Model Of Actuator Research Articles

Design, Optimization, and Modeling of a Hydraulic Soft Robot for Chronic Total Occlusions.

Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm's locomotion to assist doctors or operators in actively opening thrombi in coronary or peripheral artery vessels. Firstly, a three-actuator bionic soft robot is developed based on earthworms' physiological structure. The soft robot's locomotion gait inspired by the earthworm's mechanism is designed. Secondly, the influence of structure parameters on actuator deformation, stress, and strain is explored, which can help us determine the soft actuators' optimal structure parameters. Thirdly, the relationship between hydraulic pressure and actuator deformation is investigated by performing finite element analysis using the bidirectional fluid-structure interaction (FSI) method. The kinematic models of the soft actuators are established to provide a valuable reference for the soft actuators' motion control.

Distributed finite-time bearing-based formation control for underactuated surface vessels with Levant differentiator

In this paper, a distributed bearing-based formation control scheme with finite-time convergency is proposed for multiple underactuated surface vessels (USVs). By virtue of the guide point-based model transformation method, the dimension of underactuated tracking error dynamics can be reduced from three to two. This allows us to convert the actuator model to a fully form that matches dimension-reduced tracking error dynamics. Further, to reduce the computation complexity, a finite-time recruited filter is designed according to first-order Levant differentiator. At meanwhile, auxiliary error compensation signals are introduced to address unknowns stemming from filter process and system dynamics. Since merely relative-distances and inner bearings are utilized in the proposed bearing-based formation approaches, the proposed control scheme provides a feasible solution to achieve formation control under body-fixed frame. Finally, theoretical analysis and numerical simulations are presented to demonstrate the efficacy.

Locomotion control of a rigid-soft coupled snake robot in multiple environments

The versatile motion capability of snake robots offers themselves robust adaptability in varieties of challenging environments where traditional robots may be incapacitated. This study reports a novel flexible snake robot featuring a rigid–flexible coupling structure and multiple motion gaits. To better understand the robot’s behavior, a bending model for the soft actuator is established. Furthermore, a dynamic model is developed to map the relationship between the input air pressure and joint torque, which is the model base for controlling the robot effectively. Based on the wave motion generated by the joint coupling direction function in different planes, multiple motion gait planning methods of the snake-like robot are proposed. In order to evaluate the adaptability and maneuverability of the developed snake robot, extensive experiments were conducted in complex environments. The results demonstrate the robot’s effectiveness in navigating through intricate settings, underscoring its potential for applications in various fields.

Research on Precise Tracking Control of Gear-Shifting Actuator for Non-Synchronizer Automatic Mechanical Transmission Based on Sleeve Trajectory Planning

The Non-Synchronizer Automated Mechanical Transmission (NSAMT) demonstrates a straightforward structure and cost-effectiveness; however, the primary obstacle to its widespread application lies in NSAMT shift control. The implementation of active angle alignment effectively addresses the issue of shifting quality, but achieving active angle alignment necessitates precise tracking of the planned shifting curve by the gear-shifting actuator. To tackle the control problem of accurate tracking for NSAMT shift actuators, this paper initially analyzes the structure and shift characteristics of the NSAMT. Based on this analysis, a physical model is established using Amesim, incorporating a drive motor, two-gear NSAMT, shift actuator, sleeve, and DC motor model. An extended state observer (ESO) is designed to mitigate unknown interference within the system. Furthermore, an active angle alignment control algorithm based on “zero speed difference” and “zero angle difference” for double target tracking is constructed while planning the axial motion trajectory of the sleeve. The Backstepping algorithm is employed to successfully track and regulate this planned trajectory. Finally, through Hardware-in-the-Loop testing, we validate our proposed control strategy, which demonstrates consistent results with simulation outcomes, thereby affirming its effectiveness.

