Bumpless transfer for switched systems

Tres estrategias de transferencia sin perturbaciones fueron evaluadas para sistemas conmutados. Un método de transferencia sin perturbaciones basado en control predictivo fue desarrollado y dos teoremas para la estabilidad interna del sistema incluyendo las primeras dos estrategias de transferencia sin perturbaciones fueron encontrados y demostrados. Finalmente, los métodos de transferencia sin perturbaciones y las condiciones de estabilidad fueron aplicados sobre un sistema de cintas magnéticas.Three bumpless transfer strategies were evaluated for switched systems. A bumpless transfer method based on predictive control was developed and two theorems for the internal stability of the overall system with the first two bumpless transfer methods were found and demonstrated. Finally, the bumpless transfer methods and the stability conditions were applied on a web winding system.Magíster en Ingeniería ElectrónicaMaestrí

Stabilization of Compressor Surge Using Gain-Scheduled Controller

Gain scheduling is a control method that is used in nonlinear systems to optimize their controlled performance and robustness over a wide range of operating conditions. It is one of the most commonly used controller design approaches for nonlinear systems. In this control technique, the controller consists of a collection of linear controllers, each of which provides satisfactory closed-loop stability and performance for a small operating region, and combined they guarantee the stability of the system along the entire operating range. The operating region of the system is determined by a scheduling signal, also known as the scheduling variable, which may be either exogenous or endogenous with respect to the plan. A good design of the gain-scheduled controller requires a suitable selection of the scheduling variables to properly reflect the dynamics of the system. In this thesis, we apply the gain scheduling control method to the control of compression systems with active magnetic bearings (AMBs). First, a gain-scheduled controller is designed and tested for the rotor levitation control of the AMB system. The levitation controller is designed to guarantee robust rotor levitation over a wide range of rotating speeds. We show through numerical simulation that the rotor vibration is contained in the presence of uncertainties introduced by speed dependent gyroscopic forces. Next, we implement the gain scheduling control method to the active stabilization of compressor surge in a compression system using the AMBs as actuators. Recently, Yoon et al. [1] showed that AMBs can be used to stabilize the surge instability in a compression system. In this thesis, we demonstrate that gain scheduling control can effectively extend the stable operating region of the compression system beyond the limits presented in [1]. For the stabilization of surge, a gain-scheduled controller was obtained by combining six linear controllers that together they cover the full operating range of the compression system. We were able to demonstrate through numerical simulation that the designed surge controller is effective in suppressing the instability down to a throttle valve opening of 12%, and in the presence of random flow disturbance and actuator saturation. An observer-based technique was implemented to achieve a bumpless and smooth transfer when switching between the linear controllers

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

Robust control examples applied to a wind turbine simulated model

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modeling and control become challenging problems. On the one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behavior. Therefore, the development of modeling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of the development of robust control strategies when applied to a simulated wind turbine plant. Extended simulations with the wind turbine benchmark model and the Monte Carlo tool represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modeling and control become challenging problems. On the one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behavior. Therefore, the development of modeling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of the development of robust control strategies when applied to a simulated wind turbine plant. Extended simulations with the wind turbine benchmark model and the Monte Carlo tool represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics