Circular Trajectory Research Articles

Development of a New Cable-Driven Planar Parallel Continuum Robot Using Compound Kinematic Calibration Method

Abstract This paper presents the design, calibration, and development of a novel cable-driven planar parallel continuum robot (PCR). The PCR employs a novel drive unit, which is mainly composed of cables, guiding pulleys, and miniature linear actuators. The kinematic model of the PCR is derived based on the constant curvature assumption and the space vector method, and its workspace and singularity are analyzed. In addition, this paper adopts a novel compound kinematic calibration method, which includes the linear calibration method in the robot-specific model and the use of genetic algorithm (GA) in the robot-independent model. To verify the validity of the calibration method, the pose accuracy is assessed by providing positional points on the elliptical trajectory, and the trajectory tracking accuracy is evaluated by using circular and rectangular trajectories. The experimental results show that the static positioning accuracy is maintained at 1 mm; meanwhile, the trajectory tracking accuracy is controlled within the range of 0.9–1.4 mm. The PCR developed in this paper shows good comprehensive performance by employing the proposed novel compound kinematic calibration method.

A simple and precise alignment calibration method for cone-beam computed tomography with the verifications

Cone-beam computed tomography (CBCT) is widely used in dental imaging, small animal imaging, radiotherapy, and non-destructive industrial inspection. The quality of CBCT images depends on the precise knowledge of the CBCT system’s alignment. We introduce a distinct procedure, ‘precision alignment loop (PAL)’, to calibrate any CBCT system with a circular trajectory. We describe the calibration procedure by using a line-beads phantom, and how PAL determines the misalignments from a CBCT system. PAL also yields the uncertainties in the simulated calibration to give an estimate of the errors in the misalignments. From the analytical simulations, PAL can precisely obtain the source-to-rotation axis distance, and the geometric center G, ‘the point in z-axis meets the detector’, where the z-axis is coincident with the line from the x-ray source that intersects the axis of the rotation orthogonally. The uncertainties of three misalignment angles of the detector are within ±0.05°, which is close to ±0.04° for the results of Yang et al (2017 Med. Phys. 44 1692), but our method is easy and simple to implement. Our distinct procedure, on the other hand, yields the calibration of a micro-CT system and an example of reconstructed images, showing our calibration method for the CBCT system to be simple, precise, and accurate.

One small step for a robot, one giant leap for habitat monitoring: A structural survey of EU forest habitats with Robotically-mounted Mobile Laser Scanning (RMLS)

EU States are mandated by the 92/43/EEC Habitats Directive to generate recurring reports on the conservation status and functionality of habitats at the national level. This assessment is based on their floristic and, especially for forest habitats, structural characterization. Currently, habitat field monitoring efforts are carried out only by trained human operators. The H2020 Project “Natural Intelligence for Robotic Monitoring of Habitats – NI” aims to develop quadrupedal robots able to move autonomously in the unstructured environment of forest habitats. In this work, we tested the locomotion performance, efficiency and the accuracy of a robot performing structural habitat monitoring, comparing it with traditional field survey methods inside selected stands of Luzulo-Fagetum beech forests (9110 Annex I Habitat). We used a quadrupedal robot equipped with a Mobile Laser Scanning system (MLS), implementing for the first time a structural monitoring of EU forest habitats with a Robotically-mounted Mobile Laser Scanning (RMLS) platform. Two different scanning trajectories were used to automatically map individual tree locations and extract tree Diameter at Breast Height (DBH) from point clouds. Results were compared with field human measurements in terms of accuracy and efficiency of the survey. The robot was able to successfully execute both scanning trajectories, for which we obtained a tree detection rate of 100 %. Circular scanning trajectory performed better in terms of battery consumption, Root Mean Square Error (RMSE) of the extracted DBH (2.43 cm or 10.73 %) and prediction power (R2adj = 0.72, p < 0.001). The RMLS platform improved survey efficiency with 19.31 m2/min or 1.77 trees/min in comparison with 3.45 m2/min or 0.32 trees/min of traditional survey. Finally, a processing script was developed to allow the repeatability of RMLS surveys in similar habitat monitoring missions. In the future, a human-robotic monitoring framework might represent an accurate support for those repetitive and time-consuming activities in habitat monitoring, offering a valuable benefit for biodiversity conservation.

