Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

Mechanical Performance of Bio-inspired Bidirectional Corrugated Sandwich Pressure Shell Under External Hydrostatic Pressure

This paper aims to enhance the compression capacity of underwater cylindrical shells by adopting the corrugated sandwich structure of cuttlebone.The cuttlebone suffers uniaxial external compression,while underwater cylindrical shells are in a biaxial compressive stress state.To suit the biaxial compressive stress state,a novel bidirectional corrugated sandwich structure is proposed to improve the bearing capacity of cylindrical shells.The static and buckling analysis for the sandwich shell and the unstiffened cylindrical shell with the same volume-weight ratio are studied by numerical simulation.It is indicated that the proposed sandwich shell can effectively reduce the ratio between circumferential and axial stress from 2 to 1.25 and improve the critical buckling load by about 1.63 times.Numerical simulation shows that optimizing and adjusting the structural parameters could significantly improve the advantage of the sandwich shell.Then,the hydrostatic pressure tests for shell models fabricated by 3D printing are carried out.According to the experimental results,the overall failure position of the sandwich shell is at the center part of the sandwich shell.It has been found the average critical load of the proposed sandwich shell models exceeds two times that of the unstiffened shell models.Hence,the proposed bio-inspired bidirectional corrugated sandwich structure can significantly enhance the pressure resistance capability of cylindrical shells.

Enhancing Cancer Classification through a Hybrid Bio-Inspired Evolutionary Algorithm for Biomarker Gene Selection

In this study,our aim is to address the problem of gene selection by proposing a hybrid bio-inspired evolutionary algorithm that combines Grey Wolf Optimization(GWO)with Harris Hawks Optimization(HHO)for feature selection.Themotivation for utilizingGWOandHHOstems fromtheir bio-inspired nature and their demonstrated success in optimization problems.We aimto leverage the strengths of these algorithms to enhance the effectiveness of feature selection in microarray-based cancer classification.We selected leave-one-out cross-validation(LOOCV)to evaluate the performance of both two widely used classifiers,k-nearest neighbors(KNN)and support vector machine(SVM),on high-dimensional cancer microarray data.The proposed method is extensively tested on six publicly available cancer microarray datasets,and a comprehensive comparison with recently published methods is conducted.Our hybrid algorithm demonstrates its effectiveness in improving classification performance,Surpassing alternative approaches in terms of precision.The outcomes confirm the capability of our method to substantially improve both the precision and efficiency of cancer classification,thereby advancing the development ofmore efficient treatment strategies.The proposed hybridmethod offers a promising solution to the gene selection problem in microarray-based cancer classification.It improves the accuracy and efficiency of cancer diagnosis and treatment,and its superior performance compared to other methods highlights its potential applicability in realworld cancer classification tasks.By harnessing the complementary search mechanisms of GWO and HHO,we leverage their bio-inspired behavior to identify informative genes relevant to cancer diagnosis and treatment.

Integration of bio-inspired limb-like structure damping into motor suspension of high-speed trains to enhance bogie hunting stability

Hunting stability is an important performance criterion in railway vehicles.This study proposes an incorporation of a bio-inspired limb-like structure(LLS)-based nonlinear damping into the motor suspension system for traction units to improve the nonlinear critical speed and hunting stability of high-speed trains(HSTs).Initially,a vibration transmission analysis is conducted on a HST vehicle and a metro vehicle that suffered from hunting motion to explore the effect of different motor suspension systems from on-track tests.Subsequently,a simplified lateral dynamics model of an HST bogie is established to investigate the influence of the motor suspension on the bogie hunting behavior.The bifurcation analysis is applied to optimize the motor suspension parameters for high critical speed.Then,the nonlinear damping of the bio-inspired LLS,which has a positive correlation with the relative displacement,can further improve the modal damping of hunting motion and nonlinear critical speed compared with the linear motor suspension system.Furthermore,a comprehensive numerical model of a high-speed train,considering all nonlinearities,is established to investigate the influence of different types of motor suspension.The simulation results are well consistent with the theoretical analysis.The benefits of employing nonlinear damping of the bio-inspired LLS into the motor suspension of HSTs to enhance bogie hunting stability are thoroughly validated.

