Disturbance rejection for nonlinear uncertain systems with output measurement errors: Application to a helicopter model

As a virtual sensor, disturbance observer provides an alternative approach to reconstruct lumped disturbances (including external disturbances and system uncertainties) based upon system states/outputs measured by physical sensors. Not surprisingly, measurement errors bring adverse effects on the control performance and even the stability of the closed-loop system. Toward this end, this paper investigates the problem of disturbance observer based control for a class of disturbed uncertain nonlinear systems in the presence of unknown output measurement errors. Instead of inheriting from the estimation-error-driven structure of Luenberger type observer, the proposed disturbance observer only explicitly uses the control input. It has been proved that the proposed method endows the closed-loop system with strong robustness against output measurement errors and system uncertainties. With rigorous analysis under the semiglobal stability criterion, the guideline of gain choice based upon the proposed structure is provided. To better demonstrate feature and validity of the proposed method, numerical simulation and comparative experiments of a helicopter model are implemented

Analytical techniques: A compilation

A compilation, containing articles on a number of analytical techniques for quality control engineers and laboratory workers, is presented. Data cover techniques for testing electronic, mechanical, and optical systems, nondestructive testing techniques, and gas analysis techniques

Fault estimation algorithms: design and verification

The research in this thesis is undertaken by observing that modern systems are becoming more and more complex and safety-critical due to the increasing requirements on system smartness and autonomy, and as a result health monitoring system needs to be developed to meet the requirements on system safety and reliability. The state-of-the-art approaches to monitoring system status are model based Fault Diagnosis (FD) systems, which can fuse the advantages of system physical modelling and sensors' characteristics. A number of model based FD approaches have been proposed. The conventional residual based approaches by monitoring system output estimation errors, however, may have certain limitations such as complex diagnosis logic for fault isolation, less sensitiveness to system faults and high computation load. More importantly, little attention has been paid to the problem of fault diagnosis system verification which answers the question that under what condition (i.e., level of uncertainties) a fault diagnosis system is valid. To this end, this thesis investigates the design and verification of fault diagnosis algorithms. It first highlights the differences between two popular FD approaches (i.e., residual based and fault estimation based) through a case study. On this basis, a set of uncertainty estimation algorithms are proposed to generate fault estimates according to different specifications after interpreting the FD problem as an uncertainty estimation problem. Then FD algorithm verification and threshold selection are investigated considering that there are always some mismatches between the real plant and the mathematical model used for FD observer design. Reachability analysis is drawn to evaluate the effect of uncertainties and faults such that it can be quantitatively verified under what condition a FD algorithm is valid. First the proposed fault estimation algorithms in this thesis, on the one hand, extend the existing approaches by pooling the available prior information such that performance can be enhanced, and on the other hand relax the existence condition and reduce the computation load by exploiting the reduced order observer structure. Second, the proposed framework for fault diagnosis system verification bridges the gap between academia and industry since on the one hand a given FD algorithm can be verified under what condition it is effective, and on the other hand different FD algorithms can be compared and selected for different application scenarios. It should be highlighted that although the algorithm design and verification are for fault diagnosis systems, they can also be applied for other systems such as disturbance rejection control system among many others

A Hybrid Controller for Stability Robustness, Performance Robustness, and Disturbance Attenuation of a Maglev System

Devices using magnetic levitation (maglev) offer the potential for friction-free, high-speed, and high-precision operation. Applications include frictionless bearings, high-speed ground transportation systems, wafer distribution systems, high-precision positioning stages, and vibration isolation tables. Maglev systems rely on feedback controllers to maintain stable levitation. Designing such feedback controllers is challenging since mathematically the electromagnetic force is nonlinear and there is no local minimum point on the levitating force function. As a result, maglev systems are open-loop unstable. Additionally, maglev systems experience disturbances and system parameter variations (uncertainties) during operation. A successful controller design for maglev system guarantees stability during levitating despite system nonlinearity, and desirable system performance despite disturbances and system uncertainties. This research investigates five controllers that can achieve stable levitation: PD, PID, lead, model reference control, and LQR/LQG. It proposes an acceleration feedback controller (AFC) design that attenuates disturbance on a maglev system with a PD controller. This research proposes three robust controllers, QFT, Hinf , and QFT/Hinf , followed by a novel AFC-enhanced QFT/Hinf (AQH) controller. The AQH controller allows system robustness and disturbance attenuation to be achieved in one controller design. The controller designs are validated through simulations and experiments. In this research, the disturbances are represented by force disturbances on the levitated object, and the system uncertainties are represented by parameter variations. The experiments are conducted on a 1 DOF maglev testbed, with system performance including stability, disturbance rejection, and robustness being evaluated. Experiments show that the tested controllers can maintain stable levitation. Disturbance attenuation is achieved with the AFC. The robust controllers, QFT, Hinf , QFT/ Hinf, and AQH successfully guarantee system robustness. In addition, AQH controller provides the maglev system with a disturbance attenuation feature. The contributions of this research are the design and implementation of the acceleration feedback controller, the QFT/ Hinf , and the AQH controller. Disturbance attenuation and system robustness are achieved with these controllers. The controllers developed in this research are applicable to similar maglev systems

