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International audience; This article deals with robust fixed-time stability and stabilization. First, new global robust fixed-time stability results are proposed for scalar systems by using constant and variable exponent coefficients. Then, they are applied to global robust fixed-time stabilization of a class of uncertain nonlinear second order systems by using sliding mode control. All the results are illustrated in simulation.

In this brief, a control technique is proposed to achieve finite-time trajectory tracking of the position of a perturbed electropneumatic actuator. This controller guarantees the convergence at exactly a predefined convergence time $t_{F}$ . It is based on the integral sliding-mode concept, and is composed of two terms: a first one named nominal control which is designed to obtain desired performances (convergence time) for the disturbance free system, and a second robust control , based on super-twisting algorithm for the disturbance compensation. This brief presents its practical implementation to an electropneumatic actuator, in single-output (SISO) and multi-input multi-output (MIMO) contexts. The robustness of the control law is discussed with respect to external disturbances.

International audience; This paper provides a practical control solution to remote control systems with unknown time-varying delays. An external signal which can be considered as a specific communication loop is added to estimate the unknown round-trip delay in finite time. Then the system is stabilized with the practical delay estimation technique and a predictor-based controller. The main results of this paper also provide an alternative way to design predictor-based controller for systems with known input and output time-varying delays. The theoretical results of this paper are illustrated by simulation results.

International audience; The objective of this paper is to build feedback control solutions for LTI systems with unknown constant input-delay. The control scheme includes a time-delay estimation algorithm and a predictor-based controller. The Lyapunov-Krasovskii theorem provides the global exponential stability of the closed-loop system. Some examples illustrate the theoretical results and the performances of the proposed method.

A new control scheme based on adaptive super-twisting algorithm is proposed for a floating wind turbine equipped by a permanent magnet synchronous generator. The adaptive control method is especially efficient for systems with uncertainties and external perturbations and, therefore, is well adapted to wind turbines systems. Such controller can be implemented with very limited knowledge of system model (only the relative degree is required) that greatly reduces the controller gains tuning effort. Simulations are made on FAST software and compared with a standard gain-scheduled PI controller.

This paper addresses the possibility of using robust control theory for preventing earthquakes through fluid injections in the earth's crust. The designed robust controllers drive aseismically a fault system to a new equilibrium point of lower energy by tracking a slow reference signal. The control design is based on a reduced-order nonlinear model able to reproduce earthquake-like instabilities. Uncertainties related to the frictional and mechanical properties of the underlying physical process and external perturbations are considered. Two types of controllers are derived. The first one is based on sliding-mode theory and leads to local finite-time convergence of the tracking error and rejection of Lipschitz w.r.t. time perturbations. The second controller is based on LQR control and presents global exponential stability of the tracking error and rejection of Lipschitz w.r.t. states perturbations. Both controllers generate a continuous control signal, attenuating the chattering effect in the case of the sliding-mode algorithms. The developed controllers are tested extensively and compared on the basis of numerical simulations and experiments in the laboratory. The present work opens new perspectives for the application of robust nonlinear control theory to complex geosystems, earthquakes and sustainable energy production.

In this paper, a novel adaptive super-twisting controller is used for a floating wind turbine system working in region III. The tuning of the controller with time varying gains does not need any information on the bounds of the system uncertainties. As it is known, the floating wind turbine is an extremely nonlinear system and a simple model to reproduce all its dynamics does not exist. For these reasons, the proposed new controller is well adapted to this kind of system. The control objectives are power regulation, platform pitch motion reduction and reduction of blades fatigue load. The proposed controller is tested on FAST simulator, and the obtained results show its high level capability compared to other control strategies.

The aim of this article is to study the properties of the sign gradient descent algorithms involving the sign of the gradient instead of the gradient itself and first introduced in the RPROP algorithm. This article provides two results of convergence for local optimization , a first one for nominal systems without uncertainty and a second one for systems with uncertainties. New sign gradient descent algorithms including the dichotomy algorithm DICHO are applied on several examples to show their effectiveness in terms of speed of convergence. As a novelty, the sign gradient descent algorithms can allow to converge in practice towards other minima than the closest minimum of the initial condition making these algorithms suitable for global optimization as a new metaheuristic method.