Localizing sounds revolving at very high velocities: An auditory wagon-wheel effect

Localizing sound sources as they move around us is a critical function of the auditory system. Yet most research focuses on static sound sources or sources moving at slow velocities. The present work explores circular trajectories at very high velocities well above the velocity at which we lose the sense of direction (∼2.5 rot/s with white noise). As the number of rotations per second approaches the fundamental frequency of the spinning sound, a sense of direction re-emerges. This creates what has been described informally as the auditory equivalent to the wagon-wheel effect: the sound appears to move in one direction when the velocity is below the fundamental frequency, and it appears to move in the opposite direction when the velocity is above the fundamental frequency. We report on two experiments testing this effect with a 200-Hz complex sound using adaptive VBAP spatialization on a 16-loudspeaker array. Experiment 1 (N = 15) confirmed that participants perceived opposite directions when the velocity was below or above the fundamental frequency. Experiment 2 (N = 7) explores the relationship between this effect at very high velocities and the ability to track sound at slower velocities. Preliminary findings suggest some overlap between localization processes at slow and high velocities.

Direction of arrival estimation using the rotating equatorial microphone

Introduction: Direction of arrival (DOA) estimation of sound sources is an essential task of sound field analysis which typically requires two or more microphones. In this study, we present an algorithm that allows for DOA estimation using the previously designed Rotating Equatorial Microphone prototype, which is a single microphone that moves rapidly along a circular trajectory, introducing DOA-dependent periodic distortions in the captured signal.Methods: Our algorithm compensates for the induced spectral distortions caused by the REM’s circular motion for multiple DOA candidates. Subsequently, the best DOA candidate is identified using two distortion metrics. We verify our approach through numerical simulations and practical experiments conducted in a low-reverberant environment.Results: The proposed approach localizes unknown single-frequency sources with a mean absolute error of 23 degrees and unknown wideband sources with a mean absolute error of 5.4 degrees in practice. Two sources are also localizable provided they are sufficiently separated in space.Conclusion: Whilst previous work only allowed for DOA estimation of a single monochromatic sound source with a known frequency, our DOA estimation algorithm enables localization of unknown and arbitrary sources with a single moving microphone.

Compliance Modeling and Kinetostatic Analysis of a Generalized 3-PSS Compliant Parallel Micro-Motion Platform.

In order to expand the range of motion performance of the 3-PSS-compliant parallel micro-motion platform, a variable inclination angle of the mechanism's guide rails was introduced to construct a category of generalized 3-PSS compliant parallel micro-motion platforms with distinct configurations (exhibiting different motion performances) but identical motion patterns (three translational degrees of freedom). The compliance and kinetostatics of such micro-motion platform are modeled and analyzed. Firstly, the compliance model is established based on the coordinate transformation method. Then, simplifying the micro-motion platform into a spring system, the kinetostatic model in terms of input force-output displacement is established based on the compliance model using the compliance matrix method. For practical application considerations, the kinetostatic model in terms of input displacement-output displacement is further derived based on the input force-output displacement model. Then, the correctness of the established compliance model and kinetostatic model is successively verified through finite element simulation. Finally, using two specified motion trajectories (spatial spiral trajectory and planar circular trajectory) as examples, an analysis is conducted on the influence of guide rail inclination angle variations on the kinetostatic performance of the micro-motion platform. This analysis serves as guidance for the rational design of such micro-motion platforms.

DDPG-based reinforcement learning for controlling a spatial three-section continuum robot

This paper proposes an approach to controlling a spatial three-section continuum robot using reinforcement learning (RL). Rather than relying on traditional methods that use bending and orientation angles, this study utilizes the curvature of each section to achieve the desired position. The training process involves identifying a 3D workspace for the robot and utilizing a deep neural network to optimize its control policies. The results demonstrate that the robot’s end effector can follow a given trajectory with a maximum error of 1 [1/mm] based on the generated curvature for each section. The Deep Deterministic Policy Gradients (DDPG) algorithm is employed to optimize the robot’s control policies. Additionally, the developed DDPG algorithm is compared to the Deep Q-Network (DQN) from a precision standpoint, particularly during the tracking of a circular trajectory. This comparison highlights the superior accuracy of DDPG in managing the intricate movements required for continuum robotics, making it a promising tool for applications where precision is crucial, such as in medical and surgical robotics.