BiLSTM-MLP based hysteresis modeling for soft pneumatic joint actuator

Soft pneumatic joint actuators show great potential in applications such as medical machinery, wearable devices, and soft grippers due to their inherent compliance. However, due to the internal friction and periodic relaxation of the elastic materials, the output force of soft pneumatic joint actuators has complex hysteresis characteristics, which seriously affects their control accuracy. To address the asymmetry hysteresis of actuator output force, a neural network model combining a bidirectional long-short-term memory network (BiLSTM) and a multilayer perceptron (MLP) is proposed. The MLP serves as the output layer of the BiLSTM, which is utilized to capture the time dependency of the actuator output force. By applying further nonlinear transformations, the feature representation of the BiLSTM output is retrieved and merged, improving the prediction and generalization capabilities of the model. The experimental results show that the BiLSTM-MLP model has a maximum output force error of only 0.306 N, an average error of less than 0.08 N, and a goodness of fit more than 0.999. Compared with the MLP, LSTM, BiLSTM, and improved PI models, the BiLSTM-MLP model can have higher prediction accuracy, better characterize the hysteresis properties of soft joint actuators, and provides a promising approach for hysteresis modeling of various elastomer actuators.

Electromechanical Coupling Model for Ionic Liquid Gel Soft Actuators

A soft robot is composed of soft materials, which exhibit continuous deformation and driving structure integration and can arbitrarily change shapes and sizes over wide ranges. It shows strong adaptability to unstructured environments and has broad application prospects in military reconnaissance, medical rescues, agricultural production, etc. Soft robots based on ionic electroactive polymers (EAPs) have low-driving voltages, large-actuation displacements, fast responses, light weights, and low powers and have become a hot research field of bionic robots. Ionic liquid gels (ILGs) are new ionic EAPs. In this study, a new soft actuator was designed based on an ILG, and the electromechanical coupling model of an ILG soft actuator was studied in detail. Based on the system transfer function method, a mechatronic coupling model for the soft actuator was developed. According to the material characteristics and current response law of the ILG-containing EAP, an equivalent circuit model was used to describe transfer of the output current and input voltage. Based on the equivalent transformer model for ionic polymer–metal composite (IPMC) actuators proposed by Claudia Bonomo, the electromechanical coupling equation and a driving equation of the ILG soft actuator were established. The least-squares method was used with the coupling model of an ILG soft actuator to identify the system parameters for the model, and the effects of the structural parameters on the end displacement and driving force of the soft actuator were analyzed.

A correlation study on piezo-embedded carbon fibre reinforced polylactic acid composite: Experimental and numerical modelling

In this research work, a piezoelectric sensor and actuator model was designed. Carbon fibre-reinforced polylactic acid (CF/PLA) composites were fabricated using the fused deposition modelling (FDM) technique using many parameters to achieve this goal. For instance, the primary key parameters were 0.1 mm (layer height) and 25 mm/s (print head). Besides, the fabricated samples were subjected to a tensile study. Besides, MATLAB® Partial Differential Equation (PDE) tool was used to develop a finite element analysis (FEA) model for the piezoelectric actuator using the experimentally tested results. The MATLAB® was also used to examine the geometry and tip deflection. The experimental works were carried out to measure the sample’s strain using piezoelectric sensors. This approach could be used to establish the accuracy of the model. The CF/PLA composites were fabricated using 20 wt.% of reinforcements. The experimental results and finite element simulation were good agreement on results. Results reported that the deflections of 6.5765 mm, 5.197 mm, and 7.6328 mm, respectively embedded with PZT 5J, PZT 5H, and PZT 5A.

A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions

This study compared the efficacy of the actuator line and actuator surface models in carrying out large-eddy simulations of a utility-scale wind turbine. A large-eddy simulation with the actuator surface and line models was employed to study the wake flow and power production of the turbine. While both the actuator models were employed for the blade representation, the nacelle was modeled using the actuator surface approach. Both of the actuator models demonstrated agreement in the mean velocity field, power production, and turbulence kinetic energy of the wake flow. Comparing the wake flow, power production, and turbulence kinetic energy results, it was found that the mean discrepancy between the two models was 0.6%, 0.3%, and 2.3%, respectively. Despite the minor discrepancies, both actuator models accurately captured the hub vortex in the wake of the nacelle, evidenced by an energy peak in wind speed spectra at f/fω≈0.34.