This article proposes a review of the modeling approaches for floating offshore wind turbines (FOWTs) for nonlinear control design. The aerodynamic, hydrodynamic and mooring line dynamic modules for the FOWT have been reviewed to provide an overview of several modeling approaches with their respective features. Next, three control-oriented models from the literature are revisited by presenting their methodological approaches to modeling and identification. These three models cover the three most popular types of FOWTs. Then, the performances of these models are validated with the open fatigue, aerodynamics, structures, and turbulence (OpenFAST) code, and their performances are evaluated according to several criteria. Finally, one of the three models is used to illustrate a nonlinear second-order sliding mode control based on the twisting algorithm to optimize the performance of the FOWT in terms of energy extraction and reduction in the platform pitch oscillation.

This work addresses the problem of developing control algorithms for the control of the aerodynamic lift of wind turbine blades using air injection, taking into account disturbances caused by turbulent perturbations. For this, a test bench is used where the lift of a 2D blade section in a wind tunnel can be controlled by a set of micro-jets close to the trailing edge. Through a continuous, local identification of the lift variations a model-free control that does not need any prior knowledge of the system is proposed. It allows the control of the flow of the micro-jets and stabilizes the lift around a tracking reference. The ability of the proposed control algorithm to track the lift reference when subjected to external perturbations, i.e., gusts, is discussed. In particular, this work demonstrates that the lift can be set to particular values using the proposed control strategy, and can be re-stabilized to pre-gust lift conditions. Experimental results illustrate globally the feasibility of such a control.

In this paper, novel definitions of Phase and Gain Margins are introduced for a class of Discrete Nonlinear Time – Invariant Lur’e Systems. Also, Describing Function – Harmonic Balance technique and Tsypkin Criterion based algorithms are proposed for calculating practical Phase and Gain margins in such systems. The efficacy of the proposed algorithms is illustrated in a tutorial example.

The concept of healthy twin wind turbines is recently studied in the literature. Control in the dq-frame, based on the symmetric of the healthy system, has been proposed. Nevertheless the robustness of such control with respect to asymmetric faults has not been studied. In this paper, a new asymmetric model is proposed in abc-frame, taking into consideration an electrical fault. The healthy control is tested in the framework of the faulty model, and simulations show that some robustifications are necessary.

In this paper, a novel concept of Gain Margin is defined and studied for a class of Nonlinear Systems specifically the Lur'e type. The corresponding algorithms for computing practical Gain Margins in such systems, based on Lyapunov's Second Method and Linear Matrix Inequalities, are introduced. The efficacy of the proposed algorithms is illustrated in tutorial examples.

In this paper, adaptive high order sliding mode (HOSM) based control schemes are proposed for a floating offshore wind turbine (FOWT). These adaptive control methods are especially efficient for systems with uncertainties and external perturbations that is well adapted to wind turbines systems. The two HOSM based controllers are applied on FOWT, their main features being that they require a very reduced knowledge of the system (only the relative degree is supposed known) and a reduced tuning effort compared to standard controllers for FOWT as gain scheduled PI (GSPI) controller. Simulation results show high performances of the proposed controllers for rotor speed regulation and reduction of platform pitch motion.

International audience; The stability of a prediction-based controller is studied in presence of time-varying delays both in the input and in the output. Thanks to the reduction method and a Lyapunov-Krasovskii analysis, stability conditions are derived. A comparison is also made between the single input delay and single output delay cases. It is shown that this method can be applied to stabilize output delay systems without restriction on the delay rate. The results are illustrated numerically on a double integrator.

The estimation of the state of lateral dynamics of a vehicle is usually performed using information gathered by several sensors, such as cameras, radars, odometers, and accelerometers. However, some quantities and their variations cannot be measured directly in all driving situations whereas they are required for vehicle control. Among these unmeasured quantities, one can find road curvature. This paper proposes to apply nonlinear observers to provide such information, in addition to other quantities related to the vehicle state, in the context of Traffic Jump Pilot. The first contribution of this paper is to formulate the nonlinear dynamics model and then to design two nonlinear observers based on High-Gain and Sliding Mode techniques. Furthermore, in order to ensure their efficient applications in a real situation, an experimental methodology is developed in order to optimize their performances by finding an optimal set of gain values. In that respect, a large database of real driving conditions and different road curvature scenarios is recorded for the performances evaluation and then a recent multi-objective optimization algorithm is used to find the optimal tuning parameters of the observers. The effectiveness of the proposed methodology is illustrated through an application to a driving test, which is not in the database. The use of this optimization tool is a novelty in the context of nonlinear observation and control, which allows getting optimized observers that can be efficiently applied to experimental data.

