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This paper proposes an adaptive output feedback full state constrain (FSC) controller based on the adaptive neural disturbance observer (ANDO) for a nonlinear electro-hydraulic system (NEHS) with unmodeled dynamics. The Barrier Lyapunov Functions (BLFs) are utilized to ensure that all states of the system are specified within the constraints, and the approximation ability of radial basis function neural networks (RBFNNs) is used to cope with the unknown nonlinear functions. An adaptive neural compensation disturbance observer is elaborated to estimate the compound disturbance and oil leakage fault, effectively addressing these negative effects. Subsequently, observer-based output feedback command filter scheme is developed to diminish the explosion of complexity in the taking derivative procedure and obtain high precise tracking performance. The convergence of tracking errors into a small region around the equilibrium is demonstrated by the Lyapunov stability theory. Ultimately, simulation, experiment, and comparative studies are provided to further validate the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

This article proposes a novel real-time optimization-based energy management strategy (EMS) for proton membrane exchange fuel cell (PEMFC)-battery-supercapacitors-driven hybridized-electric tramways (HETs). The proposed algorithm is derived based on an enhanced extremum seeking (ES) algorithm, with a new equivalent state-of-charge (SOC) and a new adaptive co-state introduced. Thereby, optimized reference power for each power source can be distributed appropriately when using three components. The workability and prominent of the proposed technique are demonstrated through comparative simulations with fuzzy-rule-based EMS (FEMS) and equivalent consumption minimization strategy (ECMS) in two case studies: with and without considering the supercapacitors, as an important factor in the EMS design to stabilize the SOC of energy storage devices (ESDs). Briefly, under the proposed ES-based method, the PEMFC power can be regulated such that high-efficiency can be performed, approximately by 46.7%. Subsequently, the hydrogen consumption is reduced about 31.2% compared to a comparative fuzzy-based EMS. Besides, the supplements' SOCs at the end of a driving cycle are also regulated to be equal to the initial ones. [ABSTRACT FROM AUTHOR]

• This work first time deploys the radial basis function neural network (RBFNN)-based control with norm estimation in a new way to facilitate the control development. • Inequality constraint of using norm estimation is relaxed but still retaining the same properties of the original system. • A nonlinear disturbance state observer (NDSO)-based RBFNN is employed to not only estimate unmeasured states but also lumped disturbances and uncertainties. • An observer-based NN finite time control is established to achieve the system output tracking regulation. Due to the difficulty encountered in dealing with unstructured system dynamics with unmeasured system state variables, this paper presents a novel observer-based neural network finite-time output control strategy for general high-order nonlinear systems (HNSs). The suggested technique is performed based on the backstepping-like control (BSC) scheme with a hybrid nonlinear disturbance-state observer and norm estimation-based radial basis function neural network (RBFNN). This helps not only reduce the number of estimated parameters but also relax the restriction of using inequality when exploiting the norm estimation concept in a conventional way; thus, retaining the same properties of the original system. Therefore, an observer-based finite-time output feedback control is established to deal with the unstructured dynamical behaviors and satisfying the output tracking regulation with the semi-global practically finite-time stability (SGPFS) guaranteed for the closed-loop system. The effectiveness and workability of the proposed algorithm is verified by a numerical simulation on a specific practical application. [ABSTRACT FROM AUTHOR]

Recently, floating offshore wind turbines (FOWTs) have attracted increasing attention owing to their capabilities, and such devices are being considered the next-generation technology to develop green energy. However, despite their prominent benefits, FOWTs are vulnerable to damage and degradation due to frequent operation under harsh environments involving highly variable wind flows and incident waves. In such scenarios, the system dynamics tend to generate additional motions, workloads, and undesired fluctuations. Owing to these aspects, the optimization of control strategies is challenging and thus must be extensively investigated to ensure long-term survivability. Many approaches involving both simulations and experiments on small-scaled test rigs have been reported. In this regard, this paper highlights the encountered issues and reviews the state-of-the-art control technologies for FOWTs, with the classifications based on the enhancements in the typical methods and floater architectures under region 3 (high wind speed) conditions. • Outlined potentials and challenges associated with floating offshore wind turbines. • Classification based on enhancement in key methodologies and properties of floaters. • Control strategies arranged and compared from simple to modern and advanced control algorithms. • Presentation of enumerated tables with evaluated criteria for suitable decisions of methods. • Comparisons about influences of controller parameters on the system performance. [ABSTRACT FROM AUTHOR]