Dynamic Modeling and Analysis of Soft Dielectric Elastomer Balloon Actuator with Polymer Chains Crosslinks, Entanglements and Finite Extensibility

Soft dielectric elastomers (SDEs) represent a category of intelligent electroactive materials utilized in electro-mechanical actuation technology. The dynamic performance of these materials during actuation is notably affected by intrinsic factors like crosslinks, entanglements and the limited extensibility of polymer chains. In this paper, we provide a theoretical framework for modeling the dynamic behavior of a balloon actuator made up of soft dielectric elastomer. To account for the inherent characteristics of polymer chain networks, we employ a physics-based nonaffine material model proposed by Davidson and Goulbourne. The governing equation for dynamic motion is established using Euler–Lagrange’s equation of motion for conservative systems. The reported dynamic modeling framework is then utilized to explore the transient response, stability, periodicity and resonance properties of a dielectric elastomer balloon (DEB) actuator for varying levels of polymer chain crosslinks, entanglements and finite extensibility parameters. To assess the periodicity and stability of the nonlinear vibrations exhibited by the DEB actuator, we present Poincaré maps and phase-plane plots. The results demonstrate that changes in the density of polymer chain entanglements lead to transitions between quasi-periodic and aperiodic vibrations. These findings represent an essential initial step toward the design and production of intelligent soft actuators with diverse applications in future technologies.

Direct ink writing of polymer matrix composite with carbon for driving a flexible thermoelectric actuator of shape memory polymer

Carbon nanomaterials and polymer composites that possess excellent electrical and mechanical properties for soft robots have been investigated over decades in multidisciplinary research fields. As considering the incorporation of carbon into polymer composite, several major concerns include the electrical conductivity, elastic module, and manufacturing flexibility that can enable them to satisfy various functions such as actuation and sensing. In this paper, we report a comprehensive study on how to design and fabricate a soft gripper based on carbon polymer matrix composite and multilayer structure through multistep processes of 3D printing on paper. Using commercial conductive additives of graphene and carbon nanotube with polydimethylsiloxane (PDMS), a polymer matrix composite (PMC) was prepared for the ink of direct ink writing (DIW) with percolation conductivity. Additionally, a shape memory polymer (SMP) was utilized for fused deposition modeling (FDM) of a thermal actuator. Incorporating the DIW of PMC with the FDM of SMP on paper, a soft gripper with four fingers was designed and fabricated to show remarkable thermoelectrical actuation for grasping a 50 mm-diameter 10 g-weight spherical ball. In the future, it would provide an alternative approach for the fields of science and engineering, such as nanomaterials and nanotechnology, space applications, sustainable soft robots, and flexible autonomous systems.

Multiphysics Modeling of a Synthetic Jet Actuator in Operation

Active flow control is a promising technology for reducing noise, emissions, and power consumption in various applications. To better understand the performance of synthetic jet actuators, a computational model that couples structural mechanics with electrostatics, pressure acoustics, and fluid dynamics is needed. The model presented here was validated against experimental data and then used to investigate the fluid behavior inside and outside the synthetic jet actuator cavity, the impacts of thermoviscous losses on capturing the acoustic response of the actuator, and the viability of different modeling methods of diaphragms in computational simulations. The results capture the feedback from the fluid onto the diaphragm and highlight the need for careful acoustic modeling.

Modelling of soft fiber-reinforced bending actuators through transfer learning from a machine learning algorithm trained from FEM data

A soft fiber-reinforced bending actuator (SFRBA) is a multi-material system that plays a crucial role in robotics applications due to its high output force and robust bending motion. However, the multi-material composition of SFRBAs causes significant structural nonlinearity. This nonlinear behavior is difficult to capture using traditional analytical models. This study presents a method for modeling the SFRBA using finite element method (FEM) and nonlinear machine learning algorithms (MLAs). First, the key structural parameters of the SFRBA are defined and selected as input variables for the method. An accurate FEM, considering varying actuation pressure, is then employed to generate a simulation training dataset. Subsequently, three nonlinear MLAs, including polynomial regression (PLR), extreme gradient boosting regression (XGBoostR), and normalized multilayer perceptron regression (NMLPR), are developed to model the bending angle of the SFRBA. Moreover, transfer learning is deployed to improve the accuracy and convergence speed of the optimal NMLPR. Experimental measurements are conducted to validate the established MLAs, and the results demonstrate that the refined NMLPR outperforms the other models, yielding an average Root Mean Square Error (RMSE) of 7.935° and Mean Absolute Percentage Error (MAPE) of 6.45%. Furthermore, the refined NMLPR is implemented in a feedback control loop to showcase its real-time ability to convert actuation pressure information into bending angles. The results exhibit excellent control performance, with an average MAPE of less than 6% and a low time delay of 0.0875 s. This work exemplifies a methodology that combines FEM and MLAs for modeling SFRBAs, paving the way for their further development and practical application.

