Ingeniería de Control y Automatización
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Item Metadata only Model-based fault diagnosis via structural analysis of a reverse osmosis plant(Pontificia Universidad Católica del Perú, 2021-05-11) Göpfert, Johannes Georg; Pérez Zúñiga, Carlos Gustavo; Reger, JohannWater desalination is one approach to force water scarcity. One of the processes used for desalination is reverse osmosis. Like other systems, a reverse osmosis plant is susceptible to faults. A fault can lead to a loss of efficiency, or if the fault is severe to a total breakdown. Appropriate measures can minimize the impact of faults, but this requires in time fault detection. The following thesis shows a proposal for an online fault diagnosis system of a reverse osmosis plant. For the model-based approach, a mathematical model of a reverse osmosis plant has been developed. The model contains a new approach for modeling the interaction between the high-pressure pump, the brine valve, and the membrane module. Furthermore, six faults considered for fault diagnosis have been modeled. Two of the faults are plant faults: The leakage of the feed stream and membrane fouling. The other four faults are sensor or actuator malfunctions. The fault diagnosis system is developed via structural analysis, a graph-based approach to determine a mathematical model’s overdetermined systems of equations. With the structural analysis, 73 fault-driven minimal structurally overdetermined (FMSO) sets have been determined. The results show that all six faults are detectable. However, two faults are not isolable. Five of the FMSO sets have been chosen to deduce the residuals used for online fault detection and isolation. The simulations demonstrate that the calculated residuals are appropriate to detect and isolate the faults. If one assumes that only the considered faults occur, it is possible to determine some faults’ magnitude.Item Metadata only Energy-Based Control for the Cart-Pole System in Implicit Port-Hamiltonian Representation(Pontificia Universidad Católica del Perú, 2020-03-19) Huamán Loayza, Alex Smith; Reger, Johann; Cieza Aguirre, Oscar B.; Pérez Zúñiga, Carlos GustavoThis master thesis is devoted to the design, analysis, and experimental validation of an energy-based control strategy for the well-known benchmark cart-pole system in implicit Port-Hamiltonian (PH) representation. The control scheme performs two tasks: swingup and (local) stabilization. The swing-up controller is carried out on the basis of a generalized energy function and consists of bringing the pendulum trajectories from the lower (stable) position to a limit cycle (homoclinic orbit), which passes by the upright (unstable) position, as well as the cart trajectories to the desired point. The (local) stabilizing controller is designed under a novel algebraic Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) technique and ensures the upright (asymptotic) stabilization of the pendulum as well as the cart at a desired position. To illustrate the effectiveness of the proposed control scheme, this work presents simulations and real-time experiments considering physical damping, i.e., viscous friction. The results are additionally contrasted with another energy-based control strategy for the cart-pole system in explicit Euler-Lagrange (EL) representation.Item Metadata only Robust estimation of vertical wheel forces via modulation-based sensor fusion(Pontificia Universidad Católica del Perú, 2019-11-05) Segura Rojas, Juan de Dios; Reger, Johann; Pérez Zúñiga, Carlos GustavoSince its introduction by Shinbrot, numerous variations of parameter identification based on the Modulating Function Technique (MFT) have been developed. Recently researches have achieved to estimate also states through this method. In this thesis, the MFT is utilized for the estimation, of both parameters and states, that lead to observe the behaviour of the vertical suspension forces on a vehicle over time. In order to deal with the frequency disturbances present by perturbations as measurement noise and vibrations, the Fourier Modulating Function (FMF) as a kernel is proposed. Furthermore, this method is implemented with the concept of sensor fusion. The estimation that results after the implementation of an adaptive observer during the present work is going to show the robustness of the studied technique.Item Metadata only Contributions to ida-pbc with adaptive control for underactuated mechanical systems(Pontificia Universidad Católica del Perú, 2018-10-17) Popayán Avila, Jhossep Augusto; Reger, Johann; Morán Cárdenas, Antonio ManuelThis master thesis is devoted to developing an adaptive control scheme for the well- known Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) technique. The main objective of this adaptive scheme is to asymptotically stabilize a class of Underactuated Mechanical Systems (UMSs) in the presence of uncertainties (not necessarily matched). This class of UMSs is characterized by the solvability of the Partial Differential Equation (PDE) resulting from the IDA-PBC technique. Two propositions are stated in this work to design the adaptive IDA-PBC. One of the main properties of these propositions is that even though the parameter estimation conver- gence is not guaranteed, the adaptive IDA-PBC achieves asymptotic stabilization. To illustrate the effectiveness of these propositions, this work performs simulations of the Inertia Wheel Inverted Pendulum (IWIP) system, considering a time-dependent input disturbance, a type of physical damping, i.e., friction (not considered in the standard IDA-PBC methodology), and parameter uncertainties in the system (e.g., inertia).Item Metadata only Autonomous obstacle avoidance and positioning control of mobile robots using fuzzy neural networks(Pontificia Universidad Católica del Perú, 2018-10-17) Grebner, Anna-Maria