A robust integral backstepping controller is designed in this paper in order to control a new structure of twin wind turbines. The novelty of this concept is the free motion of the arms carrying the two turbines. In order to initiate a yaw rotation, the pitch blades angles are modified to create a difference between the drag forces of the two rotors. The controller aims at maximizing the electrical power by an optimal orientation of the structure. A strategy based on backstepping approach is proposed.

In this paper, a continuous control strategy for robust stabilization of a class of uncertain multivariable linear systems with delays in both the state and control variables is proposed. A predictor is designed to compensate the delay effect in control input, and then an integral sliding mode control technique along with super-twisting algorithm is applied to compensate partially the effect of the perturbation term. Finally, a nominal delay-free part of the control input is designed to stabilize the sliding mode dynamics. The method is extended to the class of systems modeled in Regular form, it is proposed a transformation for the systems with delay in state then results in a system delay-free in state. Conditions for the stability of the closed-loop uncertain system are derived. Simulation results are presented and compared against previous works.

The stability of a prediction-based controller for linear time-invariant (LTI) systems is studied in the presence of time-varying input and output delays. The uncertain delay case is treated as well as the partial state knowledge case. The reduction method is used in order to prove the convergence of the closed-loop system including the state observer, the predictor and the plant. Explicit conditions that guarantee the closed-loop stability are given, thanks to a Lyapunov-Razumikhin analysis. Simulations illustrate the theoretical results.

It is well known that higher order sliding mode controllers (HOSMCs) are robust against perturbations but consume large amounts of energy which is mainly due to the chaterring of the control input. This paper proposes a controller allowing to keep the robustness while reducing the energy consumption. This is made by introducing a time-varying parameter $\alpha$ on the exponent term of the controller. The finite time convergence of the closed-loop system to a vicinity of the origin is established. Finally, simulations that validate the effectiveness of the proposed controller are presented. An additional result concerning the use of a different law for varying $\alpha$ is introduced.

A new control strategy based on adaptive second order sliding mode approach is applied to a floating wind turbine system in the above rated region. This adaptive controller is well adapted to a highly nonlinear system as floating wind turbine, and can be easily implemented with very reduced knowledge of modeling. The proposed controller partially based on multi-blade coordinates transformation combines collective and individual collective blade pitch control, for power regulation, platform pitch motion reduction and reduction of blades fatigue load. The proposed controller is implemented on FAST simulator and shows high level of performances.

Summary In this paper, a new second-order sliding mode output feedback control law is proposed. It amounts to approach the dynamic performance of the twisting algorithm, but the main advantage of this new control method is that it requires only the information of the sliding variable, and not its derivative. A gain adaptation law is also developed for this new control law. Then this control strategy is applied to the position control of an electropneumatic system, and its performance is compared with other two very recent adaptive second-order sliding mode control laws. Copyright © 2016 John Wiley & Sons, Ltd.

A novel control scheme for the regulation and trajectory tracking in spite of external perturbations of the three degrees of freedom (3-DOF) helicopter is presented. The scheme allows reduced control effort, vibration reduction, and accurate tracking. The proposed approach combines a continuous differentiator with an adaptive super twisting controller. The differentiator provides state estimation, whereas the adaptive super twisting algorithm is chosen such that the gains of the controller are adapted to reduce the control effort and do not require the knowledge of the bounds of the uncertainties and perturbations. Furthermore, finite time convergence of the continuous differentiator to a neighborhood of the desired trajectory, allows to design independently controller and the differentiator, satisfying the principle of separation. Finally, the proposed control scheme is validated by experimental tests under external disturbances.

This editorial article gives a short introduction to Special Issue of International Journal of Control on Adaptive Sliding Mode Control and Observation.

Pneumatic actuators are quite difficult to control in an accurate way. Indeed their dynamics are generally described by an uncertain nonlinear system. The uncertainties are caused by friction, (external) perturbations and parametric uncertainties due to a very tedious identification process. This paper deals with the position control problem of an electropneumatic actuator using sliding mode control.

This paper proposes an ℒ1 fuzzy adaptive controller for a class of uncertain continuous-time single-input single-output nonaffine nonlinear systems. The structure of this controller is derived based on ℒ1 adaptive control design methodology and integrates a fuzzy system. The latter is used to approximate as best as possible a function of an unknown ideal implicit controller, which provides good results and improves the performance significantly. The ℒ1 fuzzy adaptive controller consists of a predictor, a control law and its adaptive laws. The major advantage of the proposed control scheme is its ability to guarantee uniformly bounded transient and tracking performance for the controlled system. These performance bounds can be rendered arbitrarily small by the systematic choice of design parameters. The effectiveness and feasibility of the proposed ℒ1 fuzzy adaptive controller are examined experimentally in the position control of a pneumatic actuator system.

