Radial Basis Function Neural Network Sliding Mode Control for Ship Path Following Based on Position Prediction

Zhang, Hugan; Zhang, Xianku; Bu, Renxiang

doi:10.3390/jmse9101055

Cited by 28 publications

(15 citation statements)

References 33 publications

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“…At this stage, the RDOAI-ICS technique exploited the RBFNN model to generate textual descriptions. RBFNN is a specific kind of feedforward network that exactly uses a single hidden layer (HL) [20]. The presented method is used increasingly in regression and classification problems.…”

Section: Image Captioning Using Rbfnn Modelmentioning

confidence: 99%

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

Hilal¹,

Alrowais²,

Al‐Wesabi³

et al. 2023

Computer Systems Science and Engineering

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The problem of producing a natural language description of an image for describing the visual content has gained more attention in natural language processing (NLP) and computer vision (CV). It can be driven by applications like image retrieval or indexing, virtual assistants, image understanding, and support of visually impaired people (VIP). Though the VIP uses other senses, touch and hearing, for recognizing objects and events, the quality of life of those persons is lower than the standard level. Automatic Image captioning generates captions that will be read loudly to the VIP, thereby realizing matters happening around them. This article introduces a Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System (RDOAI-ICS) for Visually Impaired People. The presented RDOAI-ICS technique aids in generating image captions for VIPs. The presented RDOAI-ICS technique utilizes a neural architectural search network (NASNet) model to produce image representations. Besides, the RDOAI-ICS technique uses the radial basis function neural network (RBFNN) method to generate a textual description. To enhance the performance of the RDOAI-ICS method, the parameter optimization process takes place using the RDO algorithm for NasNet and the butterfly optimization algorithm (BOA) for the RBFNN model, showing the novelty of the work. The experimental evaluation of the RDOAI-ICS method can be tested using a benchmark dataset. The outcomes show the enhancements of the RDOAI-ICS method over other recent Image captioning approaches.

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Section: Image Captioning Using Rbfnn Modelmentioning

confidence: 99%

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

Hilal¹,

Alrowais²,

Al‐Wesabi³

et al. 2023

Computer Systems Science and Engineering

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“…(1) i (0) are constant. Substituting (31) into (21), a new Taylor-based SMC scheme is developed to attain a less conservative sign-function gain by selecting 𝜂 i = 0 in (27) as…”

Section: A New Taylor-based Smc Schemementioning

confidence: 99%

“…It seems that achieving a less conservative sign-function gain is constrained by the amplitude of system uncertainty. In order to achieve this goal, approximation of system models by intelligent methods such as fuzzy control [24][25][26] and neural network techniques [27][28][29] has been widely used. However, the real-time control may be affected by imposing excessive computational load.…”

Section: Introductionmentioning

confidence: 99%

Taylor‐based adaptive sliding mode control method for robot manipulators

Fateh

Momeni

Masouleh

2023

IET Control Theory & Appl

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This paper develops a novel Taylor‐based adaptive sliding mode control method (ASMC) for robot manipulators. In the first new scheme, sliding mode control (SMC) is effectively enhanced using the Taylor expansion for achieving a less conservative sign‐function gain that enables chattering attenuation. After that, a new Taylor‐based adaptive SMC scheme is proposed without prior knowledge of the upper bound of uncertainty and the Taylor expansion coefficients. Then, a new Taylor‐based boundary layer ASMC scheme is proposed for chattering attenuation. As a fact, no chattering is expected to be observed as long as the sliding surface remains an invariant set. However, the sliding surface will not be an invariant set unless the sign‐function is precisely determined on the sliding surface. It is verified that the sign‐function cannot be precisely determined on the sliding surface due to the presence of uncertainty, hence, the chattering phenomenon. In the new Taylor‐based boundary layer ASMC scheme, the conventional ASMC is modified by removing the sign‐function in the vicinity of the sliding surface and using the Taylor expansion to estimate and compensate for the uncertainty. Compared to a time‐delay ASMC applied to a robot manipulator, the Taylor‐based ASMC scheme exhibits a less conservative sign‐function gain resulting in chattering attenuation.

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“…RBF techniques are gaining more and more ground in the computer-aided engineering (CAE) field. Their application has already spread in the automotive [29], naval [30], aeronautical [31], energy [32], and medical fields [33]. Their main advantage is their potential to morph the mesh without changing its topology or its consistency while retaining disk usage at low levels.…”

Section: The Mesh Morphing Techniquementioning

confidence: 99%

The Hemodynamic Effect of Modified Blalock–Taussig Shunt Morphologies: A Computational Analysis Based on Reduced Order Modeling

et al. 2022

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The Modified Blalock Taussig Shunt (MBTS) is one of the most common palliative operations in case of cyanotic heart diseases. Thus far, the decision on the position, size, and geometry of the implant relies on clinicians’ experience. In this paper, a Medical Digital Twin pipeline based on reduced order modeling is presented for fast and interactive evaluation of the hemodynamic parameters of MBTS. An infant case affected by complete pulmonary atresia was selected for this study. A three-dimensional digital model of the infant’s MBTS morphology was generated. A wide spectrum of MBTS geometries was explored by introducing twelve Radial Basis Function mesh modifiers. The combination of these modifiers allowed for analysis of various MBTS shapes. The final results proved the potential of the proposed approach for the investigation of significant hemodynamic features such as velocity, pressure, and wall shear stress as a function of the shunt’s morphology in real-time. In particular, it was demonstrated that the modifications of the MBTS morphology had a profound effect on the hemodynamic indices. The adoption of reduced models turned out to be a promising path to follow for MBTS numerical evaluation, with the potential to support patient-specific preoperative planning.

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Radial Basis Function Neural Network Sliding Mode Control for Ship Path Following Based on Position Prediction

Cited by 28 publications

References 33 publications

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

Taylor‐based adaptive sliding mode control method for robot manipulators

The Hemodynamic Effect of Modified Blalock–Taussig Shunt Morphologies: A Computational Analysis Based on Reduced Order Modeling

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