A State-Space Approach to Parametrization of Stabilizing Controllers for Nonlinear Systems

A state-space approach to Youla-parametrization of stabilizing controllers for linear and nonlinear systems is suggested. The stabilizing controllers (or a class of stabilizing controllers for nonlinear systems) are characterized as (linear/nonlinear) fractional transformations of stable parameters. The main idea behind this approach is to decompose the output feedback stabilization problem into state feedback and state estimation problems. The parametrized output feedback controllers have separation structures. A separation principle follows from the construction. This machinery allows the parametrization of stabilizing controllers to be conducted directly in state space without using coprime-factorization

A Passivity-based Nonlinear Observer and a Semi-global Separation Principle

The main topics of this dissertation are the observer problem and its applications to the output feedback stabilization for nonlinear systems. The observer problem refers to the general problem of reconstructing the state of a system only with the input and output information of the system. While the problem has been solved in depth for linear systems, the nonlinear counterpart has not yet been wholly solved in the general sense. Motivated by this fact, we pursue the general method of observer construction in order to provide much larger classes of systems with the design method. In particular, we propose a new approach to the observer problem via the passivity, which is therefore named the passivity framework for state observer. It begins by considering the observer problem as the static output feedback stabilization for a suitably defined error dynamics. We then make use of the output feedback passification which is the recent issue in the literature, to the design of observer as a tool for static output feedback stabilization. The proposed framework includes the precise definition of passivity-based state observer (PSO), the design scheme of it, and the redesign technique for a given PSO to have the robust property to the measurement disturbances in the sense of input-to-state stability. Moreover, it is also shown that the framework of PSO provides the unified viewpoint to the earlier works on the nonlinear observer and generalizes them much more. As well as the new notion of PSO, two other methods of observer design are proposed for the special classes of nonlinear systems. They are, in fact, a part of or an extension of the design scheme of PSO. However, compared to the general design scheme of PSO, these methods specifically utilize the particular structure of the system, which therefore lead to more explicit techniques for the observer design. The first one we present for the special cases is the semi-global observer, which extends with much flexibility the earlier designs of Gauthiers high-gain observer. By introducing the saturation function into the observer design, several difficulties to construct the high-gain observer (e.g. peaking phenomenon, etc.) are effectively eliminated. As the second result, we propose a novel design method for the nonlinear observer, which may be regarded as the observer backstepping since the design is recursively carried out similarly to the well-known backstepping control design. It enlarges the class of systems, for which the observer can be designed, to the systems that have the non-uniformly observable modes and detectable modes as well as uniformly observable modes. The other topic of the dissertation is the output feedback stabilization of nonlinear systems. Our approach to the problem is the state feedback control law plus the state observer, therefore, in view of the so-called separation principle. The benefits of the approach via separation principle is that the designs of state feedback law and observer are completely separated so that any state feedback and any observer can be combined to yield the output feedback controller, which is well-known for linear systems. Unfortunately, it has been pointed out that the separation principle for nonlinear systems does not hold in the global sense, and thus the alternative semiglobal separation principle (i.e., the separation principle on a bounded region rather than on the global region) has been studied so far. In this dissertation, we continue that direction of research and establish the semi-global separation principle that shares the more common properties with the linear one than the earlier works do. In particular, it is shown that, for general nonlinear systems, when a state feedback control stabilizes an equilibrium point with a certain bounded region of attraction, it is also stabilized by an output feedback controller with arbitrarily small loss of the region, under uniform observability. The proposed output feedback controller has the dynamic order n which is the same as the order of the plant, which is the essential difference from the earlier works. As a consequence, the nonlinear separation principle enables the state observer of the dissertation to be used in conjunction with any state feedback for the output feedback stabilization, although the observer problem in itself is worthwhile in several practical situations

Robust Asymptotic Stabilization of Nonlinear Systems with Non-Hyperbolic Zero Dynamics

In this paper we present a general tool to handle the presence of zero dynamics which are asymptotically but not locally exponentially stable in problems of robust nonlinear stabilization by output feedback. We show how it is possible to design locally Lipschitz stabilizers under conditions which only rely upon a partial detectability assumption on the controlled plant, by obtaining a robust stabilizing paradigm which is not based on design of observers and separation principles. The main design idea comes from recent achievements in the field of output regulation and specifically in the design of nonlinear internal models.Comment: 30 pages. Preliminary versions accepted at the 47th IEEE Conference on Decision and Control, 200

Output-Feedback Control of Nonlinear Systems using Control Contraction Metrics and Convex Optimization

Control contraction metrics (CCMs) are a new approach to nonlinear control design based on contraction theory. The resulting design problems are expressed as pointwise linear matrix inequalities and are and well-suited to solution via convex optimization. In this paper, we extend the theory on CCMs by showing that a pair of "dual" observer and controller problems can be solved using pointwise linear matrix inequalities, and that when a solution exists a separation principle holds. That is, a stabilizing output-feedback controller can be found. The procedure is demonstrated using a benchmark problem of nonlinear control: the Moore-Greitzer jet engine compressor model.Comment: Conference submissio

A Separation Principle on Lie Groups

For linear time-invariant systems, a separation principle holds: stable observer and stable state feedback can be designed for the time-invariant system, and the combined observer and feedback will be stable. For non-linear systems, a local separation principle holds around steady-states, as the linearized system is time-invariant. This paper addresses the issue of a non-linear separation principle on Lie groups. For invariant systems on Lie groups, we prove there exists a large set of (time-varying) trajectories around which the linearized observer-controler system is time-invariant, as soon as a symmetry-preserving observer is used. Thus a separation principle holds around those trajectories. The theory is illustrated by a mobile robot example, and the developed ideas are then extended to a class of Lagrangian mechanical systems on Lie groups described by Euler-Poincare equations.Comment: Submitted to IFAC 201