Dynamic crushing behaviors and enhanced energy absorption of bio-inspired hierarchical honeycombs with different topologies

In order to pursue good crushing load uniformity and enchance energy absorption efficiency of conventional honeycombs, a kind of bio-inspired hierarchical honeycomb model is proposed by mimicking the arched crab shell structures. Three bio-inspired hierarchical honeycombs(BHHs) with different topologies are designed by replacing each vertex of square honeycombs with smaller arc-shaped structures. The effects of hierarchical topologies and multi-material layout on in-plane dynamic crushings and absorbed-energy capacities of the BHHs are explored based on the explicit finite element(FE) analysis.Different deformation modes can be observed from the BHHs, which mainly depend upon hierarchical topologies and impact velocities. According to energy efficiency method and one-dimensional(1D) shock theory, calculation formulas of densification strains and plateau stresses for the BHHs are derived to characterize the dynamic bearing capacity, which is consistent well with FE results. Compared with conventional honeycombs, the crushing load efficiency and energy absorption capacity of the BHHs can be improved by changing the proper hierarchical topology and multi-material layout. These researches will provide theoretical guidance for innovative design and dynamic response performance controllability of honeycombs.

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.

Vibration isolation performance analysis of a bilateral supported bio-inspired anti-vibration control system

To achieve better anti-vibration performance in a low frequency region and expand the range of vibration isolation,a bilateral supported bio-inspired anti-vibration(BBAV)structure composed of purely linear elements is proposed,inspired by the motion form of bird legs and the nonlinear extension and compression of muscles and tendons.The kinematic relations and nonlinear dynamic model considering vertical and rotational vibrations are established.The loading capacity and equivalent stiffness are investigated with key parameters.The amplitude-frequency characteristics and force transmissibility are used to evaluate the stability and anti-vibration performance with the effects of the excitation amplitude,rod length,installation angle,and spring stiffness.The results show that the loading requirements and resonant characteristics of the BBAV structure are adjustable,and superior vibration isolation performance can be achieved readily by tuning the parameters.The X-shaped vibration structure is sensitive to the spring stiffness,which exhibits a wider vibration isolation bandwidth with smaller spring stiffness.Besides,depending on the parameters,the nonlinear behavior of the BBAV system can be interconverted between the softening type and the hardening type.The theoretical analysis in this study demonstrates the advantages and effectiveness of the vibration isolation structure.

CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

Blockchain has been widely used in finance,the Internet of Things(IoT),supply chains,and other scenarios as a revolutionary technology.Consensus protocol plays a vital role in blockchain,which helps all participants to maintain the storage state consistently.However,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus protocol.To address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation opinions.This can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore accurate.In addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of attack.The experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control performance.This is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are crucial.The ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is essential.The likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical importance.Long-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be made.The focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation post-failure.This paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past decade.These strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and reestablishment.The paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in FTC.Finally,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.

Integration of a Fault-Tolerant H-Bridge Inverter into the Photovoltaic System for DC-AC Conversion of Electrical Energy

The photovoltaic system is experiencing great growth in the production of electrical energy these days.It plays a vital role in the production of electrical energy in isolated towns.It is generally either stand-alone or connected to a network.The energy produced by the photovoltaic generator is in continuous form;the conversion from its continuous form to the alternating form requires a converter:the inverter.In order to improve the quality of the waveform,we moved from the classic solar inverter to multilevel inverters.These multilevel inverters are equipped with power switches which are required to withstand strong fluctuations in the voltage produced by the GPV(photovoltaic generator).It is obvious that the degradation of the inverter leads to a distortion of the wave quality.This article presents the simulation of the GPV-Chopper Boost-Inverter chain in fault-tolerant cascaded H-bridges in order to overcome the difficulties of voltage constraints experienced by power switches(IGBT:insulated gate bipolar transistor).The results of simulations carried out in Matlab/Simulink show good performance of the designed inverter model.

