Browsing by Subject "Adaptive control"
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Item Adaptation, gyro-ree stabilization, and smooth angular velocity observers for attitude tracking control applications(2014-08) Thakur, Divya, active 21st century; Akella, Maruthi Ram, 1972-This dissertation addresses the problem of rigid-body attitude tracking control under three scenarios of high relevance to many aerospace guidance and control applications: adaptive attitude-tracking control law development for a spacecraft with time-varying inertia parameters, velocity-free attitude stabilization using only vector measurements for feedback, and smooth angular velocity observer design for attitude tracking in the absence of angular velocity measurements. Inertia matrix changes in spacecraft applications often occur due to fuel depletion or mass displacement in a flexible or deployable spacecraft. As such, an adaptive attitude control algorithm that delivers consistent performance when faced with uncertain time-varying inertia parameters is of significant interest. This dissertation presents a novel adaptive control algorithm that directly compensates for inertia variations that occur as either pure functions of the control input, or as functions of time and/or the state. Another important problem considered in this dissertation pertains to rigid-body attitude stabilization of a spacecraft when only a set of inertial sensor measurements are available for feedback. A novel gyro-free attitude stabilization solution is presented that directly utilizes unit vector measurements obtained from inertial sensors without relying on observers to reconstruct the spacecraft's attitude or angular velocity. As the third major contribution of this dissertation, the problem of attitude tracking control in the absence of angular velocity measurements is investigated through angular velocity observer (estimator) design. A new angular velocity observer is presented which is smoothed and ensures asymptotic convergence of the estimation errors irrespective of the initial true states of the spacecraft. The combined implementation of a separately designed proportional-derivative type controller using estimates generated by the observer results in global asymptotic stability of the overall closed-loop tracking error dynamics. Accordingly, a separation-type property is established for the rigid-body attitude dynamics, the first such result to the author's best knowledge, using a smooth (switching-free) observer formulation.Item Adaptive estimation and control algorithms for certain classes of large-scale sensor and actuator uncertainties(2012-05) Mercker, Travis H.; Akella, Maruthi Ram, 1972-; Arapostathis, Ari; Hull, Davis G.; Lightsey, Glenn; Marchand, Belinda G.This dissertation considers the general problem of controlling dynamic systems subject to large-scale sensor and actuator uncertainties. The assumption is made that the uncertainty is limited to either pure rotation (i.e. special orthogonal matrix) or that each axis is rotated independently. Although uncertainty can appear in more general forms, this representation describes a ``net-effect'' when the ideal axes have become misaligned that is of fundamental importance to the control of numerous systems. Adaptive observers and controllers are introduced that guarantee perfect reference trajectory tracking even with the appearance of these large-scale uncertainties. The specific contributions of this dissertation are as follows: (I) the problem of rigid-body attitude tracking with vector measurements, unknown gyro bias, and unknown body inertia matrix is addressed for the first time. In this problem, the body attitude acts as unknown special orthogonal matrix (i.e. sensor uncertainty). A set of adaptive observers and an adaptive controller is presented that guarantees perfect tracking as well as convergence of the attitude and bias estimates through a Lyapunov stability analysis. (II) An adaptive observer is developed for the scenario where the control is pre-multiplied by an unknown constant scaling and rotation matrix which gives a non-affine representation of the uncertainty. The observer is shown to be convergent given a certain persistence of excitation condition on the input signal and using a smooth projection scheme on the estimate of the unknown scaling. In addition, the observer is combined with a stabilizing control to guarantee perfect tracking which establishes a separation like property. (III) The class of uncertainties where each axis of the control is independently misaligned is examined. The problem is split into studies of in-plane and out-of-plane misalignment angles given that they exhibit fundamental technical differences in establishing convergence. Where possible, rigorous stability proofs are given for a series of adaptive observers. The structure of the observers assure that the estimates do not introduce any singularities into the control problem other than those inherent from the misalignment geometry. The inherent singularities are avoided through the use of projection schemes which allow for extension to the control problem. This work represents the first significant effort to develop adaptive observers and controllers for this class of misalignments.Item Adaptive inverse modeling of a shape memory alloy wire actuator and tracking control with the model(2009-06-02) Koh, Bong SuIt is well known that the Preisach model is useful to approximate the effect of hysteresis behavior in smart materials, such as piezoactuators and Shape Memory Alloy(SMA) wire actuators. For tracking control, many researchers estimate a