Kilsoo Kim

A Parameter Dependent Riccati Equation Approach to Output Feedback Adaptive Control

A parameter dependent Riccati equation approach is taken to analyze the stability properties of an output feedback adaptive control law design. The adaptive controller is intended to augment a nominal, fixed gain, observer based output feedback control law. Although the formulation is in the setting of model following adaptive control, the realization of the adaptive controll er does not require implementing the reference model. In this regard, the cost of implementing the adaptive controller above that of a fixed gain control law is far less than that of other methods. The error signals are shown to be uniformly ultimately bounded and an expression for the ultimate bound is provided. The control design process and theoretical results are illustrated using a model for wing-rock dynamics. Research in adaptive output feedback control of uncertain nonlinear systems is motivated by the many emerging applications that employ novel actuation devices for active control of flexible structures and fluid flows. These applications include actuators such as piezo-electric films and s ynthetic jets, which are typically nonlinearly coupled to t he plant dynamics they are intended to control. Models for these applications vary from accurate low frequency models to models that crudely approximate the true dynamics even at low frequencies. Examples of applications include active damping of flexible structures, control of aeroservoelasti c aircraft, and active control of flows. Adaptive control can be used to satisfy performance requirements in the presence of large scale parameter uncertainty, and improved safety in the event of actuator failure.

K-modification in Adaptive Control

This paper presents a new modification for adaptive control by adding a tunable stiffness term to the standard weight update law. This approach can be combined with well known �and e-modification terms. In comparison to these modifications, the proposed modification term provides a filtering effect that is frequency dependent to improve adaptive system performance such that smooth transient responses can be obtained. The motivation behind this approach comes from the desire to achieve a prescribed natural frequency and damping ratio for the error transients.

Adaptive Attitude and Vibration Control of the NASA Ares Crew Launch Vehicle

The control system of the NASA Crew Launch Vehicle is designed to meet performance and robustness requirements during its ascent ∞ight phase. However, the controller bandwidth and the attainable level of robust performance is limited by the degree of ∞exibility inherent in the long and slender design that has been adopted for this vehicle. Since there remains a substantial degree of uncertainty regarding the structural dynamics of this vehicle, the degree of risk associated with ∞ight control is reduced by permitting a greater level of robust performance to be attained by augmenting the existing ∞ight control system design with an adaptive element. Attitude stabilization and ∞exible mode suppression of the model is achieved by using a model reference adaptive controller designed to maintain nominal tracking performance in the presence of disturbances, parametric uncertainties and unmodeled dynamics. The control law employs an output feedback neural network adaptive element which augments an existing decoupled gain scheduled linear control law in a centralized manner to expand the class of uncertainty the system can potentially suppress. The resulting closed loop system can be shown to be uniformly ultimately bounded through a Lyapunov-like stability analysis.

Derivative-Free Output Feedback Adaptive Control of an Aeroelastic Generic Transport Model

This paper illustrates an application of derivative-free, output feedback adaptive control on an aeroelastic model of longitudinal dynamics for a generic transport model. The controller uses a state observer as a reference model, and has a derivative-free delayed weight update law. Since it does not assume the existence of constant ideal weights, it is particulary well suited for adaptation to sudden changes in system dynamics, such as might be due to reconfiguration, deployment of a payload, docking, structural damage, or to difficult to model external disturbances. In addition, it i s applicable to output feedback

Derivative-Free Output Feedback Adaptive Control

This paper presents an output feedback adaptive control architecture for continuoustime uncertain dynamical systems based on state observer and derivative-free delayed weight update law. The assumption of constant unknown ideal weights is generalized to the existence of time-varying weights without assuming the existence of their derivatives in a time interval. As a result, this approach is particularly well suited for adaptation in the presence of sudden change in uncertain system dynamics, such as might be due to reconfiguration, deployment of a payload, docking, structural damage, or there is a difficult to model disturbance. Using a Lyapunov-Krasovskii functional, it is proven that the error dynamics are uniformly ultimately bounded, without the need for modification terms in the adaptive law. The complexity of the proposed approach is less than many other output feedback adaptive control architectures available in the literature and it can be used to augment an existing state observer based linear controller.

