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The degradation seriously affects the durability and cost of the proton exchange membrane fuel cell (PEMFC). This article presents a novel model-driven method based on the frequency-domain Kalman filter (FDKF) and voltage degradation model to predict the degradation of PEMFC in the frequency domain. The advantage of the proposed FDKF method is that it can process the data in groups; thus, the computation time can be greatly reduced with high accuracy. Two degradation experiments under constant and quasi-dynamic currents have been used to demonstrate its prognosis performances under different conditions and different training times. Compared with the traditional time-domain extended Kalman filter method and literature, it has been demonstrated that the proposed one has higher accuracy and requires much less calculation time.

This article proposes a novel disturbance-observer-based complementary sliding-mode (DO-CSM) speed controller for the field-oriented controlled permanent-magnet synchronous motor (FOC-PMSM) drive system. At first, the rotor speed dynamics of the PMSM drive system considering the lumped disturbance, which consists of external disturbances, parametric uncertainties, and unmodeled dynamics, is presented. Then, the classic CSM speed controller and a typical artificial neural network (ANN)-based CSM speed controller, i.e., the Elman NN (ENN)-based intelligent CSM (ENN-ICSM) speed controller for the FOC-PMSM drive system, are reviewed. Afterward, the design of the proposed DO-CSM speed controller, which combines the signum-function-based CSM controller with the super-twisting sliding-mode observer (STSMO), is presented. In such a speed controller, the rotor speed tracking control is accomplished by the adopted CSM controller, whereas the STSMO is employed to estimate and compensate for the lumped disturbance in the rotor speed dynamics. Finally, experimental comparisons among the proposed DO-CSM speed controller, the classic CSM speed controller, and three selected ENN-ICSM speed controllers are carried out. Experimental results verify the effectiveness and superiority of the proposed DO-CSM speed controller.

In this paper, a sliding mode observer (SMO) for the speed-sensorless direct torque vector control of linear induction motor(LIM) is proposed, considering the influence of dynamic end effects. The proposed SMO estimate the motor speed, the rotor flux, the angular position of the rotor flux, and the speed dependent parameter $w$ , only by using the measured stator voltages and stator currents. The nonlinear sliding mode technique guarantees very good performance for different situations of motor speed. The proposed SMO does not use complicated observer gains and robust to the parameter variation over the full-speed range. Moreover, the convergence of SMO is proven by using the Lyapunov theory. Furthermore, LIM Drive state observability is presented with detailed analysis. The performance of the proposed SMO is verified by hardware-in-the-loop test (HIL) system. Furthermore, a comparative study with and Luenberger observer(LO) and model reference adaptive system(MRAS) is presented.

In this article, a variable gain super-twisting algorithm based on a barrier function is proposed for a class of first order disturbed systems with uncertain control coefficient and whose disturbances derivatives are bounded but the upper bounds of those derivatives are unknown. The specific feature of this algorithm is that it can ensure the convergence of the output variable and maintain it in a predefined neighborhood of zero independent from the upper bound of the disturbances derivatives. Moreover, thanks to the structure of the barrier function, it forces the gain to decrease together with the output variable and the control signal follows the absolute value of the disturbances.

International audience; The aging prognosis model of Proton Exchange Membrane Fuel Cell (PEMFC) can predict the aging state of PEMFC to develop an effective prognostic maintenance plan. This paper proposes an aging prognosis model of PEMFC in different operating conditions based on the Backpropagation (BP) neural network and evolutionary algorithm. The influence of PEMFC current, hydrogen pressure, temperature, and relative humidity on the aging of PEMFC can be considered by the proposed method. Firstly, the aging prognosis model of PEMFC is built by the BP neural network. Then, the evolutionary algorithm including Mind Evolutionary Algorithm (MEA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) is used to optimize the parameters of the established aging prognosis model of PEMFC. Finally, the accuracy of the proposed aging prognosis model is validated by 3 PEMFC aging experiments in different operating conditions. The results show that MEA, GA, and PSO can greatly improve the accuracy of the aging prognosis model of PEMFC. The MEA improves the accuracy by 10 times, while the computing time increases by 0.085s. The proposed MEA-BP that has a very short computing time can be applied to online applications.

