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We address the problem of output redundancy in discrete-time linear systems, with the aim of obtaining an optimized combination of sensors for structurally rejecting certain disturbances.We frame our goal as the design problem of a nonlinear observer consisting in a linear Luenberger structure augmented with an adaptive weighted pseudoinverse combination of the available measurements. A novel optimization algorithm is proposed for the update of the dynamic weights of the pseudoinverse, together with a selector that overrides the optimizer whenever the pseudoinverse becomes close to being singular. Numerical simulations on the case study of a discrete-time mechanical system support and validate the proposed architecture.

The problem of unknown input observer design is considered for coupled PDE/ODE systems subject to incremental sector bounded nonlinearities and unknown boundary inputs. Assuming available measurements at the boundary of the distributed domain, the synthesis of the unknown input observer is based on Lyapunov methods and recast in terms of some matrix inequalities. Numerical simulations support and confirm the theoretical findings, illustrating the robust estimation performances of the proposed nonlinear unknown input observer.

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 localand global,the accuracy and reliability of the estimation can be improved. The properties of the obtained so-called glocalobserver are investigated and illustrated by means of numerical simulations.

This paper is concerned with stability and control of the parabolic p-Laplace equation. The autonomous equation is shown to be asymptotically stable, while the stronger property of exponential stability is guaranteed by the presence of lower-order terms satisfying a suitable growth condition. On the basis of these results, the problem of reference tracking using a distributed control input is investigated and, in particular, two approaches are discussed: finite-time stabilization and quadratic optimal control. Numerical simulations are provided to support and illustrate the theoretical results.

The aim of this work is characterizing the class of LPV systems that admit steady-state trajectories depending exclusively on the scheduling parameter. In particular, it will be shown that only certain parameter dependent steady-state profiles are admissible and can be reached by means of a suitable control input. Furthermore, the asymptotic stability and the stabilization of such steady-states is investigated using Lyapunov-based techniques. Extensive numerical simulations illustrate and corroborate the theoretical results. [ABSTRACT FROM AUTHOR]

We provide two nonlinear solutions to the model recovery anti-windup (MRAW) design problem, both of them relying on the definition of a set of nested ellipsoids in the state space of the anti-windup dynamics. Each ellipsoidal set arises from a convenient trade-off between size of the ellipsoid and guaranteed exponential convergence rate induced by the corresponding saturated feedback. The first solution is given by a hybrid selection of the MRAW stabilizer, relying on a natural hysteresis switching mechanism. The second solution corresponds to a Lipschitz but non-differentiable scheduled selection, which essentially smoothens out the discontinuous nature of the nested ellipsoids. We discuss the role of our design architecture and establish a number of important properties induced by the proposed controllers. Their effectiveness is comparatively illustrated on a few example studies.

This paper proposes a linear parameter varying (LPV) model reference-based control for fixed-wing unmanned aerial vehicles (UAVs), which achieves agile and high performance tracking objectives in extended flight envelopes, e.g. when near stall or deep stall flight conditions are considered. Each of the considered control loops (yaw, pitch and airspeed) delivers an error model that can be reshaped into a quasi-LPV form through an appropriate choice of the scheduling variables. The quasi-LPV error models are suitable for designing error feedback controllers using linear matrix inequalities (LMIs), which are derived within the quadratic Lyapunov framework. Simulation results are used to show the effectiveness of the proposed approach.

The phenomenon of icing, i.e. ice accretion on aircraft surfaces, affects the flight performance of unmanned aerial vehicles (UAVs). Autonomous icing detection schemes are needed in order to assure high efficiency and limit energy consumption of de-icing and anti-icing schemes. The novel contribution of this paper is to apply a linear parameter varying multiple model adaptive estimator to the model of the longitudinal nonlinear dynamics of a UAV, in order to achieve an icing diagnosis that provides information about the icing location. An advantage of applying a linear parameter varying approach is that the icing diagnosis scheme is consistent with the UAV dynamics for a wide range of operating conditions, and it uses only existing standard sensors. Simulation results are used to illustrate the application of the proposed method.