Adaptive robust control with slipping parameters estimation based on intelligent learning for wheeled mobile robot

The widespread use of wheeled mobile robots (WMRs) in many fields has created new challenges. A critical issue is wheel slip, which, if not accurately determined and controlled, causes instability and deviation from the robot’s path. In this paper, an intelligent approach for estimating the longitudinal and lateral slip of wheels is proposed that can effectively compensate for the negative effects of slippage. The proposed algorithm relies on three regression networks to estimate the longitudinal slip ratio of the right and left wheels and sideslip angle on terrains with different friction coefficients. The datasets collected during tests on different surfaces with various maneuvers are used to train the artificial neural networks (ANNs). A developed dynamic model of a WMR considering wheel slip and modified traction force is presented. The adaptive robust controller, based on sliding mode control (SMC), is introduced to deal with the problems related to slipping, unknown uncertainties, and disturbances. The simulation results demonstrate that the presented controller has better performance than SMC in handling external disturbances and uncertainties, which leads to reduction in tracking error and faster convergence to zero. The proposed controller with an intelligent slip estimator, has been applied to a four-wheel mobile robot to demonstrate its effectiveness and feasibility. The high accuracy of slip estimation in the mentioned intelligent algorithm has resulted in the presented method being on average 26% more effective in reducing the tracking error than the control method without slip compensation in each test for circular trajectory.

Effect of the beam oscillation on the structure and mechanical properties of electron beam welded joints of Ti6Al4V and Al6082-T6 alloys

The results of electron beam welding of Ti6Al4V and Al6082-T6 alloys are presented. The influence of electron-beam scanning geometry on the structure and mechanical properties of the welded joint is studied. Two kinds of samples were investigated – the first specimen was welded without beam oscillation and the second one was obtained using an oscillating electron beam following a circular trajectory of scanning with an oscillation radius of 0.2 mm. X-ray diffraction (XRD) method was used for the determination of the phase composition of the welded joints. The microstructure of the welded joints was studied using Scanning electron microscopy (SEM). Energy-dispersive X-ray spectroscopy (EDX) was applied for the chemical composition investigation. Tensile experiments and microhardness measurements were performed to study the mechanical properties of the welded joints. The sample welded without the application of an oscillating beam showed higher values for the yield strength and tensile strength. The values measured for the microhardness within the welded seam are about 450 HV0.05 in both cases. However, the application of a beam oscillation leads to a significant increase in the micro-hardness of the heat affected zone at the Ti-based alloy. The measured values reached 627 HV0.05.

Development of a Minimally Invasive Surgical Robot Using Self-Helix Twisted Artificial Muscles

In the field of surgery, minimally invasive surgical robots (MISRs) have emerged as the persistent pursuit of physicians to minimize harm and perform precise surgery. The structure of newly proposed MISRs tends to change form rigid to flexible, which poses a challenge to precise control. In this work, a MISR actuated by self-helix twisted artificial muscles (SHTAMs) with large bending angle and high precision is developed. The configuration and operation principle of the MISR are illustrated. Then, the physical model of SHTAM and the kinematics model of the end effector are established. The contraction ratio of SHTAM reaches 27.5%, and the output force is 5424.2 mN. Besides, the maximum bending angle (about 92°) of MISR is measured to verify the kinematic analysis. Moreover, in the point positioning control experiments, the steady-state error is less than 0.11°. Subsequently, the trajectory tracking tests on sinusoidal trajectories with different frequencies and amplitudes are carried out, and the circular trajectory tracking experiment is also performed with a maximum error of 1.8° in cold gel environment. The experimental results indicate that the proposed MISR has a large bending angle and can achieve accurate trajectory control, which exhibits excellent prospect in precision minimally invasive surgery.

Adaptive Skid-Steering Control Approach for Robots on Uncertain Inclined Planes with Redundant Load-Bearing Mobility.

Climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components, while the motion control of climbing manipulation-oriented robots (CMo-Rs) is still challenging considering anti-slippage problems. In this study, a CMo-R with full-scenery climbing capability and redundant load-bearing mobility is designed based on magnetic adsorption. A four-wheel kinematic model considering the slipping phenomenon is established. An adaptive kinematic control algorithm based on slip estimation using Lyapunov theory is designed for uncertain inclined planes. For comparison, the traditional PID-based algorithm without slip consideration is implemented as well. Numeric simulations are conducted to tackle the trajectory tracking problems for both circular and linear trajectories on the horizontal plane (HP), 50° inclined plane (50° IP), 60° inclined plane (60° IP), and vertical plane (VP). The results prove that our approach achieves better tracking accuracy. It demonstrated applicability in various climbing scenarios with uncertain inclined planes. The results of experiments also validate the feasibility, applicability, and stability of the proposed approach.

Reduction of cone-beam CT artifacts in a robotic CBCT device using saddle trajectories with integrated infrared tracking.

Cone beam computed tomography (CBCT) is widely used in many medical fields. However, conventional CBCT circular scans suffer from cone beam (CB) artifacts that limit the quality and reliability of the reconstructed images due to incomplete data. Saddle trajectories in theory might be able to improve the CBCT image quality by providing a larger region with complete data. Therefore, we investigated the feasibility and performance of saddle trajectory CBCT scans and compared them to circular trajectoryscans. We performed circular and saddle trajectory scans using a novel robotic CBCT scanner (Mobile ImagingRing (IRm); medPhoton, Salzburg, Austria). For the saddle trajectory, the gantry executed yaw motion up to using motorized wheels driving on the floor. An infrared (IR) tracking device with reflective markers was used for online geometric calibration correction (mainly floor unevenness). All images were reconstructed using penalized least-squares minimization with the conjugate gradient algorithm from RTK with voxel size. A disk phantom and an Alderson phantom were scanned to assess the image quality. Results were correlated with the local incompleteness value represented by , which was calculated at each voxel as a function of the source trajectory and the voxel's 3D coordinates. We assessed the magnitude of CB artifacts using the full width half maximum (FWHM) of each disk profile in the axial center of the reconstructed images. Spatial resolution was also quantified by the modulation transfer function at 10% (MTF10). When using the saddle trajectory, the region without CB artifacts was increased from 43 to 190mm in the SI direction compared to the circular trajectory. This region coincided with low values for . When was larger than 0.02, we found there was a linear relationship between the FWHM and . For the saddle, IR tracking allowed the increase of MTF10 from 0.37 to 0.98 lp/mm. We achieved saddle trajectory CBCT scans with a novel CBCT system combined with IR tracking. The results show that the saddle trajectory provides a larger region with reliable reconstruction compared to the circular trajectory. The proposed method can be used to evaluate other non-circulartrajectories.

Optimum object selection methods for spontaneous gaze-based interaction with linear and circular trajectories

The demand for touchless technologies has increased since the outbreak of Covid-19. Spontaneous gaze-based interaction is a promising technique because it offers a natural approach for object selection using eye movements. There are two types of object trajectory in spontaneous gaze-based interaction: linear and circular trajectories. However, previous studies did not consider the optimum object selection method by taking into account the characteristics of each trajectory. In addition, previous studies suffered from high missed detection that caused spontaneous gaze-based applications to be less accurate and responsive. To address these scientific gaps, we conducted a novel study to propose optimum methods for object selection in linear and circular trajectories. The experimental results suggested that each trajectory requires a different combination of events detection and object selection techniques to achieve optimum performance. We recommend 2D Correlation as the object selection technique. In addition, we also recommend the Velocity and Movement Pattern Identification (I-VMP) and the Hidden Markov Model (HMM) as events detection techniques in linear and circular trajectories, respectively. The proposed approaches solved the missed detection problem and significantly increased the accuracy of gaze-based object selection to 95.60% and 99.73% on linear and circular trajectories, respectively. In the future, our discoveries are promising for the development of accurate, responsive, and seamless gaze-based touchless applications.

Defected twisted ring topology for autonomous periodic flip-spin-orbit soft robot.