By replacing conventional supplies such as fossil fuels or internal combustion engines (ICEs), this paper presents a new configuration of hybrid power sources (HPS) based on the integration of a proton-exchange membrane fuel cell (PEMFC) with batteries (BATs) and supercapacitors (SCs) for hydraulic excavators (HEs). In contrast to conventional architectures, the PEMFC in this study functions as the main power supply, whereas the integrated BAT–SC is considered as an auxiliary buffer. Regarding shortcomings existing in the previous approaches, an innovative energy management strategy (EMS) was designed using a new mapping fuzzy logic control (MFLC) for appropriate power distribution. Comparisons between the proposed strategy with available approaches are conducted to satisfy several driving cycles with different load demands and verify the strategy's effectiveness. Based on the simulation results, the efficiency of the PEMFC when using the MFLS algorithm increased up to 47% in comparison with the conventional proposed EMS and other approaches. With the proposed strategy, the HPS can be guaranteed to not only sufficiently support power to the system even when the endurance process or high peak power is required, but also extend the lifespan of the devices and achieves high efficiency. [ABSTRACT FROM AUTHOR]

Construction machines are heavy-duty equipment and a major contributor to the environmental pollution. By using only electric motors instead of an internal combustion engine, the problems of low engine efficiency and air pollution can be solved. This paper proposed a novel energy management strategy for a PEM fuel cell excavator with a supercapacitor/battery hybrid power source. The fuel cell is the main power supply for most of the excavator workload while the battery/supercapacitor is the energy storage device, which supplies additional required power and recovers energy. The whole system model was built in a co-simulation environment, which is a combination of MATLAB/Simulink and AMESim software, where the fuel cell, battery, supercapacitor model, and the energy management algorithm were developed in a Simulink environment while the excavator model was designed in an AMESim environment. In this work, the energy management strategy was designed to concurrently account for power supply performance from the hybrid power sources as well as from fuel cells, and battery lifespan. The control design was proposed to distribute the power demand optimally from the excavator to the hybrid power sources in different working conditions. The simulation results were presented to demonstrate the good performance of the system. The effectiveness of the proposed energy management strategy was validated. Compared with the conventional strategies where the task requirements cannot be achieved or system stability cannot be accomplished, the proposed algorithms perfectly satisfied the working conditions. [ABSTRACT FROM AUTHOR]

This paper proposed a combined method for wind energy conversion system using pressure coupling (PC) hydrostatic transmission. The operation strategy is the combination of maximizing power point tracking at the input power and stabilizing the output power. The maximum power point tracking method is to control the turbine speed for tracking the optimal tip speed ratio (TSR). For maximizing the input power, a PID controller and a sliding mode controller are applied for speed control to track a predefined speed that is calculated from the optimal TSR. The output power is stabilized by using a high-pressure accumulator for accumulating and compensating the power. The driven speed of the generator is controlled by the PC principle, using a PID controller and an adaptive fuzzy sliding mode controller. Experiments are carried out to verify the proposed method. The overall efficiency in several wind speed profiles is about 40%. [ABSTRACT FROM PUBLISHER]

This paper presents a new control strategy that combines classical control and an optimization scheme to regulate the output voltage of the bidirectional converter under the presence of matched and mismatched disturbances. In detail, a control-oriented modeling method is presented first to capture the system dynamics in a common canonical form, allowing different disturbances to be considered. To estimate and compensate for unknown disturbances, an extended state observer (ESO)-based continuous sliding mode control is then proposed, which can guarantee high tracking precision, fast disturbance rejection, and chattering reduction. Next, an extremum seeking (ES)-based adaptive scheme is introduced to ensure system robustness as well as optimal control effort under different working scenarios. Finally, comparative simulations with classical proportional-integral-derivative (PID) control and constant switching gains are conducted to verify the effectiveness of the proposed adaptive control methodology through three case studies of load resistance variations, buck/boost mode switching, and input voltage variation. [ABSTRACT FROM AUTHOR]