Sliding mode adaptive state observation for time-delay uncertain nonlinear systems

In this paper a method to design robust adaptive sliding mode observers (ASMO) for a class of nonlinear time- delay systems with uncertainties, is proposed. The objective is to achieve insensitivity and robustness of the proposed sliding mode observer to matched disturbances. A novel systematic design method is synthesized to solve matching conditions and compute observer stabilizing gains. The Lyapunov-Krasovskii theorem is employed to prove the ultimate stability with arbitrary boundedness radius of the estimation error of the proposed filter. Finally, the ability of ASMO for fault reconstruction is studied

Learning curve using the Sunnybrook Facial Grading System in assessing facial palsy:An observational study in 100 patients

Little is known about facial function assessments of inexperienced observers in facial palsy. In this observational study learning curve was examined of two inexperienced observers assessing facial function of 100 patients using the Sunnybrook Facial Grading System. Interobserver agreement gradually improved over time, stabilizing after approximately 70 assessments. Best agreement on the voluntary movement subscore was observed, followed by synkinesis and resting symmetry subscores. Inexperienced observers can perform facial function assessments in facial palsy, but should be adequately trained first

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

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

Autopoietic organization of firm: an illustration for the construction industry

Generally poor productivity, delays, low profitability and exceeded budgets are Common problems in modern construction management, however it seems that a basic obstacle lies far deeper in the understanding of a firm's fundamental mission, its existence. The main objective of this paper therefore is to examine the operational living of a construction firm and by doing that to reveal the key problem or the solution for a construction firm - its organization. A firm as a social system in which interactions between its constitutive components (employees) are surordinated to its maintenance (keeping a system alive) is an autopoietic social system. Two domains of external perturbations are uncovered to which a construction firm has to adapt (market driven and project driven perturbations). Constructed conceptual model of an autopoietic organization is based upon two necessary and sufficient operational domains that a firm has to create in order to become an autopoietic, adaptive social system. The first one is a domain of interactions between employees and other operationally external systems, which is representing an idea-generating domain of interactions. The second is employee's autonomous operational domain, which embodies employee's autonomy and individuality and represents a necessary condition for the establishment of an idea-generating domain. Finally, it is recognized that interactions within these four domains keep a construction firm alive

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

Comparison of a Reduced-Order Observer and a Full-Order Observer for Sensorless Synchronous Motor Drives

Two back-electromotive-force (EMF)-based position observers are compared for motion-sensorless synchronous motor drives: the reduced-order observer and the adaptive full-order observer. A stabilizing gain is proposed for the adaptive full-order observer, which guarantees the local stability of the closed-loop system, if the motor parameters are known. Equations for the steady-state position error and for the linearized estimation-error dynamics under erroneous parameters are derived, and the robustness of the two observers against parameter errors is analyzed and compared. The observers are experimentally evaluated using a 6.7-kW synchronous reluctance motor drive in low-speed operation and under parameter errors. The gain selection of the reduced-order observer is easier, but the adaptive full-order observer can be made more robust against parameter variations and noise.Peer reviewe