Periodic spin-orbit motion is ubiquitous in nature, observed from electrons orbiting nuclei to spinning planets orbiting the Sun. Achieving autonomous periodic orbiting motions, along circular and noncircular paths, in soft mobile robotics is crucial for adaptive and intelligent exploration of unknown environments-a grand challenge yet to be accomplished. Here, we report leveraging a closed-loop twisted ring topology with a defect for an autonomous soft robot capable of achieving periodic spin-orbiting motions with programmed circular and re-programmed irregular-shaped trajectories. Constructed by bonding a twisted liquid crystal elastomer ribbon into a closed-loop ring topology, the robot exhibits three coupled periodic self-motions in response to constant temperature or constant light sources: inside-out flipping, self-spinning around the ring center, and self-orbiting around a point outside the ring. The coupled spinning and orbiting motions share the same direction and period. The spinning or orbiting direction depends on the twisting chirality, while the orbital radius and period are determined by the twisted ring geometry and thermal actuation. The flip-spin and orbiting motions arise from the twisted ring topology and a bonding site defect that breaks the force symmetry, respectively. By utilizing the twisting-encoded autonomous flip-spin-orbit motions, we showcase the robot's potential for intelligently mapping the geometric boundaries of unknown confined spaces, including convex shapes like circles, squares, triangles, and pentagons and concaves shapes with multi-robots, as well as health monitoring of unknown confined spaces with boundary damages.

Hypometria of saccadic eye movements to targets in rapid circular motion.

Saccades to objects moving on a straight trajectory take the velocity of the object into account. However, it is not known whether saccades can compensate for curved trajectories, nor is it known how they are affected by high target speeds. In Experiment 1, participants made a saccade in a delayed saccade task to a target moving in a circular trajectory. Surprisingly, saccades to high-speed moving targets were severely hypometric, with gains of only ∼55% for trajectories of the largest angular speed (2 revolutions per second) and eccentricity (12°). They also had unusually low peak velocities. In Experiment 2, the target jumped along a circular path around a central fixation point. Hypometria was still severe, except for very large jumps. Experiment 3 was like Experiment 1, except that a landmark was positioned on the trajectory of the target, and participants were instructed to make a saccade to the landmark or to its memorized location. This ameliorated hypometria considerably. Given the delayed nature of the tasks of Experiments 1 and 2, participants had considerable time to program a voluntary saccade to a location on the trajectory, if not to the rapidly moving target itself. Nevertheless, the abnormal saccade properties indicate that motor programming was compromised. These results indicate that motor output can be inextricably bound to sensory input to its detriment, even during a highly voluntary motor act; that apparent motion can produce this behavior; and that such abnormal saccades can be "rescued" by the presence of a stable visual goal.

Exact linearization and control of a mobile robot for the inspection of soil resources in Solanum tuberosum crops.

In recent years, the development of robots for agro-industrial applications, such as the cultivation of Solanum tuberosum potatoes, has aroused the interest of the academic and scientific communities. This is due, at least in part, to the complexity of modeling and robustly controlling some dynamics inherent to nonlinear behaviors normally attributed to the different technologies associated with the movement of these autonomous vehicles and their non-holonomic constraints. The different nonlinear dynamics of mobile robots are usually represented by state-space models. However, given some equilibrium and stability characteristics, the implementation of effective controllers for the robust parametric tracking and variation problem requires techniques that allow the operability of robots around regions of stable equilibrium. Feedback linearization control is one such technique that attempts to mathematically eliminate nonlinear expressions from the plant model. However, this technique requires an observable and controllable mathematical model. If there is some relationship between the model inputs and a controlled output that allows the relative degree of the control law to be determined, the controller design and implementation are posed as a linear issue. Flat filters developed from the generalized proportional integral control approach are an alternative that could facilitate the design of controllers for these linearized systems. From these flat filters, it is possible to obtain the transfer function of a controller without relying on the derivatives of the system output. This work proposes the design of a controller via exact linearization and its equivalent flat filter for a robot inspector of the soil resource of S. tuberosum crops in the department of Cundinamarca, Colombia. The actuator motion constraints resulted in a robot with two degrees of mobility and one non-holonomic constraint. Numerical validation of this system suggests that it can be an effective solution to the problem of tracking control at changing references by providing a system capable of navigating through crop rows. The results suggest correct tracking for linear and circular trajectories. However, the control lacks the ability to track spiral-type trajectories.