Within the framework of the classical problem of Lyapunov redesign, the barrier function-based adaptation control is presented. The proposed approach does not require the knowledge of an upper bound of the uncertainty. However, producing a continuous control signal adjusts the chattering problem and ensures that the solution will converge in finite time to a region with a priori prescribed ultimate bound.

With increasingly serious environmental issues such as global warming, fossil fuels are gradually being replaced by clean energy. Fuel cells (FC) combining with hydrogen as a sort of clean energy have already been employed in many applications. Due to the nonlinear current-voltage property of FC, a DC-DC boost converter and a suitable controller are necessary for the FC system. In this paper, an observer-based adaptive sliding mode control is designed by considering the actual vehicle applications with unknown load and variable FC voltage for interleaved boost converter (IBC). The designed controller shows strong robustness in output voltage because of the adaptive laws. The system stability is proofed by Lyapunov functions. Last, the simulations were carried out to further verify the effectiveness of the designed controller.

International audience; This paper aims to design a novel control strategy of a single converter hybrid power system including a Proton Exchange Membrane Fuel Cell (PEMFC) and super capacitors for electric vehicle applications. The control objective to be addressed in such systems is to smooth the current of PEMFC considering the transient power and sinusoidal disturbance from the load. Moreover, in real-time applications, it is required to ensure the operation by taking into account the component constraints and the degradation of PEMFC. To achieve these goals, a robust nonlinear cascaded voltage control loop is developed in this paper. For the inner voltage loop, a second order twisting controller with dynamic saturation scheme is adopted to ensure the convergence of the DC bus voltage to its reference value as well as to attenuate the oscillations on PEMFC current. For the outer voltage loop, a Proportional Integral controller (PI) with anti-windup scheme is utilized to control the super capacitors voltage at its desired value. Furthermore, in order to consider the degradation of PEMFC in the controlled system, an estimation of the degradation model parameters has been provided by Cubature Kalman Filter. Comparative Hardware-in-the-loop (HIL) tests between the proposed control strategy and the traditional two PI controllers strategy for the hybrid power system is performed. The results of HIL tests verified the effectiveness of the proposed nonlinear control strategy.

International audience; This paper proposes a novel Hermite neural network-based second-order sliding-mode (HNN-SOSM) control strategy for the synchronous reluctance motor (SynRM) drive system. The proposed HNN-SOSM control strategy is a nonlinear vector control strategy consisting of the speed control loop and the current control loop. The speed control loop adopts a composite speed controller, which is composed of three components: 1) a standard super-twisting algorithm-based SOSM (STA-SOSM) controller for achieving the rotor angular speed tracking control, 2) a HNN-based disturbance estimator (HNN-DE) for compensating the lumped disturbance, which is composed of external disturbances and parametric uncertainties, and 3) an error compensator for compensating the approximation error of the HNN-DE. The learning laws for the HNN-DE and the error compensator are derived by the Lyapunov synthesis approach. In the current control loop, considering the magnetic saturation effect, two composite current controllers, each of which comprises two standard STA-SOSM controllers, are designed to make direct and quadrature axes stator current components in the rotor reference frame track their references, respectively. Comparative hardware-in-the-loop (HIL) tests between the proposed HNN-SOSM control strategy and the conventional STA-SOSM control strategy for the SynRM drive system are performed. The results of the HIL tests validate the feasibility and the superiority of the proposed HNN-SOSM control strategy.

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International audience; With the drastic inclination towards reduction of atmospheric issues, fuel-cell vehicles are becoming the major alternative for internal combustion. Due to the characteristics of the fuel cell, multiple-input converter is more attractive in redundancy and safety. In this paper, a multi-input three-phase interleaved boost converter (IBC) is designed by analyzing every state of its work to obtain its averaged state-space equation. Two control methods based on PI and super-twisting (ST) are designed and applied to the converter. A fault-tolerant method is proposed for the IBC. The simulation results of fault-tolerant based on two control methods are compared. The results show that it has better performance in fluctuation of DC bus voltage and inductor current when using ST method.