Preisach model and then compute its inverse model for hysteresis compensation. However, the inverse of its hysteresis behavior also shows hysteresis behavior. From this idea, the inverse model with Kransnoselskii-Pokrovskii(KP) model, a developed version of Preisach model, can be used directly for SMA position control and avoid the inverse operation. Also, we propose another method for the tracking control by approximating the inverse model using an orthogonal polynomial network. To estimate and update the weight parameters in both inverse models, a gradient-based learning algorithm is used. Finally, for the SMA position control, PID controller, adaptive controllers with KP model and adaptive nonlinear inverse model controller are compared experimentally.Item Adaptive vehicle control by combined DYC and FWS(2014-05) Bissonnette, Mathew Ward; Longoria, Raul G.Vehicle stability is an important consideration in vehicle design. When driver intervention is insufficient, safety can be improved by the addition of vehicle stability control (VSC). Typical vehicle stability controllers are designed using a linearized vehicle model and an assumed set of parameters. However, some parameters like mass and inertial properties may not be constant between operations. To recover controller performance in the presence of unknown parameters, adaptive estimates can be developed. This thesis seeks to implement a model reference adaptive controller for yaw rate and side slip control and to evaluate any implementation issues that may arise. A linearized vehicle model is used for controller design via a Lyapunov approach and a combined front wheel steering (FWS) and direct yaw control (DYC) controller is developed. The combined FWS+DYC controller is tested in a low friction double lane change with initial parameter estimation error. The FWS+DYC controller was found to be robust to parameter changes, and the adaptive parameter estimates did not provide any noticeable improvement over the non-adaptive case. A four wheel steering (4WS) controller is developed by a similar approach and tested under the same conditions. Both controllers were found to be effective at stabilizing the vehicle. An unexpected finding was that though the combined FWS+DYC controller was effective even in low friction conditions with parameter errors, the required motor torque was very large and oscillated rapidly. This was diminished through the addition of a low pass filter on the controller yaw moment output, but could not be removed entirely.Item Control algorithms and flight software framework for a spacecraft guidance navigation and control system(2011-12) Zhang, Jing; Lightsey, E. GlennThis thesis presents a comparison of controller designs and a system software design for a general Guidance, Navigation and Control (GNC) system. The first part of the thesis investigates four control algorithms based on Lyapunov Direct Method in conjunction with sliding mode and adaptive control. These algorithms address three practical issues in controller design: maximum actuation limitation, external disturbances, and imperfect dynamic models. Each of the algorithms is proven to be globally asymptotically stable within its constraints. A simulation is then used to model a cube-satellite attitude maneuver using each of the controllers to evaluate its performance. The second part of this thesis discusses the development of a high-level flight software architecture capable of handling common tasks, including ground station communication and attitude maneuvers, as well as power or device failures.Item Hierarchical modeling of multi-scale dynamical systems using adaptive radial basis function neural networks: application to synthetic jet actuator wing(Texas A&M University, 2004-09-30) Lee, Hee EunTo obtain a suitable mathematical model of the input-output behavior of highly nonlinear, multi-scale, nonparametric phenomena, we introduce an adaptive radial basis function approximation approach. We use this approach to estimate the discrepancy between traditional model areas and the multiscale physics of systems involving distributed sensing and technology. Radial Basis Function Networks offers the possible approach to nonparametric multi-scale modeling for dynamical systems like the adaptive wing with the Synthetic Jet Actuator (SJA). We use the Regularized Orthogonal Least Square method (Mark, 1996) and the RAN-EKF (Resource Allocating Network-Extended Kalman Filter) as a reference approach. The first part of the algorithm determines the location of centers one by one until the error goal is met and regularization is achieved. The second process includes an algorithm for the adaptation of all the parameters in the Radial Basis Function Network, centers, variances (shapes) and weights. To demonstrate the effectiveness of these algorithms, SJA wind tunnel data are modeled using this approach. Good performance is obtained compared with conventional neural networks like the multi layer neural network and least square algorithm. Following this work, we establish Model Reference Adaptive Control (MRAC) formulations using an off-line Radial Basis Function Networks (RBFN). We introduce the adaptive control law using a RBFN. A theory that combines RBFN and adaptive control is demonstrated through the simple numerical simulation of the SJA wing. It is expected that these studies will provide a basis for achieving an intelligent control structure for future active wing aircraft.Item Persistence filters for controller and observer design in singular gain systems(2011-05) Srikant, Sukumar; Akella, Maruthi Ram, 1972-; Lightsey, E G.; Bennighof, Jeffrey