International audience; The subject of this paper is about the use of a suspended Cable-Driven Parallel Robot (CDPR) for pick-and-place operations of heavy and heterogeneous objects. The knowledge of the payload mass and its center of mass in real-time is an asset for robust control of the device, which is required to ensure a good stability, especially when the objects have different shapes, sizes and masses. Accordingly, this paper aims at experimentally evaluating the effects of (i) the pulleys modeling and (ii) the use of force sensors for the payload estimation. It turns out that the consideration of the pulleys into the geometric model of the robot improves the mass and center of mass estimations of the payload. A comparison is made between the estimation of cable tensions from force sensors and from motor currents. Finally, a torque controller with a feedforward term for real-time mass compensation is proposed and implemented on a CDPR prototype.

In the present paper, a robust predictor-based sliding mode control for perturbed time-varying delay systems is proposed. A predictor is designed to compensate the time-varying delay effect in control input, and then an integral sliding mode control technique along with super-twisting algorithm is applied to compensate partially the effect of the perturbation term. Finally, a nominal delay-free part of the control input is designed to stabilize the sliding mode dynamics. Conditions for the stability of the closed-loop perturbed system are derived. Simulation result is presented.

This paper proposes a new control scheme for a non-standard wind turbines system, that comprises two identical wind turbines and has no yaw actuator to ensure the alignment face to the wind. Furthermore, the controller based on super-twisting algorithm is a sensorless one, in the sense that it does not require wind speed measurement. Such feature is attained thanks to the use of a very recent differentiation approach. The performance of the proposed controller is assessed by simulation.

The main contribution of the paper is to propose a scheme of attitude controller for a class of unmanned aerial vehicles based on an adaptive version of the super-twisting algorithm. This controller is based on a very recent second-order sliding mode controller, which is robust in spite of uncertainties and perturbations, ensures finite time convergence, reduces the chattering, increases the accuracy, and does not require time derivative of the sliding variable. A very important feature of the controller is its adaptive gain, which allows to design the controller without knowing bounds of the uncertainties and perturbations. This controller is validated by experimental results. Comparisons versus PID-based controller are made in order to evaluate the robustness of the closed-loop system when similar perturbations are acting. Copyright © 2015 John Wiley & Sons, Ltd.

International audience; This brief presents a set of experimental results concerning the sliding mode control of an electropneumatic system. Two discrete-time control strategies are considered: an explicit and an implicit (that is very easy to implement with a projection on the interval [−1, 1]) Euler discretizations. While the explicit implementation is known to generate numerical chattering , the implicit one is expected to significantly reduce chattering while keeping the accuracy. The experimental results reported in this brief remarkably confirm that the implicit discrete-time sliding mode supersedes the explicit ones, with several important features: chattering in the control input is almost eliminated (while the explicit and saturated controllers behave like high-frequency bang–bang inputs), the input magnitude depends only on the perturbation size and is independent of the controller gain and sampling time.

International audience; A new predictive scheme is proposed for the control of Linear Time Invariant (LTI) systems with a constant and known delay in the input and unknown disturbances. It has been achieved to include disturbances effect in the prediction even though there are completely unknown. The Artstein reduction is thenrevisited thanks to the computation of this new prediction. An extensive comparison with the standard scheme is presented throughout the article. It is proved that the new scheme leads to feedback controllers that are able to reject perfectly constant disturbances. For time-varying ones, a better attenuation is achieved for a wide range of perturbations and for both linear and nonlinear controllers. A criterion is given to characterize this class of perturbations. Finally, some simulations illustrate the results.

This paper deals with the speed control of a DC motor with known input delay and unknown disturbances. A recent predictive technique is used in order to design two controllers that will be able to satisfactorily reject disturbances in spite of the time delay. A comparison between the Artstein reduction method and this new one is performed throughout the article. The control laws are validated first by simulation and then by a practical implementation. The paper presents the very first application of this new predictive method.

In this paper, a new scheme for pose estimation in vision system is presented and evaluated on a serial robot. A nonlinear observer is proposed for online estimation of the deviations of the embedded camera w.r.t the ground reference without knowledge of the geometric features of the scene. This observer is based on high-gain strategy. The presented results consist in using feature and observation scheme to guarantee the observability and efficiency of the estimation. Experimentation results, which are the first of such observers, are presented in a controlled environment of a KUKA robot.