International audience; In order to improve the durability and economy of a hybrid power system composed of a battery and supercapacitors, a control strategy that can reduce fluctuations of the battery current is regarded as a significant tool to deal with this issue. This paper puts forwards a disturbance rejection control strategy for a hybrid power system taking into account the degradation of the battery. First, the degradation estimation of the battery is done by the model-driven method based on the degradation model and Cubature Kalman Filter (CKF). Considering the transient and sinusoidal disturbance from the load in such a hybrid system, it is indispensable to smooth the behavior of the battery current in order to ensure the lifespan of the battery. Moreover, the constraints for the hybrid system should be considered for safety purposes. In order to deal with these demands, a cascaded voltage control loop based on a super twisting controller and proportional integral controller with an anti-windup scheme is designed for regulating the DC bus voltage in an inner voltage loop and supercapacitors’ voltage in an outer voltage loop, respectively. The specific feature of the proposed control method is that it operates like a low-pass filter so as to reduce the oscillations on the DC bus.

International audience; This study proposes a second-order sliding-mode observer (SOSMO) of the linear induction motor to deal with the sensorless problem, considering the influence of the end effects. The proposed SOSMO required only the measured voltages and currents to provide flux, motor speed and speed-depended parameter estimation simultaneously. The stability of the system and the error convergence of the flux and the speed have been proved. The performance of the proposed observer is verified by hardware-in-the-loop test system. Furthermore, a comparative study with model reference adaptive system and Luenberger observer is presented.

The specific feature of the wind energy conversion system (WECS) is that its model is a nonlinear system with uncertainties whose upper bound is also unknown. To control WECS, barrier function based-adaptive Super-Twisting controllers are proposed, ensuring the convergence of the extracted power to the maximum value obtained by maximum power point tracking (MPPT) controller, and the convergence of the reactive power to the reference reactive value with predefined errors independent of the upper bound of the uncertainties derivatives.

In this paper, a new barrier function-based adaptive strategy is proposed for first order sliding mode controller. This strategy is applied to a class of first order disturbed systems whose disturbance is bounded with unknown boundary. The proposed barrier strategy can ensure the convergence of the output variable and maintain it in a predefined neighborhood of zero independent of the upper bound of the disturbance, without overestimating the control gain.

An algorithm for adaptation of Levant's differentiator (LD) gains is designed for the case when the upper bound of second derivative of base signal exists but it is unknown. The barrier function is...

An algorithm for adaptation of first order sliding mode differentiator gains is proposed for the case when the upper bound of the second derivative exists but it is unknown. The proposed barrier adaptive algorithm can ensure the convergence of the differentiator to some vicinity of the first derivative. Then, a convergence detection criteria is used to estimate the size of this vicinity. The properties of the proposed algorithm in the presence of noise are discussed.

A fault-tolerant control scheme with a fixed control allocation strategy for linear time varying systems is proposed. The effects of the faults in the critical control channels are compensated theoretically exactly and the remaining effects are minimised by using an output integral sliding mode technique. Both aspects are achieved right after the initial time by using only output information. This approach allows dealing with total failures in some actuators under the assumption of redundancy. The effectiveness of the proposed scheme considering time varying faults is validated by computer simulations.

International audience; In this paper, we present a Lyapunov-based homogeneous controller for the stabilisation of a perturbed chain of integrators of arbitrary order r >= 1. The proposed controller is based on homogeneous controller for stabilisation of pure chain of integrators. The control of homogeneity degree is also introduced and various controllers are designed using this concept, namely a bounded-controller with minimum amplitude of discontinuous control and a controller with globally fixed-time convergence. The performance of the controller is validated through simulations.