K.; Hull, David G.; Griffin, LisaThis dissertation develops a general framework for designing stabilizing feedback controllers and observers for dynamics with state/time dependent gains on the control signals and measured outputs. These gains have potential singularity periods but satisfy a technically non-trivial condition referred to as persistence of excitation. A persistence filter design constitutes the primary theoretical innovation of this work around which the controller and observer development is centered. Application areas of singular gain systems considered in this study include robotics, biomechanics, intelligent structures and spacecrafts. Several representative problems involving singular, time-dependent gains are addressed. The specific contributions of this dissertation are outlined as follows: (i) a stabilizing feedback for linear, single-input systems with time-varying, singular control scaling is designed that allows arbitrary exponential convergence rate for the closed-loop dynamics. An adaptive control generalization of this result allows asymptotic convergence in presence of unknown plant parameters. An extension to a special, single-input nonlinear system in the controller canonical form is also proposed. It is proven that this control design results in bounded tracking error signals for a trajectory tracking objective; (ii) observer design for linear, single-output systems with time-varying, singular measurement gains is considered. A persistence filter similar in structure to the control counterpart aids an observer design that guarantees exponential state reconstruction with arbitrary convergence rates; (iii) the observer and controller designs are combined to obtain an exponentially stabilizing output feedback controller for linear, single-input, single-output dynamics with singular gains on both the control and measurements. A novel separation property is established as a consequence. The construction motivates applications to stabilization with reversible transducers which can switch between sensor and actuator modes. The results are verified on two illustrative applications, vibration control using piezoelectric devices and inverted pendulum stabilization with a DC motor. The linear result is further generalized to include state dependent gains; (iv) application of the persistence filter theory to spacecraft attitude stabilization using intermittent actuation is explored. The intermittence is characterized by a time-varying, periodically singular control gain. A nonlinear persistence filter allows construction of an exponentially stabilizing controller and simulations verify convergence with intermittent actuation where conventional proportional-derivative control fails; (v) a stabilization result for a special multi-input, linear system with time-varying matrix control gains is presented. The matrix gain is assumed to be diagonal but allows fewer controls than states subject to a controllability assumption in absence of the singular gain matrix. The single-input adaptive control results are shown to extend to the multi-input case. An application to angular velocity stabilization of an underactuated rigid spacecraft is considered.Item Robustness properties of quaternion-based attitude control systems(2016-05) Yang, Sungpil; Akella, Maruthi Ram, 1972-; Bakolas, Efstathios; Arapostathis, Aristotle; Acikmese, Behcet; Mazenc, FredericBoth stabilizing and tracking solutions of the rigid-body attitude control problem, using various attitude representations, are now well understood. Based on the sensor availability, numerous full-state feedback or gyro-free output feedback controllers have been proposed and studied. In the dissertation, we revisit classical proportional-derivative (PD) type attitude controllers when the system is subject to uncertainties like time-delay in the feedback loop, measurement errors, external disturbance torques and modeling uncertainties. We not only analyze existing PD-type controllers while considering various types of uncertainties, but also design tracking controllers robust to the system parameter uncertainties. We adopt the quaternion representation for the attitude kinematics so that we can avoid the geometric singularities coming with minimal 3-dimensional parameter representations. For stability and robustness analysis of the PD-type controllers, we do not rely on the linear system framework in which the original dynamics are considered as the sum of the nominal linear part and the nonlinear perturbation part. Instead, another approach is suggested as suitable for the quaternion kinematic representation so that results are not restricted to a neighborhood of the origin. We first deal with one of the common Lyapunov functions used for quaternion-based attitude control problem. Then, through the strictification process, a new Lyapunov function is constructed which can be analyzed based on the standard Lyapunov stability analysis method. As a result, we establish sufficient conditions for locally stability or boundedness of the system subject to aforementioned uncertainties for both PD full-state feedback and PD-like gyro-free output feedback controllers. When our scope is narrowed to the system parameter uncertainties, we propose adaptive controllers that track predefined reference trajectories and estimate the unknown inertial parameters. Specifically, we apply a dynamic scaling-based Immersion and Invariance method for the first time to the attitude tracking problem. We also provide a way to control and estimate the upper bound of a dynamic scaling factor which has not yet been seen in the literature.