A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

BIO-INSPIRED SELF-ADAPTIVE MANUFACTURING SYSTEM CONTROL ARCHITECTURE

Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.

Formation Control for Water-Jet USV Based on Bio-Inspired Method

The formation control problem for underactuated unmanned surface vehicles(USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law,and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.

Nanoscale All-Oxide-Heterostructured Bio-inspired Optoresponsive Nociceptor

Retina nociceptor,as a key sensory receptor,not only enables the transport of warning signals to the human central nervous system upon its exposure to noxious stimuli,but also triggers the motor response that minimizes potential sensitization.In this study,the capability of two-dimensional all-oxide-heterostructured artificial nociceptor as a single device with tunable properties was confirmed.Newly designed nociceptors utilize ultra-thin sub-stoichiometric TiO2–Ga2O3 heterostructures,where the thermally annealed Ga2O3 films play the role of charge transfer controlling component.It is discovered that the phase transformation in Ga2O3 is accompanied by substantial jump in conductivity,induced by thermally assisted internal redox reaction of Ga2O3 nanostructure during annealing.It is also experimentally confirmed that the charge transfer in alloxide heterostructures can be tuned and controlled by the heterointerfaces manipulation.Results demonstrate that the engineering of heterointerfaces of two-dimensional(2D)films enables the fabrication of either high-sensitive TiO2–Ga2O3(Ar)or high-threshold TiO2–Ga2O3(N2)nociceptors.The hypersensitive nociceptor mimics the functionalities of corneal nociceptors of human eye,whereas the delayed reaction of nociceptor is similar to high-threshold nociceptive characteristics of human sensory system.The long-term stability of 2D nociceptors demonstrates the capability of heterointerfaces engineering for e ective control of charge transfer at 2D heterostructured devices.

Influence of bio-inspired flow channel designs on the performance of a PEM fuel cell

Performance of the proton exchange membrane fuel cell(PEMFC)is appreciably affected by the channel geometry.The branching structure of a plant leaf and human lung is an efficient network to distribute the nutrients in the respective systems.The same nutrient transport system can be mimicked in the flow channel design of a PEMFC,to aid even reactant distribution and better water management.In this work,the effect of bio-inspired flow field designs such as lung and leaf channel design bipolar plates,on the performance of a PEMFC was examined experimentally at various operating conditions.A PEMFC of 49 cm2 area,with a Nafion 212 membrane with a 40%catalyst loading of 0.4 mg·cm-2 on the anode side and also 0.6 mg·cm-2 on the cathode side is assembled by incorporating the bio-inspired channel bipolar plate,and was tested on a programmable fuel-cell test station.The impact of the working parameters like reactants’relative humidity(RH),back pressure and fuel cell temperature on the performance of the fuel cell was examined;the operating pressure remains constant at 0.1 MPa.It was observed that the best performance was attained at a back pressure of 0.3 MPa,75°C operating temperature and 100%RH.The three flow channels were also compared at different operating pressures ranging from 0.1 MPa to 0.3 MPa,and the other parameters such as operating temperature,RH and back pressure were set as 75°C,100%and 0.3 MPa.The experimental outcomes of the PEMFC with bio-inspired channels were compared with the experimental results of a conventional triple serpentine flow field.It was observed that among the different flow channel designs considered,the leaf channel design gives the best output in terms of power density.Further,the experimental results of the leaf channel design were compared with those of the interdigitated leaf channel design.The PEMFC with the interdigitated leaf channel design was found to generate 6.72%more power density than the non-interdigitated leaf channel design.The fuel cell with interdigitated leaf channel design generated5.58%more net power density than the fuel cell with non-interdigitated leaf channel design after considering the parasitic losses.