Observer based fault diagnosis of aircraft active landing gear system

A landing gear system is vital in aircraft landing and taxiing. In this paper, an observer-based fault detection and fault reconstruction means is adopted for the aircraft’s active landing gear. Firstly, a six-degree-of-freedom (6-DOF) landing gear model is established by analysing the dynamics of the fuselage and landing gears. By analysing the fault mechanism of actuators and sensors, the fault model of actuators and sensors is established. Secondly, according to the above model, the unknown input observer (UIO) is designed to obtain the residuals, and the fault detection of actuators and sensors is realized according to the comparison between residuals and thresholds. On this basis, an adaptive unknown input observer (AUIO) is designed, through which the state values and fault values can be reconstructed. Finally, simulation experiments are tested under different fault types to prove the validity of the fault detection and reconstruction based on UIO and AUIO.

Modeling and Control of a Linear Piezoelectric Actuator

To improve the output displacement of piezoelectric actuators, a linear piezoelectric actuator based on a multistage amplifying mechanism with a small volume, large thrust, high resolution, high precision, and fast response speed is proposed. However, inherent nonlinear characteristics, such as hysteresis and creep, significantly affect the output accuracy of piezoelectric actuators and may cause system instability. Therefore, a complex nonlinear hysteresis mathematical model with a high degree of fit was established. A Play operator was introduced into the backpropagation neural network, and a genetic algorithm (GA) was used to reduce the probability of the fitting of the neural network model falling into a local minimum. Moreover, simulation and experimental test platforms were constructed. The results showed that the maximum displacement of the actuator was 558.3 μm under a driving voltage of 150 V and a driving frequency of 1 Hz. The complex GA-BP neural network model of the piezoelectric actuator not only exhibited high modeling accuracy but also solved the problems of strong randomness and slow convergence. Compared with other control algorithms, the GA-BP fuzzy PID control exhibited higher control precision.

Structure design and advantage research for bidirectional synchronous force-increasing EMB actuator

Electro-Mechanical Brake (EMB) can provide an ideal brake actuator for the active braking system of intelligent vehicles and the decoupled regenerative braking system of new energy vehicles. In order to solve the problem of large volume, weight, and axial size of the existing EMB actuator, a novel bidirectional synchronous force-increasing EMB (BSF-EMB) actuator scheme is proposed. Based on the maximum required braking force of the target vehicle under emergency braking conditions and the limitation of installation space in the wheel hub. The rotary motor and the ball screw are selected, the force-increasing mechanism parameters calculation and structure design are completed. In order to minimize the difference between the force-increasing ratio of the two-stage force-increasing mechanism and the lever force-increasing mechanism. The parameters of the force-increasing mechanism are optimized based on the weight adaptive particle swarm optimization algorithm. The three-dimensional model of the EMB actuator is established. In addition, when the required braking force is the same, the mass and volume of the BSF-EMB actuator can be decreased by about 43.4% and 55.8%, compared with the existing planetary gear force-increasing EMB (PGF-EMB) actuator scheme. Therefore, the BSF-EMB actuator can effectively decrease the unsprung mass of the vehicle and resolve the issue of limited installation space in the wheel hub of compact vehicles. The EMB models for two EMB actuator structures are built based on MATLAB/Simulink, and the EMB braking response speed and tracking performance of braking force are compared. The simulation results show that the braking response speed of the BSF-EMB actuator can be increased by 11%, 10.6%, 12.7%, and 14% compared to the PGF-EMB actuator under emergence braking condition and other three general service braking conditions, and the braking force adjustment is more precise. Finally, the effectiveness for the control strategy is verified by hardware in loop (HIL) experiment under sin wave input condition for braking force. The related research can provide reference for the design and application of EMB.

Toward Smart, Automated Junctional Tourniquets-AI Models to Interpret Vessel Occlusion at Physiological Pressure Points.

