Reduced-Order Observer Design for Robot Manipulators

This paper investigates the design of reduced-order observers for robot manipulators. Observer stability conditions are obtained based on a Lyapunov analysis. The proposed observer is enhanced with a hybrid scheme that may adjust the gains to cope with possible unbounded velocities of the robot joints. Thanks to such hybrid strategy, the observer works accurately both for robots driven by open-loop controllers and by output feedback controllers. Numerical simulations illustrate the efficacy of the reduced-order observer in several scenarios, including a comparison with the performance of a classical full-order observer

Optimizing output regulation for a class of underactuated LPV systems

@ 2017 IEEE. Personal use of these materials is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating news collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIn this paper the problem of optimizing the output regulation of an underactuated LPV system is considered. When the system is underactuated, only a subset of the outputs can be arbitrarily controlled, and the remaining ones are constrained. The problem of finding the input that minimizes a cost function of the overall output tracking error is investigated for a special class of LPV systems that admit steady-states. Moreover, it is shown how such solution is related to the inputs associated to the singularly optimal regulation of each output.Peer ReviewedPostprint (author's final draft

A multiple model adaptive architecture for the state estimation in discrete-time uncertain LPV systems

@2017 Personal use of these materials is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating news collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper addresses the problem of multiple model adaptive estimation (MMAE) for discrete-time linear parameter varying (LPV) systems that are affected by parametric uncertainty. The MMAE system relies on a finite number of local observers, each designed using a selected model (SM) from the set of possible plant models. Each local observer is an LPV Kalman filter, obtained as a linear combination of linear time invariant (LTI) Kalman filters. It is shown that if some suitable distinguishability conditions are fulfilled, the MMAE will identify the SM corresponding to the local observer with smallest output prediction error energy. The convergence of the unknown parameter estimation, and its relation with the varying parameters, are discussed. Simulation results illustrate the application of the proposed method.Peer ReviewedPostprint (author's final draft

Fault tolerant control of uncertain dynamical systems using interval virtual actuators

This is the peer reviewed version of the following article: Rotondo D, Cristofaro A, Johansen TA. Fault tolerant control of uncertain dynamical systems using interval virtual actuators. Int J Robust Nonlinear Control. 2018;28:611–624, which has been published in final form at https://doi.org/10.1002/rnc.3888. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In this paper, a model reference fault tolerant control strategy based on a reconfiguration of the reference model, with the addition of a virtual actuator block, is presented for uncertain systems affected by disturbances and sensor noise. In particular, this paper (1) extends the reference model approach to the use of interval state observers, by considering an error feedback controller, which uses the estimated bounds for the error between the real state and the reference state, and (2) extends the virtual actuator approach to the use of interval observers, which means that the virtual actuator is added to the control loop to preserve the nonnegativity of the interval estimation errors and the boundedness of the involved signals, in spite of the fault occurrence. In both cases, the conditions to assure the desired operation of the control loop are provided in terms of linear matrix inequalities. An illustrative example is used to show the main characteristics of the proposed approach.Peer ReviewedPostprint (author's final draft

Fault tolerant control of uncertain dynamical systems using interval virtual actuators

This is the peer reviewed version of the following article: Rotondo D, Cristofaro A, Johansen TA. Fault tolerant control of uncertain dynamical systems using interval virtual actuators. Int J Robust Nonlinear Control. 2018;28:611–624, which has been published in final form at https://doi.org/10.1002/rnc.3888. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In this paper, a model reference fault tolerant control strategy based on a reconfiguration of the reference model, with the addition of a virtual actuator block, is presented for uncertain systems affected by disturbances and sensor noise. In particular, this paper (1) extends the reference model approach to the use of interval state observers, by considering an error feedback controller, which uses the estimated bounds for the error between the real state and the reference state, and (2) extends the virtual actuator approach to the use of interval observers, which means that the virtual actuator is added to the control loop to preserve the nonnegativity of the interval estimation errors and the boundedness of the involved signals, in spite of the fault occurrence. In both cases, the conditions to assure the desired operation of the control loop are provided in terms of linear matrix inequalities. An illustrative example is used to show the main characteristics of the proposed approach.Peer ReviewedPostprint (author's final draft

Cooperative Localization and SLAM Based on the Extended Information Filter

Virtual realit

Decidability in robot manipulation planning

Consider the problem of planning collision-free motion of n objects movable through contact with a robot that can autonomously translate in the plane and that can move a maximum of m ≤ n objects simultaneously. This represents the abstract formulation of a general class of manipulation planning problems that are proven to be decidable in this paper. The tools used for proving decidability of this simplified manipulation planning problem are, in fact, general enough to handle the decidability problem for the wider class of systems characterized by a stratified configuration space. These include, e.g., problems of legged and multi-contact locomotion, bi-manual manipulation. In addition, the approach described does not restrict the dynamics of the manipulation system modeled

Estimation in uncertain switched systems using a bank of interval observers: local vs glocal approach

This paper discusses some issues related with the design of a bank of interval observers for uncertain switched systems, in which several sources of uncertainty are considered: parametric uncertainties, unknown disturbances, measurement noise, and unknown switching signal. More specifically, this paper focuses on analyzing the interval estimation accuracy when changes of active mode induce non-positivity of the interval state estimation errors. In particular, it is shown that by combining two types of interval observers, referred to as local and global, the accuracy and reliability of the estimation can be improved. The properties of the obtained so-called glocal observer are investigated and illustrated by means of numerical simulations.acceptedVersio

Diagnosis of Icing and Actuator Faults in UAVs Using LPV Unknown Input Observers

This paper proposes a discrete-time linear parameter varying (LPV) unknown input observer (UIO) for the diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs). The proposed approach, which is suited to an implementation on-board, exploits a complete 6-degrees of freedom (DOF) UAV model, which includes the coupled longitudinal/lateral dynamics and the impact of icing. The LPV formulation has the advantage of allowing the icing diagnosis scheme to be consistent with a wide range of operating conditions. The developed theory is supported by simulations illustrating the diagnosis of actuator faults and icing in a small UAV. The obtained results validate the effectiveness of the proposed approach

Reviewing cognitive distortions in managerial decision making: towards an integrative co-evolutionary framework

Purpose – Why and how do cognitive distortions in managerial decision making occur? All organizations are imperfect systems (Katz and Khan, 1966), with wrong decisions often just round the corner. As a consequence, addressing these important questions continues to be particularly lively in the management development area, especially in terms of its intended contribution to the de-biasing activity. Thus, through this critical review article we aim to provide the current scientific dialogue on the topic with updated lenses, which can also be innovative from some aspects. Design/methodology/approach – Our review framework is based on the recent, impactful article on biases in managerial decision making by Kahneman et al. (2011), and on Bazerman and Moore’s (2013) perspective on emanating heuristics, considered as the causes of biases. Accordingly, we derive four intertwined thematic clusters of heuristics, through which we systematically group and critically analyze the management literature mostly published on the topic since 2011. Findings – From the analyzed clusters we propose an integrative framework of emanating heuristics, which focuses on the co-evolving relationships and potentially self-reinforcing processes in and between them. Originality/value – The value of our contribution is threefold: 1) from a methodological perspective, to our knowledge, the studies adopted as the basis of our analysis have not yet been simultaneously used as a comprehensive ground for updated reviews on this topic; 2) from a conceptual perspective, the emerging integrative co-evolutionary framework can help explain the dangerous connections among cognitive traps and emanating heuristics; 3) from a practical perspective, our resulting framework can also be helpful for future de-biasing attempts in the business arena