Parameter adaptation is one of the key research fields in the area of evolutionary computation. In this study, the application of neuroevolution of augmented topologies to design efficient parameter adaptation techniques for differential evolution is...
The stability and robustness of quadrotors are always influenced by unknown or immeasurable system parameters. This paper proposes a novel adaptive parameter estimation technology to obtain high-accuracy parameter estimation for quadrotors. A typical...
This article presents an adaptive integral backstepping controller (AIBC) for permanent magnet synchronous motors (PMSMs) with adaptive weight particle swarm optimization (AWPSO) parameters optimization. The integral terms of dq axis current followin...
In actual industrial control, many objects have the characteristics of large lag and time-varying parameters, which makes it difficult for traditional PID control to obtain satisfactory control effects. Therefore, engineers need a control algorithm w...
To improve the observation accuracy and robustness of the sensorless control of an interior permanent magnet synchronous motor (IPMSM), a sliding mode observer based on the super twisting algorithm (STA-SMO) with adaptive parameters estimation contro...
To address the poor adaptability to diverse driving cycles and the imbalance between optimization performance and computational efficiency in existing energy management strategies (EMSs) for plug-in hybrid electric vehicles (PHEVs), this paper propos...
Aspect-based sentiment analysis (ABSA) plays a vital role in deriving fine-grained sentiment from textual content. As large language models (LLMs) are increasingly adopted for automated data annotation in natural language processing (NLP), concerns h...
In this study, parameter adaptation methods for differential evolution are automatically designed using a surrogate approach. In particular, Taylor series are applied to model the searched dependence between the algorithm’s parameters and value...
Many data analysis problems can be modeled as a constrained optimization problem characterized by nonsmooth functionals, often because of the presence of
In order to improve the state monitoring and adaptive control capability of inertial stabilization platforms (ISPs) with unknown loads, it is necessary to estimate the dynamic parameters comprehensively online. However, most current online estimation...
Municipalities are important actors in the field of local climate change adaptation. Stakeholders need scientifically sound information tailored to their needs to make local assessment of climate change effects. To provide tailored data to support mu...
Differential evolution (DE) is one of the most promising black-box numerical optimization methods. However, DE algorithms suffer from the problem of control parameter settings. Various adaptation methods have been proposed, with success history-based...
Differential evolution (DE) has emerged as a numerical optimization technique due to its conceptual simplicity and demonstrated effectiveness across diverse problem domains. However, the algorithm’s performance remains critically dependent on a...
For the shortcomings of an unstable clustering effect and low accuracy caused by the manual setting of the two parameters Eps and MinPts of the DBSCAN (density-based spatial clustering of applications with noise) algorithm, this paper proposes an ada...
In this paper, the parameters identification and synchronization problem of fractional-order neural networks with time delays are investigated. Based on some analytical techniques and an adaptive control method, a simple adaptive synchronization cont...
Efficient in-loop filtering is critical for the latest video-coding standard, versatile video coding (H.266/VVC). While parameter-adaptive mechanisms are effective in traditional adaptive loop filters and overfitted small-scale neural in-loop filteri...
This paper presents a new adaptive torque estimation algorithm for an interior permanent magnet synchronous motor (IPMSM) with parameter variations and cross-coupling between d- and q-axis dynamics. All cross-coupled, time-varying, or uncertain terms...
Against the engineering background of continuous expansion of renewable energy units, in islanded microgrids employing virtual synchronous generator (VSG) control, newly connected VSGs often cannot obtain the key control parameters of existing VSGs,...
The operation of CNC machining centers, despite their technological progress, can still be affected by undesirable events associated with the technological parameters of their operation. The minimization of these risks can be achieved via their adapt...
Recent studies on parameter-efficient fine-tuning (PEFT) have introduced effective and efficient methods for fine-tuning large language models (LLMs) on downstream tasks using fewer parameters than required by full fine-tuning. Low-rank decomposition...
With the growing scale of pre-trained language models (PLMs), full parameter fine-tuning becomes prohibitively expensive and practically infeasible. Therefore, parameter-efficient adaptation techniques for PLMs have been proposed to learn through inc...
The operating parameters of the active direct methanol fuel cell (DMFC) are essential factors that affect cell performance. However, it is challenging to maintain the optimal maximum output power density due to the system’s complexity, the oper...
Real-time performance and adaptability are critical factors influencing the safety and stability of autonomous vehicle trajectory tracking. Therefore, enhancing these aspects is essential for improving driving safety. This paper proposes a trajectory...
Long COVID patients show symptoms, such as fatigue, muscle weakness and pain. Adequate diagnostics are still lacking. Investigating muscle function might be a beneficial approach. The holding capacity (maximal isometric Adaptive Force; AFisomax) was...
This study addresses the challenges of real-time channel state estimation and adaptive parameter adjustment in dynamic LoRa networks, where the existing methods often fail to adapt efficiently to highly variable channel conditions. This study present...