Stephanie; Reger, JohannNavigation and obstacle avoidance are important tasks in the research field of au- tonomous mobile robots. The challenge tackled in this work is the navigation of a 4- wheeled car-type robot to a desired parking position while avoiding obstacles on the way. The taken approach to solve this problem is based on neural fuzzy techniques. Earlier works resulted in a controller to navigate the robot in a clear environment. It is extended by considering additional parameters in the training process. The learning method used in this training is dynamic backpropagation. For the obstacle avoidance problem an additional neuro-fuzzy controller is set up and trained. It influences the results from the navigation controller to avoid collisions with objects blocking the path. The controller is trained with dynamic backpropagation and a reinforcement learning algorithm called deep deterministic policy gradient.Item Metadata only Optimal control for polynomial systems using the sum of squares approach(Pontificia Universidad Católica del Perú, 2018-10-16) Vilcarima Sabroso, Carlos Alberto; Reger, JohannThe optimal control in linear systems is a widely known problem that leads to the solution of one or two equations of Ricatti. However, in non-linear systems is required to obtain the solution of the Hamilton-Jacobi-Bellman equation (HJB) or variations, which consist of quadratic first order and partial differential equations, that are really difficult to solve. On the other hand, many non-linear dynamical systems can be represented as polynomial functions, where thanks to abstract algebra there are several techniques that facilitate the analysis and work with polynomials. This is where the sum-of-squares approach can be used as a sufficient condition to determine the positivity of a polynomial, a tool that is used in the search for suboptimal solutions of the HJB equation for the synthesis of a controller. The main objective of this thesis is the analysis, improvement and/or extension of an optimal control algorithm for polynomial systems by using the sum of squares approach (SOS). To do this, I will explain the theory and advantages of the sum-of-squares approach and then present a controller, which will serve as the basis for our proposal. Next, improvements will be added in its performance criteria and the scope of the controller will be extended, so that rational systems can be controlled. Finally an alternative will be presented for its implementation, when it is not possible to measure or estimate the state-space variables of the system. Additionally, some examples that validated the results are also presented.Item Metadata only Mixed H2/H∞ control for infinite dimensional systems(Pontificia Universidad Católica del Perú, 2017-08-28) Noack, Matti; Morán Cárdenas, Antonio Manuel; Reger, JohannThe class of infinite dimensional systems often occurs when dealing with distributed parameter models consisting of partial differential equations. Although forming a comprehensive description, they mainly become manageable by finite dimensional approximations which likely neglect important effects, but underlies a certain structure. In contrast to common techniques for controlling infinite dimensional systems, this work focuses on using robust control methods. Thus, the uncertainty structure that occurs due to the discretization shall be taken into account particularly. Additionally, optimal performance measures can be included into the design process. The mixed H2/H∞ control approach handles the inclusion of disturbances and inaccuracies while guaranteeing specified energy or magnitude bounds. In order to include various of these system requirements, multi-objective robust control techniques based on the linear matrix inequality framework are utilized. This offers great flexibility concerning the formulation of the control task and results in convex optimization problems which can be solved numerically efficient by semi-definite programming. A flexible robot arm structure serves as the major application example during this work. The model discretization leads to an LTI system of specified order with an uncertainty model which is obtained by considering the concrete approximation impact and frequency domain tests. A structural analysis of the system model relates the neglected dynamics to a robust characterization. For the objective selection, stability shall be ensured under all expected circumstances while the aspects of optimal H2 performance, passive behavior and optimal measurement output selection are included. The undesirable spillover effect is thoroughly investigated and thus avoided.Item Metadata only Observability studies of a turbocharger systems(Pontificia Universidad Católica del Perú, 2016-06-02) Tejada Zúñiga, María Cristina; Reger, Johann; Sotomayor Moriano, Juan JavierThe use of diesel engine turbochargers is increasing today, as it represents an option that o ers high e ciency and low fuel consumption. To design the control system in order to reduce the level of exhaust emissions there is a need for information about all states that are not measurable. To this end, observers or virtual sensors are more frequently applied, achieving estimates of the system states from inputs and measured output. To propose an observer, the precise mathematical model of the air path diesel engine system is used. This is a nonlinear model of a third order which is analyzed in terms of observability. From the point of view of systems theory, certain conditions and the existence of a transformation of the system state, called di eomorphism, need to be evaluated. Observers have been designed based on di erent approaches: Extended Luenberger Observers, High Gain Observers, Sliding Modes Observers and Extended Kalman-Bucy Filters. They have been validated by simulation for the system under consideration in this work.