International audience; This paper proposes a robust control strategy for a hybrid battery/super capacitors power system with a single converter. In such systems, it is required to smooth the battery current considering the load power transient and the current oscillations of the DC bus delivered by the load in the context of a hybrid electric vehicle. Furthermore, constraints of all the system components, i.e. maximum current of the battery and super capacitors, state of the charge of the super capacitors and battery temperature should be taken into account. To deal with these demands, a novel cascaded voltage control loop is proposed. For the outer voltage loop, an anti-windup proportional integral controller is used to regulate the super capacitor voltage at its nominal value. On the other hand, for the inner voltage loop, an anti-windup super twisting controller is proposed to ensure the convergence of the DC bus voltage to its reference value while attenuating the external perturbation. Indeed, the specific feature of such controller is that it works like a low-pass filter which leads to attenuate the current oscillations in the DC bus.

This paper proposes a finite-control-set model predictive current and capacitor voltage control strategy for the synchronous reluctance motor drive systems fed by the eight-switch three-phase inverter (ESTPI), which is a type of post-fault reconfigured three-level neutral-point-clamped inverter with open-circuit fault in a leg. The proposed control strategy uses the discrete-time models of the drive system to predict the behavior of the stator currents and the neutral point potential (NPP) error for zero and small voltage vectors provided by the ESTPI. The errors between stator currents and their references in the rotor reference frame as well as the NPP error are evaluated in a predefined cost function. The basic voltage vector, which minimizes this cost function, is selected. The proposed control strategy can achieve not only the reference stator current tracking but also the capacitor voltage offset suppression. Simulation results have shown the effectiveness of the proposed control scheme.

International audience; This paper proposes a rotor speed and position estimation scheme for the synchronous reluctance motor (SynRM) drive system based on its active flux model in the stator reference frame and the total least squares (TLS) EXIN neuron. Firstly, the active flux model of the SynRM in the stator reference frame is reconstructed to the overdetermined matrix equations. On the basis of that, the estimation of the rotor speed of the SynRM is transferred into solving a TLS problem. The TLS EXIN neuron, which is a recursive TLS algorithm, is used to solve this problem online to extract the rotor speed. The estimated rotor position is obtained from the estimated rotor speed based on the integrator. The feasibility and effectiveness of the proposed rotor speed estimation scheme have been verified by the simulation results.

International audience; A homogeneous continuous sliding mode control scheme based on finite time stability is developed in this paper for an upper limb exoskeleton robot dedicated for rehabilitation. Indeed this type of robot interacts directly with human limbs whose dynamics are unknown and different for users. Therefore, the main idea is to provide a robust motion control of the exoskeleton robot using a continuous higher order sliding mode controller despite parameters variations, uncertainties and external disturbances. The proposed controller combines the homogeneity concept and the super-twisting algorithm. Finite time stabilization is achieved using the first part of the controller while disturbance rejection is granted by the second part of the controller. Performance of the controller and its robustness are illustrated through simulations of trajectory tracking tests corresponding to passive rehabilitation exercises.

International audience; The degradation prediction is an effective tool for the long-lasting operation of the proton exchange membrane fuel cells (PEMFC). In this paper, a novel grey neural network model (GNNM) method combined with the particle swarm optimization (PSO) and the moving window method is presented to forecast the degradation of PEMFC under different operating conditions. The proposed method considers the influence of load current, inlet temperature, inlet hydrogen pressure, and inlet relative humidity. The degradation prediction model of PEMFC is established by a grey neural network. The initial weight and threshold of established GNNM are optimized by the PSO. The optimized PSO-GNNM is iteratively trained based on the moving window method through several newly measured data. The influence of different moving window sizes on the degradation prediction of the PEMFC under the static load current is investigated. Then, a comparison between the proposed method and the adaptive neuro-fuzzy inference system method is discussed. Moreover, the influence of the load current on the degradation prediction of PEMFCs in postal fuel cell electric vehicle operating under real conditions is analyzed. Finally, the proposed method is validated using 3 PEMFC aging experiments under different conditions. The results show that the proposed method can precisely forecast the degradation for PEMFC on different applications.