On trajectory control of magnetized spherical solids driven by magnetic force through soft medium

Manipulation of untethered millimeter-sized devices (bots) inside the human body has many medical applications. Most of the prior work focused on movement of such bots inside fluids, usually at low Reynolds numbers. Yet, many medical procedures are performed within soft tissues. Bot translation in soft materials differs dramatically from their motion in fluid. This paper focuses on trajectory control of small, untethered spheres driven magnetically in soft media commonly used to simulate tissues. While spherical bot shapes offer the advantage of potentially rapid change in the direction of motion, the main challenge in controlling trajectories through soft materials is their nonlinear and history dependent response forces associated with irreversible medium modification. This paper introduces control modules for manipulating spherical bots in soft media along elementary trajectories of circular and straight segments, from which more general trajectories may be assembled. The proposed control is based on a phenomenological model of soft media response forces. Numerical implementation of the proposed trajectory control along circular trajectories is shown to compare well with the results of experimental tests indicating that the accuracy on the order of the bot radius is readily achievable for trajectories whose radii of curvature is on the order of 10 bot radii.

Diverse Time Encoding Strategies Within the Medial Premotor Areas of the Primate.

The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encodes the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represented the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.

An adaptive neuro-fuzzy with nonlinear PID controller design for electric vehicles

In this work, an adaptive neuro-fuzzy (ANF) with a nonlinear proportional integral derivative (NLPID) controller (ANF-NLPID) has been proposed to solve the speed-tracking problem in electric vehicles (EVs) with brushless DC motor (BLDC). The ANF-NLPID controller eliminates the external disturbances caused by environmental or internal issues and uncertainties caused by parameter variations that lead to insufficient speed-tracking performance and increased energy consumption in EVs. An improved particle swarm optimization based on the chaos theory (IPSO-CT) algorithm is introduced to obtain the parameters of the fuzzy logic controller membership function and nonlinear PID controller and present the optimal performance for the EV. Employing the chaos technique with PSO helps to prevent the system from being trapped in the local minimum or optimum problem. The performance of the IPSO-CT algorithm is tested using a numerical comparison with other existing works. The outstanding performance of the ANF-NLPID controller has been evaluated by measuring the speed-tracking performance for the new European driving cycle (NEDC) and circular trajectories. Three case studies have been presented based on measuring the ANF-NLPID controller performance without disturbances, with disturbances, with disturbances, and uncertainties effects, respectively. Furthermore, the ANF-NLPID controller has been employed in different EV models to study the performance of this type of controller. Each of the three cases includes other existing works along with the ANF-NLPID controller to provide an insightful comparison using statistical functions to obtain each controller’s overall objective function value. The other existing works are fuzzy fractional order PID (Fuzzy FOPID), fuzzy integer order PID (Fuzzy IOPID), and integer order PID (IOPID) controllers. A sensitivity analysis has been conducted to test the proposed controller’s ability to present high speed-tracking performance while changing the disturbances and uncertainty rates. The results demonstrate that the ANF-NLPID controller is superior in speed-tracking control regulation for the new European cycle drive (NEDC) and circular speed trajectories and overcomes the external disturbances and uncertainties problem with low error results. In the end, the results reveal that the ANF-NLPID controller is more efficient than the fuzzy FOPID, fuzzy IOPID, and IOPID controllers in each case.

Application of Fuzzy Topsis for Prioritizing Barriers to Circular Economy Adoption in the Automotive Sector: A Study in an Emerging Country

Acknowledging the substantial economic, social, and environmental impacts of sustainability and circular economy (CE) practices, their imperative role in the automotive industry cannot be overstated. Despite this significance, there is a lack of studies addressing these critical themes within the automotive sector. This paper aims to bridge this gap by providing an examination of the barriers hindering the adoption of CE principles, with a specific focus on the Brazilian automotive industry. A survey, involving 41 experts comprising 21 academics specializing in sustainability and CE, 16 experienced managers, and 4 directors with substantial automotive industry expertise, was conducted. The study identified and evaluated 12 barriers to CE adoption in the automotive sector based on the experts’ assessment using Fuzzy TOPSIS. The study's findings underscore the scarcity of professionals with sufficient knowledge and expertise), the absence of supportive public policies, and the inadequate commitment from leadership as the top three priority barriers. The research recommends targeted actions for companies, policymakers, and universities to collaboratively contribute towards overcoming these identified barriers and fostering a sustainable and circular trajectory for the automotive industry.