A Bio-Inspired Flapping-Wing Robot With Cambered Wings and Its Application in Autonomous Airdrop

Flapping-wing flight, as the distinctive flight method retained by natural flying creatures, contains profound aerodynamic principles and brings great inspirations and encouragements to drone developers. Though some ingenious flapping-wing robots have been designed during the past two decades, development and application of autonomous flapping-wing robots are less successful and still require further research. Here, we report the development of a servo-driven bird-like flapping-wing robot named USTBird-I and its application in autonomous airdrop.Inspired by birds, a camber structure and a dihedral angle adjustment mechanism are introduced into the airfoil design and motion control of the wings, respectively. Computational fluid dynamics simulations and actual flight tests show that this bionic design can significantly improve the gliding performance of the robot, which is beneficial to the execution of the airdrop mission.Finally, a vision-based airdrop experiment has been successfully implemented on USTBird-I, which is the first demonstration of a bird-like flapping-wing robot conducting an outdoor airdrop mission.

Bio-inspired geomagnetic navigation method for autonomous underwater vehicle

This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.

PVC gel bio-inspired adhesives with variable modulus and its application in a gripper

Inspired by the microstructure of gecko’s toe,two kinds of polyvinyl chloride(PVC)gels with different modulus were poured on a silicon mold with micropillars,and then a bio-inspired adhesive with variable modulus was manufactured in this study.The adhesions of variable modulus and fixed modulus bio-inspired adhesives were tested,respectively,on a smooth glass and a printed circuit board(PCB)with different surface structures.The results show that PVC gel bio-inspired adhesives with variable modulus have many advantages compared with the fixed modulus bioinspired adhesives.The adhesion of variable modulus bio-inspired adhesives on the rough PCB surface increased by 2−5 times,and due to the use of variable modulus of PVC gel,the surface micropillars can maintain high aspect ratio and flexible tips at the same time.Moreover,the use of PVC gel makes it easier to demold during the bio-inspired adhesives preparation.An adhesion-desorption device was made according to the movement of the gecko toes,and the PCB was successfully grasped.

Design and Fuel Consumption Optimization for a Bio-Inspired Semi-floating Hybrid Vehicle

Based on a bionic concept and combing air-cushion techniques and track driving mechanisms, a novel semi-floating hybrid concept vehicle is proposed to meet the transportation requirements on soft terrain. First, the vehicle scheme and its improved duel-spring flexible suspension design are described. Then, its fuel consumption model is proposed accordingly with respect to two vehicle operating parameters. Aiming at minimizing the fuel consumption, two Genetic Algorithms （GAs） are designed and implemented. For the initial one （GA-1）, despite getting an acceptable result, there still existed some problems in its optimiza- tion process. Based on an analysis of the defects of GA-1, an improved algorithm GA-2 was developed whose effectiveness and stability were embodied in the optimization process and results. The proposed design scheme and optimization approaches can provide valuable references for this new kind of vehicle with industry, military or scientific exploitations, etc. promising applications in the areas of agriculture, petroleum industry, military or scientific explaitations, etc.

Distributed event region fault-tolerance based on weighted distance for wireless sensor networks

Event region detection is the important application for wireless sensor networks（WSNs）, where the existing faulty sensors would lead to drastic deterioration of network quality of service.Considering single-moment nodes fault-tolerance, a novel distributed fault-tolerant detection algorithm named distributed fault-tolerance based on weighted distance（DFWD） is proposed, which exploits the spatial correlation among sensor nodes and their redundant information.In sensor networks, neighborhood sensor nodes will be endowed with different relative weights respectively according to the distances between them and the central node.Having syncretized the weighted information of dual-neighborhood nodes appropriately, it is reasonable to decide the ultimate status of the central sensor node.Simultaneously, readings of faulty sensors would be corrected during this process.Simulation results demonstrate that the DFWD has a higher fault detection accuracy compared with other algorithms, and when the sensor fault probability is 10%, the DFWD can still correct more than 91% faulty sensor nodes, which significantly improves the performance of the whole sensor network.