This paper presents a time-varying state observer based twisting control (TC) technique scheme for linear induction motor (LIM) considering dynamic end effects. With Ducan’s T-model, indirect field oriented control strategy is introduced and the state space equation of LIM is obtained in ( d , q ) rotary reference frame. On this basis, LIM’s model is extended to two subsystems: flux extended model and speed extended model. Twisting algorithm (TA) is applied into these two subsystems to achieve speed tracking and flux tracking with finite time convergence in the presence of disturbance and uncertainty. For the rotor flux estimation, a time-varying state observer is designed, and its stability and convergence have been proved with Lyapunov’s theory. Moreover, the value of estimated LIM speed derivative is obtained via second order sliding mode observer. Furthermore, a reduced order load torque observer is designed to estimate the external load torque. The feasibility and effectiveness of proposed method has been validated by Hardware-in-the-loop (HIL) test experiment.

In this paper, barrier function-based adaptive discontinuous and continuous integral sliding mode controls are proposed. The main advantage of the proposed algorithms is that they ensure that the solutions of the systems belong to a prescribed vicinity of the desired variables starting from the initial time moment despite of disturbance with unknown upper bound or disturbance with unknown upper bound of its derivative. The proposed algorithms do not require the knowledge of the upper bound of disturbance or its derivative, and, moreover, the control gains are not overestimated.

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International audience; This paper proposes an active-flux-based rotor position and speed estimation scheme for sensorless-vector- controlled synchronous reluctance motor (SynRM) drives, which is comprised of two main parts: 1) a super-twisting sliding mode observer (ST-SMO) for estimating the derivatives of active flux components; and 2) a rotor position and speed estimator based on the phase-locked loop (PLL). The ST-SMO is designed based on the active flux model of the SynRM in the stator reference frame. The estimated active flux components, which are obtained based on the ST-SMO and the integrator, are received as inputs of the PLL, and the estimated rotor position and speed are provided as outputs of the PLL. The feasibility and effectiveness of the proposed estimation scheme have been verified by the simulation results.

International audience; This paper proposes a nonlinear feedback super twisting field oriented control (NSTC) technique for linear induction motors (LIMs), taking into consideration the dynamic end effects. The state space equation of LIM is given based on Ducan's model. Based on the knowledge of indirect field oriented control (IFOC) theory, a nonlinear feedback super twisting controller is designed to achieve speed and flux tracking, regardless of external disturbances. Simulation results show that the the proposed NSTC scheme has good tracking performance and robustness property with external disturbances.

International audience; This paper presents a novel adaptive high order sliding mode method for linear induction motor (LIM) to reconstruct the states (currents and fluxes), speed and speed-depended parameter w, only using the measured stator voltages and stator currents. The adaptive law is designed to estimate speed and speed-depended parameter w, and their stability have been proved with Lyapunov's theory. Then the estimated values ∧v,∧w are rejected into higher order sliding mode observer (HOSMO). Super twisting algorithm (STA), with its obvious advantage, is applied into HOSMO. Finally, simulation results validated the performance of the proposed adaptive HOSMO scheme.

International audience; This paper presents an adaptive twisting controller scheme for linear induction motor (LIM) to deal with unknown boundary disturbance, considering the influence of the dynamic end effects. LIM's model can be divided into two subsystems: flux extended model and speed extended model. Two adaptive twisting algorithms are applied into these two subsystems to achieve speed tracking and flux tracking with finite time convergence, in the presence of the unknown bounded disturbance. Simulation results validated the performance of the proposed adaptive twisting controller scheme.

A novel adaptive twisting controller strategy is designed for the case of second order disturbed systems whose disturbance is bounded with unknown boundary. This strategy consists in using a Barrier Function to adapt the control gain. This barrier strategy can ensure the convergence of the Lyapunov function, and maintain it in some predefined neighborhood of zero. This barrier strategy also has two main advantages: it does not require any information about the upper bound of disturbance, and does not overestimate the control gain.