Stochastic fractal search (SFS) is a novel method inspired by the process of stochastic growth in nature and the use of the fractal mathematical concept. Considering the chaotic stochastic diffusion property, an improved dynamic stochastic fractal se...
This paper presents and analyzes a new four-dimensional (4D) jounce hysteresis chaotic dynamical system and investigates its application to robust communication. An adaptive chaotic synchronization scheme is developed based on the proposed 4D jounce...
To better process irregular sample images for their image feature extraction and recognition, this essay proposes asymmetric adaptive neural network (AACNN) structures, including dual structures of an adaptive image feature extraction network (AT-CNN...
This paper puts forward a new adaptive observer scheme for joint estimation of state and multi-parameters for nonlinear dynamic systems. The adaptive observer uses chaos differential evolution algorithm to improve global optimality of estimation in t...
This paper presents a method to design a parameter adaptive suspension controller to boost ride comfort and to reduce motion sickness. According to recently published papers, combined motions of a sprung mass (SPMS) along heave and pitch directions t...
Meta-heuristic algorithms are the dominant techniques for parameter estimating for solar photovoltaic (PV) models. Current algorithms are primarily designed with a focus on search performance and convergence speed, but they fail to account for the si...
Event cameras capture sparse, high-temporal-resolution visual information, making them attractive for challenging scenarios with fast motion and severe illumination changes. However, event-based depth models trained on one real-world benchmark often...
End-to-end voice cloning models like VITS require large amounts of data to produce high-quality speech, making speaker adaptation difficult when target data is limited. To address this problem, this paper introduces AdaptVITS, a parameter-efficient f...
This paper presents an adaptive dynamic surface sliding mode control technique to address the issue of system parameter changes in permanent magnet synchronous motor (PMSM) position servo systems. The proposed method involves adopting a linear parame...
Computational fluid dynamics (CFD) numerical simulations play an important role in many research fields, including hydrological basins, rivers, floods, and dam breaks. Currently, much research mainly pursues accuracy, efficiency, scale, dimensions, e...
In this paper, an adaptation method for adjusting the scaling parameters of an unscented Kalman filter (UKF) is proposed to improve the estimation performance of the filter in dynamic conditions. The proposed adaptation method is based on a sequentia...
Visual surveillance systems have been playing a vital role in human modern life with a large number of applications, ranging from remote home management, public security to traffic monitoring. The recent High Efficiency Video Coding (HEVC) scalable e...
This paper presents a robust tracking control strategy for servo systems with unknown backlash, employing adaptive parameter identification to address performance degradation caused by backlash nonlinearities. In high-precision positioning and rapid-...
This paper presents a comparative study on active suspension controllers for ride comfort. Two types of active suspension controllers are designed and compared in terms of ride comfort: static output feedback (SOF) and parameter adaptive ones, which...
Increasingly more power electronic devices are being connected to DC microgrids, which reduces the inertia of a DC microgrid, and the DC bus voltage has poor resistance to disturbance. Adding a virtual DC motor control to the converter can effectivel...
In order to tackle the inaccurate step length measurement of people with different heights and in different motion states, a height-adaptive method of step length measurement based on motion parameters is proposed in this paper. This method takes peo...
In order to improve the performance of three-phase NPC inverters under unbalanced working conditions, a quasi-proportional complex integral controller (QPCI) three-phase inverter control method based on an adaptive fractional-order algorithm is propo...
Unbalance vibration is one of the main vibration forms of a high speed machine tool spindle. The overlarge unbalance vibration will have some adverse effects on the working life of the spindle system and the surface quality of the work-piece. In orde...
A mechanoregulatory numerical model of mandibular bone remodeling was proposed. The model incorporated regional calibration of the adaptation parameter in the Huiskes–Weinans remodeling law across 16 anatomical regions (eight cancellous and eig...
In this study, twelve modified differential evolution algorithms with memory properties and adaptive parameters were proposed to address optimization problems. In the experimental process, these modified differential evolution algorithms were applied...
Underwater images often suffer from luminance attenuation, structural degradation, and color distortion due to light absorption and scattering in water. The variations in illumination and color distribution across different water bodies further incre...
In power systems with a high penetration of renewable energy, integrating battery energy storage systems can enhance frequency regulation capabilities. However, in “islanded” operation mode, the lack of large grid interconnection support...
Achieving measurable and unmeasurable parameter prediction is the key process in model-based control, for which an accurate onboard model is the most important part. However, neither nonlinear models like component level models or LPV models, nor lin...
In this paper, a new fuzzy harmony search algorithm (FHS) for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR) and pitch adjustment (PArate) par...
Aiming at the problem that online parameter identification, based on the Model Reference Adaptive System (MRAS), is easily affected by the high-frequency noise of the sensor, an improved MRAS, based on variable bandwidth linear Active Disturbance Rej...
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