formulated nonlinear optimal control problem. Simulations and numerical results indicate that the fuel savings of trajectories generated using the proposed scheme depend on wind speed, wind estimation errors, rates of change in wind speed, and the wind model structures. For a given wind field, the magnitude of potential fuel savings is also contingent upon UAVs' performance capabilities.