International audience; This paper presents an adaptive super twisting control scheme for linear induction motor (LIM), considering dynamic end effects. The designed control strategy is based on cascaded adaptive super twisting controllers (ASTCs) which regulate the stator currents in response to LIM speed error. Based on indirect rotor field oriented control (IRFOC) strategy, the adaptive time varying switching gains are designed and adopted in external loop and internal loop control scheme. The adaptive super twisting algorithm can eliminate the influence of external disturbances and uncertainties. The designed controller shows better results than fixed parameter super twisting controller (STC) with better transient performance and less chattering. Simulation results prove the effectiveness of the proposed control scheme.

Optimized robust control for Polymer Electrolyte Membrane Fuel Cell (PEMFC) air-feed systems is an important challenge in improving the net fuel cell power output in automotive applications. This paper focuses on the practical implementation and performance comparison of robust and adaptive Second Order Sliding Mode Controllers (SOSMC) for this application. Both controllers aim to minimize the power consumption of the air-feed system by operating it to maintain the optimal oxygen excess ratio in the fuel cell. The controllers have been tested using a Hardware-In-Loop test bench based on a commercial twin screw compressor and 90 Cell, 33 kW fuel cell emulator. The experimental results demonstrate the effectiveness of both controllers and highlight that the adaptive controller is more power-efficient as the adaptive gains further reduce the internal power consumption of the air-feed system.

This paper presents an observer-based fault reconstruction method for PEM fuel cells. This method extends the results of a class of nonlinear uncertain systems with Lipschitz nonlinearities. An adaptive-gain second-order sliding mode (SOSM) observer is developed for observing the system states, where the adaptive law estimates the uncertain parameters. The inherent equivalent output error injection feature of SOSM algorithm is then used to reconstruct the fault signal. The performance of the proposed observer is validated through a hardware-in-loop emulator. The experimental results illustrate the feasibility and effectiveness of the proposed approach for application to fuel cell air-feed systems.

Pneumatic artificial muscles are very powerful pneumatic actuators that work very similarly to the human muscle. They are broadly used in the development of robotic manipulators for industry or in the medical domain mainly for their low cost, intrinsic safety and high compliance. However, devices driven by these actuators are characterized by complex nonlinear dynamics and time varying properties which impose a very challenging control issue. This can be handled using sliding mode control. Well known for its robustness and invariance, this control technique is very suitable for this type of systems. The only drawback is chattering produced by high frequency commutation due to discontinuity and overestimation of the controller gains. In this paper, we present an adaptive discrete sliding mode controller based on reaching law. Gains of the proposed controller are dynamically adjusted to the sliding motion to reduce chattering and ensure convergence in finite time with good precision. A comparison with a fixed gain discrete sliding mode controller is presented for position regulation and trajectory tracking of a robotic manipulator driven by pneumatic artificial muscles.

This paper proposes a super twisting sliding mode control technique for linear induction motors (LIMs) with unknown load torque, taking into consideration the dynamic end effects. First, LIM's dynamic end effects are presented by Ducan's T-model, then following this model is controlled by a designed super twisting controller (STC) for flux tracking and speed tracking purpose. Simultaneously, an open loop flux observer and a reduced order load torque observer are designed based on Lyapunov's analysis. Finally, simulation results show that the designed observer-based super twisting controller has great tracking performance and the system is robust with disturbances and uncertainties, and flux observer and reduced torque observer show good estimate performance with nominal system and input-to-state stability (ISS) property with uncertainty system.

International audience; In this paper, we present a generalization of the super-twisting algorithm for perturbed chains of integrators of arbitrary order. This higher order super-twisting (HOST) controller is homogeneous with respect to a family of dilations and is continuous. It is built as a dynamic controller (with respect to the state variable of the chain of integrators) and the convergence analysis is performed by the use of a homogeneous strict Lyapunov function which is explicitly constructed. The effectiveness of the controller is finally illustrated with simulations for a chain of integrators of order four, first pure then perturbed, where we compare the performances of two HOST controllers.