Learning and Reacting with Inaccurate Prediction: Applications to Autonomous Excavation

Motivated by autonomous excavation, this work investigates solutions to a class of problem where disturbance prediction is critical to overcoming poor performance of a feedback controller, but where the disturbance prediction is intrinsically inaccurate. Poor feedback controller performance is related to a fundamental control problem: there is only a limited amount of disturbance rejection that feedback compensation can provide. It is known, however, that predictive action can improve the disturbance rejection of a control system beyond the limitations of feedback. While prediction is desirable, the problem in excavation is that disturbance predictions are prone to error due to the variability and complexity of soil-tool interaction forces. This work proposes the use of iterative learning control to map the repetitive components of excavation forces into feedforward commands. Although feedforward action shows useful to improve excavation performance, the non-repetitive nature of soil-tool interaction forces is a source of inaccurate predictions. To explicitly address the use of imperfect predictive compensation, a disturbance observer is used to estimate the prediction error. To quantify inaccuracy in prediction, a feedforward model of excavation disturbances is interpreted as a communication channel that transmits corrupted disturbance previews, for which metrics based on the sensitivity function exist. During field trials the proposed method demonstrated the ability to iteratively achieve a desired dig geometry, independent of the initial feasibility of the excavation passes in relation to actuator saturation. Predictive commands adapted to different soil conditions and passes were repeated autonomously until a pre-specified finish quality of the trench was achieved. Evidence of improvement in disturbance rejection is presented as a comparison of sensitivity functions of systems with and without the use of predictive disturbance compensation

Hardware Implementation of Active Disturbance Rejection Control for Vibrating Beam Gyroscope

Obtaining the approximation of rotation rate form a Z-Axis MEMS gyroscope is a challenging problem. Currently, most commercially available MEMS gyroscopes are operating in an open-loop for purposes of simplicity and cost reduction. However, MEMS gyroscopes are still fairly expensive and are not robust during operation. The purpose of this research was to develop a high-performance and low-cost MEMS gyroscope using analog Active Disturbance Rejection Control (ADRC) system. By designing and implementing analog ADRC both above requirements were satisfied. Analog ADRC provides the fastest response time possible (because the circuit is analog), eliminates both internal and external disturbances, and increases the bandwidth of the gyroscope beyond its natural frequency. On the other hand, the overall design is extremely economical, given that the system is built using pure active and passive analog components. This work, besides achieving high-performance and providing low-cost solution, furnishes two novel designs concepts. First, Active Disturbance Rejection Controller can now be build using pure analog circuit, which has never been done before. Second, it is the first time that the advanced controller has been successfully implemented in hardware to control an inertial rate sensor like gyroscope. This work provides a novel solution to applications that require high-performance and low-cost inertial sensor

Hardware Implementation of Active Disturbance Rejection Control for Vibrating Beam Gyroscope

Obtaining the approximation of rotation rate form a Z-Axis MEMS gyroscope is a challenging problem. Currently, most commercially available MEMS gyroscopes are operating in an open-loop for purposes of simplicity and cost reduction. However, MEMS gyroscopes are still fairly expensive and are not robust during operation. The purpose of this research was to develop a high-performance and low-cost MEMS gyroscope using analog Active Disturbance Rejection Control (ADRC) system. By designing and implementing analog ADRC both above requirements were satisfied. Analog ADRC provides the fastest response time possible (because the circuit is analog), eliminates both internal and external disturbances, and increases the bandwidth of the gyroscope beyond its natural frequency. On the other hand, the overall design is extremely economical, given that the system is built using pure active and passive analog components. This work, besides achieving high-performance and providing low-cost solution, furnishes two novel designs concepts. First, Active Disturbance Rejection Controller can now be build using pure analog circuit, which has never been done before. Second, it is the first time that the advanced controller has been successfully implemented in hardware to control an inertial rate sensor like gyroscope. This work provides a novel solution to applications that require high-performance and low-cost inertial sensor

Aeronautical Engineering. A continuing bibliography with indexes, supplement 156

This bibliography lists 288 reports, articles and other documents introduced into the NASA scientific and technical information system in December 1982