A helicopter is a complex nonlinear system and also an under actuated system with fewer independent control actuators than degrees of freedom to be controlled, making the control difficult. There is a growing interest in the modeling and control of such systems using nonlinear dynamic models and nonlinear control. Analytical techniques based on Lyapunov theory are then used to design the controller and still the design can become extremely complex. Hence the existing control methods use linearization techniques on the actual nonlinear dynamics of the plant and linear control techniques. The resulting performance may not be satisfactory, especially when the system is subjected to unknown and sudden disturbances. In this thesis, we present a new Nonlinear and Adaptive controller design which uses the actual nonlinear model of the helicopter and not a linearized version. The design methodology basically involves making the combined dynamics of the helicopter and the controller resemble the dynamics of a nonlinear time varying electrical circuit having the required properties using a process similar to reverse engineering. The circuit template in turn is formed from well defined time varying and/or nonlinear electrical elements and using proper interconnections. The kind of elements used and the general form of the dynamics derived will depend upon the application. For example in the helicopter case, the closed loop dynamics of the helicopter and the controller expressed in terms of the error variable should point to a NLTV circuit with only passive elements. For this, the reactive elements should have their relaxation points (the points where the stored energy is zero) at and only at the origin. Also the stored energy should be monotonically increasing. We can bring in any knowledge including the structure that we have about the plant being controlled in enhancing the circuit.

This paper considers the nonlinear adaptive model following control of a 3-DOF model helicopter. The system model here is not decouplable by static state feedback, and the nonlinear structure algorithm is applied. When a simple model following controller is designed, it is not easy to obtain a good control performance mainly due to the parameter uncertainties. Then, two parameter identification schemes are discussed: The first scheme is based on the differential equation model. This scheme is unable to obtain a good tracking control performance because of the inaccuracy of the estimated velocity and acceleration signals. The second scheme is designed for a dynamics model derived by applying integral operators to the differential equations expressing the system dynamics. Hence, this identification algorithm requires neither velocity nor acceleration signals. The experimental results show that the second method yields a better tracking result, although tracking errors still remain. Finally, we introduce additional terms into the equations of motion to express model uncertainties and external disturbances. With reference to experimental results, this modification is shown to further improve the tracking control performance.

In Hubschraubern kommen mitunter aufwändige regelungstechnische Verfahren zum Einsatz, um ein intuitiv steuerbares und stabiles Verhalten der Maschine zu erzeugen. Klassische Ansätze in der Entwicklung setzen dabei auf Iterationen aus Systemidentifikation und Auslegung des Systems im Frequenzbereich. In diesem Buch wird vor dem Hintergrund der nur zu gerne unterschätzten Problematik der begrenzten Bandbreiten eine robuste adaptive Regelung eingeführt. Dazu wird ein hochfrequent-aktualisierender L1-adaptiver Regler entsprechend angepasst, ein neues adaptives Gesetz der Ausgangsrückführung eingeführt, eine neue Strategie zur Auslegung der Zustandsrückführung vorgestellt, und für den sicherheitskritischen Aspekt Effekte von Ungenauigkeiten im Rechentakt und von Sensorrauschen evaluiert. Während klassische Ansätze durch nichtlineare Optimierung weitestgehend automatisierbar sind und dennoch die Notwendigkeit wiederholter Flugtests nicht verhindern können, ist der L1-adaptive Regler bei entsprechendem Systemverständnis besonders geeignet, Entwicklungszeiten zu verkürzen. Strenge mathematische Beweise untermauern die Stabilität und Robustheit der eingeführten Algorithmen, wobei die Flugeigenschaften in einem Forschungssimulator verifiziert werden. Often, very complex controller techniques are applied to helicopters for generating an intuitively controllable and stable behavior of the aircraft. In legacy controllers, a number of iterations of system identification and loop shaping methods in frequency domain have to be conducted. In this book, a robust adaptive control theory is introduced, with the often underestimated fact of only limited available bandwidths in mind. To this end, the high-frequency adapting L1-adaptive controller is adjusted, a new adaptive law for output feedback is introduced, a new strategy for defining the design of a state feedback controller is proposed, and effects of uncertainties in the processor clock rate and of sensor noise are evaluated for taking the safety critical nature of the system into account. While legacy approaches can be automated by nonlinear optimization techniques and yet cannot eliminate the necessity of repeated flight tests, the L1-adaptive controller is particularly suitable to reduce development time, provided a sufficiently deep understanding of the system is available. Rigorous mathematical proofs substantiate the stability and robustness of the algorithms as shown, while performance and handling qualities are verified in a research simulator.

Modeling, Control and Coordination of Helicopter Systems provides a comprehensive treatment of helicopter systems, ranging from related nonlinear flight dynamic modeling and stability analysis to advanced control design for single helicopter systems, and also covers issues related to the coordination and formation control of multiple helicopter systems to achieve high performance tasks. Ensuring stability in helicopter flight is a challenging problem for nonlinear control design and development. This book is a valuable reference on modeling, control and coordination of helicopter systems,providing readers with practical solutions for the problems that still plague helicopter system design and implementation. Readers will gain a complete picture of helicopters at the systems level, as well as a better understanding of the technical intricacies involved.

The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.

Nonlinear problems in flight control have stimulated cooperation among engineers and scientists from a range of disciplines. Developments in computer technology allowed for numerical solutions of nonlinear control problems, while industrial recognition and applications of nonlinear mathematical models in solving technological problems is increasing. The aim of the book Advances in Flight Control Systems is to bring together reputable researchers from different countries in order to provide a comprehensive coverage of advanced and modern topics in flight control not yet reflected by other books. This product comprises 14 contributions submitted by 38 authors from 11 different countries and areas. It covers most of the currents main streams of flight control researches, ranging from adaptive flight control mechanism, fault tolerant flight control, acceleration based flight control, helicopter flight control, comparison of flight control systems and fundamentals. According to these themes the contributions are grouped in six categories, corresponding to six parts of the book.