In this paper, an adaptive algebraic observer is proposed for a Polymer Electrolyte Membrane Fuel Cell (PEMFC) air-feed system, based on Higher Order Sliding Mode (HOSM) differentiators. The goal is to estimate oxygen and nitrogen partial pressures in the fuel cell cathode side, using measurements of supply manifold pressure and compressor mass flow rate. As the proposed technique requires the time derivatives of the states, Lyapunov-based adaptive HOSM differentiators are synthesized and implemented for estimating these derivatives without a-priori knowledge of the upper bounds of their higher order time derivatives. The performance of the proposed method is validated through experiments on a Hardware-In-Loop (HIL) test bench. These results illustrate the feasibility and effectiveness of the proposed approach.

In this paper, an adaptive-gain, Second Order Sliding Mode (SOSM) observer for multi-cell converters is designed by considering it as a type of hybrid system. The objective is to reduce the number of voltage sensors by estimating the capacitor voltages from measurement of the load current. The proposed observer is proven to be robust in the presence of perturbations with unknown boundaries. As the states of the system are only partially observable, a recent concept known as Z(TN)-observability is used to address the switching behavior. Multi-rate simulation results demonstrate the effectiveness and the robustness of the proposed observer with respect to output measurement noise and system uncertainty (load variations).

This paper provides a reliable tool for simulating the effects of exhaust gas flow through the variable turbine geometry section of a variable geometry turbocharger (VGT), on flow control mechanism. The main objective is to estimate the resistive aerodynamic force exerted by the flow upon the variable geometry vanes and the controlling actuator, in order to improve the control of vane angles. To achieve this, a 1D model of the exhaust flow is developed using Navier–Stokes equations. As the flow characteristics depend upon the volute geometry, impeller blade force and the existing viscous friction, the related source terms (losses) are also included in the model. In order to guarantee stability, an implicit numerical solver has been developed for the resolution of the Navier–Stokes problem. The resulting simulation tool has been validated through comparison with experimentally obtained values of turbine inlet pressure and the aerodynamic force as measured at the actuator shaft. The simulator shows good compliance with experimental results.

Summary In this paper, we have studied the control problem of target point-based path following for car-type vehicles. This special path-following task arises from the needs of vision-based guidance systems, where a given target point located ahead of the vehicle, in the visual range of the camera, must follow a specified path. A solution to this problem is developed through a nonlinear transformation of the path-following problem into a reference trajectory tracking problem, by modeling the target point as a virtual vehicle. The use of target point complicates the control problem, as the development produces a first-order nonlinear nonglobally Lipschitz differential equation with finite escape time. This problem is solved by using small control signals. Bounded feedback laws are designed to control the real vehicle's angular acceleration and the virtual vehicle's velocity, to achieve stability. The resulting controller is globally asymptotically stable with respect to the origin, the proof of which is derived from Lyapunov-based arguments and a bootstrap argument. It is also shown that the use of exponentially convergent observers/differentiators does not affect the stability of the closed-loop system. The effectiveness of this controller has been illustrated through simulations. Copyright © 2014 John Wiley & Sons, Ltd.