Adaptive Output Feedback Control for an Aeroelastic Generic Transport Model: A Parameter Dependent Riccati Equation Approach

This paper presents the application of an adaptive output feedback control design for an aeroelastic genetic transport model. The adaptive design uses a novel parameter dependent Riccati equation approach. The adaptive controller is intended to augment a nominal, fixed g ain, observer based output feedback control law. Although the formulation is in the setting of model following adaptive control, the realization of the adaptive controller does not require implementing the reference model. In this regard, the cost of implementing the adaptive controller, above that of a fixed gain control law, i s far less than that of other methods. In addition, it is applicable to output feedback adaptive control design for non-minimum phase plants. I. Introduction Research in adaptive output feedback control of uncertain nonlinear systems is motivated by the many emerging applications that employ novel actuation devices for active control of flexible structures and fluid flows. These applications include actuators such as piezo-electric films and s ynthetic jets, which are typically nonlinearly coupled to t he plant dynamics they are intended to control. Models for these applications vary from accurate low frequency models to models that crudely approximate the true dynamics even at low frequencies. Examples of applications include active damping of flexible structures, control of aeroservoelasti c aircraft, and active control of flows. Adaptive control can be used to satisfy performance requirements in the presence of large scale parameter uncertainty, and improved safety in the event of actuator failure. The adaptive output feedback approach used in this paper is taken from Ref. 1. It assumes that a state observer is employed in the nominal controller design. The observer design is modified and employed in the adaptive part of the design. This is combined with a novel adaptive weight update law. The weight update law ensures that estimated states follow both the reference model states and the true st ates so that both state estimation errors and state tracking errors are bounded. Although the formulation is in the setting of model following adaptive control, the realization of the adaptive controller uses the observer of the nominal controller in place of the reference model to generate an error signal. Thus the only components that are added by the adaptive controller are the realizations of the basis functions and the weight adaptation law. The realization is even less complex than that of implementing a model reference adaptive controller in the case of state feedback. The stabi lity analysis employs a Lyapunov candidate function that entails the solution of a parameter dependent Riccati equation (rather than a Lyapunov equation) to show that all error signals are uniformly ultimately bounded (UUB). It is shown how the upper limit for the Riccati equation parameter is employed in the design of the adaptive law, and also influen ces the ultimate bounds for the state estimate error and the adapted weight error.

K-modication based H2 Adaptive Control

Two novel adaptive control laws are presented. The first is based on the use of a tunable stiffness term that provides a frequency dependent filtering effect, smoother transient responses, and time delay robustness in the adaptive system. The second is an H2 approach which extends a recently developed Kalman filter based approach to adaptive control law modification, by providing an optimal time varying adaptation gain. The proposed H2 model reference adaptive control law with K-modification combines the advantages in each method. It can also be used with the well known - and e-modification terms.

Guidance, navigation, and control of an unmanned hovercraft

This paper introduces a simulation and evaluation of guidance, navigation, and control algorithms applied to an autonomous hovercraft. A line-of-sight guidance law is adopted in conjunction with a neural network based adaptive dynamic inversion control scheme for the underactuated hovercraft following a prescribed path. The simulation result demonstrates that the guidance and control scheme can be effective in waypoint following of the underactuated hovercraft, especially, when external disturbances exist. It is also shown that the error signals are bounded using Lyapunovs direct method.

Modeling of a 3-DOF Dynamic Wind Tunnel Traverse

A 3-DOF (pitch, plunge, and roll) programmable dynamic traverse has been designed and constructed for dynamic testing of aerodynamic models in the wind tunnel. The system design allows an experimentalist to carry heavy models with all of the needed sensors for evaluating true unsteady aerodynamic flight qualities. Controlling the forces and moments applied to the model allows the experimentalist to drive the model through predetermined trajectories. The desired forces and moments can also be applied to the model independent of the model motion with very low impedance. This allows for the model motion to be controlled by relatively weak aerodynamic forces, essentially simulating free flight in the tunnel, while still providing necessary forcing to remove unwanted effects such as gravity. Using feedback on the applied force and moments, the dynamic characteristics of the model can be actively modified to alter dynamic characteristics such as the system’s natural frequency, damping, and mass and inertia properties. In this paper a dynamic model of the traverse is obtained using experimental data for simulation and control design purposes.

Centralized Adaptive Control of a Complex Flexible System

Recent advances in the technology of inexpensive sensors and actuators allow for implementation of distributed sensors and actuators for large-scale systems. This paper presents a first step towards a control architecture in which a neural network-based adaptive controller provides central hierarchy for existing or newly implemented controllers to account for system uncertainties in a complex flexible system. In contrast to previous decentralized methods wherein controllers are designed based on local measurements, the proposed method implements a central network that processes all the measured outputs and thus provides implicit coordination between subsystems. We illustrate the proposed method by considering regulation of a mass with a unknown flexible appendage and a flexible inverted pendulum.