Data-enabled extremum seeking: A cooperative concurrent learning-based approach

This paper introduces a new class of feedback-based data-driven extremum seeking algorithms for the solution of model-free optimization problems in smooth continuous-time dynamical systems. The novelty of the algorithms lies on the incorporation of memory to store recorded data that enables the use of information-rich datasets during the optimization process, and allows to dispense with the time-varying dither excitation signal needed by standard extremum seeking algorithms that rely on a persistence of excitation (PE) condition. The model-free optimization dynamics are developed for single-agent systems, as well as for multi-agent systems with communication graphs that allow agents to share their state information while preserving the privacy of their individual data. In both cases, sufficient richness conditions on the recorded data, as well as suitable optimization dynamics modeled by ordinary differential equations are characterized in order to guarantee convergence to a neighborhood of the solution of the extremum seeking problems. The performance of the algorithms is illustrated via different numerical examples in the context of source-seeking problems in multivehicle systems.     

Multi‐parametric extremum seeking‐based iterative feedback gains tuning for nonlinear control

We study in this paper the problem of iterative feedback gains auto‐tuning for a class of nonlinear systems. For the class of input–output linearizable nonlinear systems with bounded additive uncertainties, we first design a nominal input–output linearization‐based robust controller that ensures global uniform boundedness of the output tracking error dynamics. Then, we complement the robust controller with a model‐free multi‐parametric extremum seeking control to iteratively auto‐tune the feedback gains. We analyze the stability of the whole controller, that is, the robust nonlinear controller combined with the multi‐parametric extremum seeking model‐free learning algorithm. We use numerical tests to demonstrate the performance of this method on a mechatronics example. Copyright © 2016 John Wiley & Sons, Ltd.     

Finite-time extremum seeking control for a class of unknown static maps

This article proposes an extremum-seeking control design that achieves finite-time stability of the optimum of an unknown measured cost function. The finite-time extremum-seeking control technique is shown to achieve finite-time practical stability of the optimum of the cost function. The main characteristic of the proposed extremum seeking control approach is that the corresponding target averaged system achieves finite-time stability. A simulation study is presented to demonstrate the effectiveness of the approach.     

Model‐based vs data‐driven adaptive control: An overview

In this paper, we present an overview of adaptive control by contrasting model‐based approaches with data‐driven approaches. Indeed, we propose to classify adaptive controllers into two main subfields, namely, model‐based adaptive control and data‐driven adaptive control. In each subfield, we cite monographs, survey papers, and recent research papers published in the last few years. We also include a few simple examples to illustrate some general concepts in each subfield.     

Application of passivity and cascade structure to robust control against loss of actuator effectiveness

In this paper the problem studied is passive fault tolerant control with respect to loss of actuator effectiveness, for nonlinear models. The main idea of the work is the formulation of the faulty models as cascade systems of the healthy models with the fault models. Based on this simple formulation, passivity theory is used to ensure the stability of the faulty system. We also study the problem of input saturation. The type of faults studied here are constant as well as time‐varying faults. The validity of the proposed controllers is shown on several numerical examples. Copyright © 2009 John Wiley & Sons, Ltd.     

Special issue on omnidirectional vision and its applications

Machine Vision and Applications -     

Flexible Links Manipulators: from Modelling to Control

This paper relates recent results obtained in the field of modelling and control of flexible link manipulators and proposes an investigation of the problem raised by this type of systems (at least in the planar case). First, adopting the modal floating frame approach and the Newton–Euler formalism, we propose an extension of the models for control to the case of fast dynamics and finite deformations. This dynamic model is based on a nonlinear generalisation of the standard Euler–Bernoulli kinematics. Then, based on the models recalled we treat the end-effector tracking problem for the one-link case as well as for the planar multi-link case. For the one-link system, we propose two methods, the first one is based on causal stable inversion of linear non-minimum phase model via output trajectory planning. The other one is an algebraic scheme, based on the parametrization of linear differential operators. For the planar multi-link case the control law proposed is based on causal stable inversion over a bounded time domain of nonlinear non-minimum phase systems. Numerical tests are presented together with experimental results, displaying the well behaved of these approaches.     

Online Parameter Identification for State of Power Prediction of Lithium-ion Batteries in Electric Vehicles Using Extremum Seeking

International Journal of Control, Automation and Systems - Accurate state-of-power (SOP) estimation is critical for building battery systems with optimized performance and longer life in electric...     

Hybrid Stereo Configurations Through a Cylindrical Sensor Calibration

This paper deals with the calibration of a cylindric omnidirectional imaging system, based on a rotating 2,048 pixels linear camera which provides high definition panoramas. The two-step algorithm relies on line-segment projections as calibration features, which are sinusoidal curves. We proposed a cylindrical line detection, based on the dual principle of the Hough transform. Moreover, the use of Plucker coordinates introduces some new characteristics in the calibration process. This kind of formalism allow a linearization of the cylindrical projection, which is non-linear in the usual way. Results obtained from this first step are used to evaluate one of the intrinsics, the other one being determined by a linear criterion minimization in the dual space, i.e. the sines magnitudes space.