Summary In this paper, we present an output feedback backstepping controller for mechatronic actuators with dynamic adaptive parameters for friction and load compensation. The targeted application is angular position control of automotive mechatronic valves, which possess nonlinear dynamics due to friction. The proposed controller requires only position measurement. The velocity, current, and friction dynamics are obtained by estimation and observation. The adaptive control law compensates the variations in friction behavior and load torque variation, which are common in real life applications. Lyapunov analysis has been used to show the asymptotic convergence of the closed-loop system to zero. Simulation and laboratory experimental results illustrate the effectiveness and robustness of the controller. Further experiments on an engine test bench demonstrate the applicability of this controller in commercial engines, as well as its effectiveness as compared with conventional PI controllers.Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, we design, analyze, and experimentally validate an observer-based backstepping controller for electropneumatic actuators. These actuators are commonly used in diesel engines for variable geometry turbochargers (VGT) control. They are preferred over other actuation techniques due to better force/weight ratio; however, their drawbacks, such as nonlinear air mass flow, friction, and aerodynamic forces make their control as a challenging problem. The aim of this paper is to achieve precise control of the actuator by compensating friction and aerodynamic VGT forces. A Lyapunov-based output feedback controller is developed using backstepping technique. As the actuator position is the only measured state, pressure and friction states are obtained from sliding mode-based observers. The exponential convergence of the controller-observer closed-loop system is proved using Lyapunov analysis. Experimental results are presented, which demonstrate the effectiveness of the proposed controller.

In this paper, a full-bridge boost power converter topology is studied for power factor control, using output higher order sliding mode control. The AC/DC converters are used for charging the battery and super-capacitor in hybrid electric vehicles from the utility. The proposed control forces the input currents to track the desired values, which can control the output voltage while keeping the power factor close to one. Super-twisting sliding mode observer is employed to estimate the input currents and load resistance only from the measurement of output voltage. Lyapunov analysis shows the asymptotic convergence of the closed-loop system to zero. Multi-rate simulation illustrates the effectiveness and robustness of the proposed controller in the presence of measurement noise.

This paper presents a detailed physical model of an electro-pneumatic system, used to control Variable Geometry Turbochargers (VGT). The VGT actuator system consists of two parts, a diaphragm based pneumatic actuator and a solenoid based Electro-pneumatic Pressure Converter (EPC). The proposed model copes with the pressure dynamics inside the pneumatic actuator, with special focus on the EPC. The dynamics of both parts have been modeled separately and combined into one model by parameterizing the effective flow area and the air mass flow through the pneumatic actuator. The variations in volume, temperature and air mass flow rate have been taken into account. The model so obtained serves mainly for studying the effect of actuator dynamics on the global engine system. For control purposes, the detailed model is simplified to reduce the calculation load. Both models are validated using experimental data obtained from an engine test bench.

Polymer Electrolyte Membrane Fuel Cells (PEMFC) are extremely sensitive to load variations. A rapid load variation can damage the system in many ways. For this reason, a Load Governor (LG) based on constrained Extremum Seeking (ES) approach has been proposed in this paper. The LG controller ensures that the physical constraints of the system are not violated and the ES controller varies the LG bandwidth parameter to optimize the net power output. The proposed controller has been tested on a Hardware-In-Loop (HIL) emulation test bench, based on a commercial centrifugal compressor and a real time PEMFC emulator. Experimental results show a good performance of the proposed scheme during load variations.

Pressure difference inside the Polymer Electrolyte Membrane Fuel Cells (PEMFC) arises due to load variations, during which the pressure difference between anode and cathode rises. Practically, this problem can be avoided by equalizing anode and cathode pressures, to protect the fuel cell from permanent damage. This paper focuses on pressure regulation in the anode and cathode sides of the PEMFC. The control objective is achieved using second order sliding mode multi-input multi-output (MIMO) controller based on “Twisting algorithm”. Parametric uncertainty is formally presented and included in a nonlinear dynamic fuel cell model. The resultant nonlinear controller is robust and is proved to guarantee performance around any equilibrium point and under parametric uncertainty. Simulation results show that the proposed controller has a good transient response under load variations.

Numerous advanced control techniques for actuator control of an engine’s air path have been developed in recent years. Among these approaches, the performance of sliding mode controllers stands out due to their robustness against changes in the physical conditions around the engine. This paper presents the design and testing of three high-order sliding mode controllers and a comparison of their performance in controlling a mechatronic engine air path valve. The most effective strategies are further tested for their robustness against variations in temperature and load conditions. The experimental results show the effectiveness and robustness of the controllers. Comparative results are presented that allow the performance of the considered algorithms to be compared both with respect to each other and with respect to sliding surfaces.