A novel approach to estimation of structured uncertainties is proposed for a class of nonlinear systems based on algebraic geometry tools. The notion of Polynomial Partition of Unity (PPU) is introduced and it constitutes a key feature of the proposed estimation technique, whose main advantage is the potentiality of being executed offline. Provided that the system dynamics satisfy some PPU and gradient properties, and collecting a sufficient number of measurements at different time steps, the values of unknown parameters are proved to be included in the finite set of common solutions to a family of polynomial equations. An optimization method based on multiple-models is then proposed to further refine the estimation. The case-study of sensorless permanent magnet synchronous motors is presented as a support to theoretical developments. [ABSTRACT FROM AUTHOR]

This paper proposes an actuator failure tolerant robust control scheme for underwater Remotely Operated Vehicles (ROVs). A reduced order observer has been introduced for estimating the ROV velocities and a sliding mode control law has been developed using the available position measurements and the velocity estimates provided by the observer to achieve output regulation. A thruster failure is shown to be detectable simply checking the presence of any deviation of the observed sliding surfaces. Moreover, an isolation policy for the failed thruster is proposed. Finally, control reconfiguration is performed exploiting the inherent redundancy of actuators with the implementation of an adaptive input allocation architecture. An extensive simulation study has been performed, supporting the effectiveness of the proposed approach.

A set of alternative collision avoidance control behaviors are parameterized by two parameters: Offsets to the guidance course angle commanded to the autopilot, and changes to the propulsion command ranging from nominal speed to full reverse. Using predictions of the trajectories of the obstacles and ship, the compliance with the COLREGS rules and collision hazards associated with the alternative control behaviors are evaluated on a finite prediction horizon. The optimal control behavior is computed in a model predictive control implementation strategy. Uncertainty can be accounted for by increasing safety margins or evaluating multiple scenarios for each control behavior. Simulations illustrate the effectiveness in test cases involving multiple dynamic obstacles and uncertainty associated with sensors and predictions.

This paper presents a contribution to the problem of obtaining an optimal synthesis for shortest paths for a unicycle guided by an on-board limited Field-Of-View (FOV) sensor, which must keep a given landmark in sight. Previous works on this subject have provided an optimal synthesis for the case in which the FOV is limited in the horizontal directions (H-FOV, i.e., left and right boundaries). In this paper we study the complementary case in which the FOV is limited only in the vertical direction (V-FOV, i.e., upper and lower boundaries). With respect to the H-FOV case, the vertical limitation is all but a simple extension. Indeed, not only the geometry of extremal arcs is different, but also a more complex structure of the synthesis is revealed by analysis. We will indeed show that there exist initial configurations for which the optimal path does not exist. In such cases, we provide an $\varepsilon$-optimal path whose length approximates arbitrarily well any other shorter path. Finally, we provide a partition of the motion plane in regions such that the optimal or $\varepsilon$-optimal path from each point in that region is univocally determined. [ABSTRACT FROM AUTHOR]

This technical note proposes the use of a time-varying sliding surface for stabilizing linear, possibly unstable, Multi-Input plants subject to saturating actuators, in the presence of bounded matched uncertainties. The present work generalizes our previous contributions in several different directions. First, the constructive procedure is generalized, and a result about asymptotical stabilization is given, under the usual assumption of the saturation threshold being larger than the bound on uncertainties. Another goal of the technical note is to widen the set of plants considered including linear Multi-Input systems. Simulation results show both the effectiveness of the control technique and the low computational burden required. [ABSTRACT FROM AUTHOR]

In this paper, the behavior of scalar multi-agent systems over networks subject to time-driven jumps. Assuming that all agents communicate through distinct communication digraphs at jump and flow times, the asymptotic multi-consensus behavior of the hybrid network is explicitly characterized. The hybrid multi-consensus is shown to be associated with a suitable partition that is almost equitable for both the jump and flow communication digraphs. In doing so, no assumption on the underlying digraphs is introduced. Finally, the coupling rules making the multi-consensus subspace attractive are established. Several simulation examples illustrate the theoretical results.