Robust Control

The need to be tolerant to changes in the control systems or in the operational environment of systems subject to unknown disturbances has generated new control methods that are able to deal with the non-parametrized disturbances of systems, without adapting itself to the system uncertainty but rather providing stability in the presence of errors bound in a model. With this approach in mind and with the intention to exemplify robust control applications, this book includes selected chapters that describe models of H-infinity loop, robust stability and uncertainty, among others. Each robust control method and model discussed in this book is illustrated by a relevant example that serves as an overview of the theoretical and practical method in robust control

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

Reachability Analysis of Cyber-Physical Systems Using Symbolic-Numeric Techniques

In this thesis, we address the problem of reachability analysis in cyber-physical systems. These are systems engineered by interfacing computational components with the physical world. They provide partially or fully automated safety-critical services in the form of medical devices, autonomous vehicles, avionics and power systems. We propose techniques to reason about the reachability of such systems, and provide methods for falsifying their safety properties. We model the cyber component as a software program and the physical component as a hybrid dynamical system. Unlike model based analysis, which uses either a purely symbolic or a numerical approach, we argue in favor of using a combination of the two. We justify this by noting that the software program running on a computer is completely specified and has precise semantics. In contrast, the model of the physical system is only an approximation. Hence, we treat the former as a white box, but treat the latter as a black box. Using symbolic methods for the cyber components and numerical methods for hybrid systems, we carefully capture the complex behaviors of software programs and circumvent the difficulty in analyzing complex models developed through first principles. To combine the two techniques, we use a Counterexample Guided Abstraction Refinement (CEGAR) framework. Furthermore, we explore learning techniques like regression and piecewise affine modeling to estimate and represent black box hybrid dynamical systems for the purpose of falsification. We use prototype implementations to demonstrate the effectiveness of presented ideas. Using non-trivial benchmarks, we compare their performance against the state of the art. We also comment on their applicability and discuss ideas for further improvement

Robust adaptive flight control systems in the presence of time delay

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from department-submitted PDF version of thesis.Includes bibliographical references (p. 161-165).Adaptive control technology is a promising candidate to deliver high performance in aircraft systems in the presence of uncertainties. Currently, there is a lack of robustness guarantees against time delay with the difficulty arising from the fact that the underlying problem is nonlinear and time varying. Existing results for this problem have been quite limited, with most results either being local or at best, semi-global. In this thesis, robust adaptive control for a class of plants with global boundedness in the presence of time-delay is established. This class of plants pertains to linear systems whose states are accessible. The global boundedness is accomplished using a standard adaptive control law with a projection algorithm for a range of non-zero delays. The upper bound of such delays, i.e. the delay margin, is explicitly computed. The results of this thesis provide a highly desirable fundamental property of adaptive control, robustness to time-delays, a necessary step towards developing theoretically verifiable flight control systems.by Megumi Matsutani.Ph.D

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

Adaptive Control

Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems

Discrete Modeling and Sliding Mode Control of Piezoelectric Actuators

With the ability to generate fine displacements with a resolution down to sub-nanometers, piezoelectric actuators (PEAs) have found wide applications in various nano-positioning systems. However, existence of various effects in PEAs, such as hysteresis and creep, as well as dynamics can seriously degrade the PEA performance or even lead to instability. This raises a great need to model and control PEAs for improved performance, which have drawn remarkable attention in the literature. Sliding mode control (SMC) shows its potential to the control of PEA, by which the hysteresis and other nonlinear effects can be regard as disturbance to the dynamic model and thus rejected or compensated by its switching control. To implement SMC in digital computers, this research is aimed at developing novel discrete models and discrete SMC (DSMC)-based control schemes for PEAs, along with their experimental validation. The first part of this thesis concerns with the modeling and control of one-degree of freedom (DOF) PEA, which can be treated as a single-input-single-output (SISO) system. Specifically, a novel discrete model based on the concept of auto-regressive moving average (ARMA) was developed for the PEA hysteresis; and to compensate for the PEA hysteresis and improve its dynamics, an output tracking integrated discrete proportional-integral-derivative-based SMC (PID-SMC) was developed. On this basis, by making use of the availability of PEA hysteresis models, two control schemes, named “the discrete inversion feedforward based PID-SMC” and “the discrete disturbance observer (DOB)-based PID-SMC”, were further developed. To illustrate the effectiveness of the developed models and control schemes, experiments were designed and conducted on a commercially available one-DOF PEA, as compared with the existing ones. The second part of the thesis presents the extension of the developed modeling and control methods to multi-DOF PEAs. Given the fact that details with regard to the PEA internal configurations is not typically provided by the manufacturer, a state space model based on the black box system identification was developed for the three-DOF PEA. The developed model was then integrated in the output tracking based discrete PID-SMC, with its effectiveness verified through the experiments on a commercially available three-DOF PEA. The superiority of the proposed control method over the conventional PID controller was also experimentally investigated and demonstrated. Finally, by integrating with a DOB in the discrete PID-based SMC, a novel control scheme is resulted to compensate for the nonlinearities of the three-DOF PEA. To verify its effectiveness, the discrete DOB based PID-SMC was applied in the control experiments and compared with the existing SMC. The significance of this research lies in the development of the discrete models and PID-based SMC for PEAs, which is of great help to improve their performance. The successful application of the proposed method in the control of multi-DOF PEA allows the application of SMC to the control of complicated multi-inputs-multi-outputs (MIMO) systems without details regarding the internal configuration. Also, integration of the inversion based feedforward control and the DOB in the SMC design has been proven effective for the tracking control of PEAs

Feature relative navigation for automous underwater vehicles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1997.Includes bibliographical references (leaves 184-196).by Andrew Arnold Bennett.Ph.D

Information inference for cyber-physical systems with application to aviation safety and space situational awareness

Due to the rapid advancement of technologies on sensors and processors, engineering systems have become more complex and highly automated to meet ever stringent performance and safety requirements. These systems are usually composed of physical plants (e.g., aircraft, spacecraft, ground vehicles, etc.) and cyber components (e.g., sensing, communication, and computing units), and thus called as Cyber-Physical Systems (CPSs). For safe, efficient, and sustainable operation of a CPS, the states and physical characteristics of the system need to be effectively estimated or inferred from sensing data by proper information inference algorithms. However, due to the complex nature of the interacting multiple-heterogeneous elements of the CPS, the information inference of the CPS is a challenging task, where exiting methods designed for a single-element dynamic system (or for even dynamic systems with multiple-homogenous elements) could not be applicable. Moreover, the increasing number of sensor resources in CPSs makes the task even more challenging as meaningful information needs to be accurately and effectively inferred from huge amount of data, which is usually noise corrupted. Many aerospace systems such as air traffic control systems, pilot-automation integrated systems, networked unmanned aircraft systems, and space surveillance systems are good examples of CPSs and thus have the aforementioned challenging problems. The goals of this research are to 1) overcome the challenges in complex CPSs by developing new information inference methodologies based on control, estimation, hybrid systems and information theories, and 2) successfully apply them to various complex and safety-critical aerospace systems such as air transportation systems, space surveillance systems, and integrated human-machine systems, to promote their efficiency and safety