Hemorrhage is the leading cause of preventable death in both civilian and military medicine. Junctional hemorrhages are especially difficult to manage since traditional tourniquet placement is often not possible. Ultrasound can be used to visualize and guide the caretaker to apply pressure at physiological pressure points to stop hemorrhage. However, this process is technically challenging, requiring the vessel to be properly positioned over rigid boney surfaces and applying sufficient pressure to maintain proper occlusion. As a first step toward automating this life-saving intervention, we demonstrate an artificial intelligence algorithm that classifies a vessel as patent or occluded, which can guide a user to apply the appropriate pressure required to stop flow. Neural network models were trained using images captured from a custom tissue-mimicking phantom and an ex vivo swine model of the inguinal region, as pressure was applied using an ultrasound probe with and without color Doppler overlays. Using these images, we developed an image classification algorithm suitable for the determination of patency or occlusion in an ultrasound image containing color Doppler overlay. Separate AI models for both test platforms were able to accurately detect occlusion status in test-image sets to more than 93% accuracy. In conclusion, this methodology can be utilized for guiding and monitoring proper vessel occlusion, which, when combined with automated actuation and other AI models, can allow for automated junctional tourniquet application.

Initial flight test verification of software and hardware in the loop simulations of the flight stabilization system

PurposeThis paper aims to present assessment of models and simulation results used in the development process of flight stabilisation system that uses trim tabs for PZL-130 Orlik turboprop military trainer aircraft. Flight test of the system allowed to compare software and hardware simulation results with real flight recordings.Design/methodology/approachProposed flight stabilisation system was developed using modern techniques of model-based design, automatic code generation, software and hardware in the loop testing. The project reached flight testing stage which allowed to gather data to verify models and simulation results and asses their quality.FindingsResults of the comparison showed that the trim tab actuator model used in simulation can be improved by adding play. This reduced the difference between simulation and real flight system output – actuator angle. The influence of airloads on the flying actuator angle compared to hardware in the loop simulation in lab is less than ± 0.6°.Originality/valueProposed flight stabilisation system that uses trim tabs has several benefits over classic automatic flight system in terms of weight, energy consumption and structure simplicity and does not need aircraft primary control modification. It was developed using modern techniques of model-based design, automatic code generation and hardware in the loop simulations.

Optimal control for quadrotors during inspection of power utility assets

Renewable energy and power utilities inspection by autonomous aircraft enables rapid and effective risk-free assessment of the state of systems, and provides a qualitative and accurate assessment of defects and damages. To realize maximum operational benefits of aerial inspections, effective controls for autonomous aircraft must be ensured and the system should be operated in an optimal policy. Hence, the objective of this paper is to consider optimal control strategies for a quadrotor helicopter type UAV. Based on some structural properties of the considered system, in particular the flatness property, we suggest a control strategy that ensures tracking a time parameterized path that connects two given points in the state space while minimizing the energy consumption. The proposed controller enables longer-endurance missions for the quadrotor and effective supervision and inspection of large energy systems and power plants. In this paper the analysis of the control law takes into consideration the highly nonlinear dynamic model of the quadrotor and the electrical actuator model. The current approach in solving the optimal control problem under consideration allows one to eliminate the differential equation and to reformulate the optimal control problem to a nonlinear dynamic programming problem. The approach can make monitoring operations of renewable energy plants by aerial vehicles, more efficient.

Integrated Intelligent Educational Environment – Opportunities for STEM Education

The paper reviews the technology integration in STEM education within the scope of an Integrated Intelligent Educational Environment (IIEE). A conceptual model of such an environment is suggested. The model consists of an Intelligent Educational System that communicates through a gateway with sensors and actuators within the integrated environment. A possible usage of different technology devices within IIEE regarding STEM education is proposed. A common information model for both sensors and actuators is presented. A custom packet-based communication protocol is designed to support multiple wired and wireless communication media. IIEEs that include various technological devices provide an explorative and engaging context for STEM education. Toolkits for projects on engineering and technology can be prepared and play an active role in STEM classrooms.

Dynamic Modeling of a Fluidic Soft Actuator: First Results Within a Fractional Approach

Dynamic modeling of soft actuators is a challenging field of research mainly due to the nonlinear properties of the materials they are made of, as well as the infinite degrees of freedom that they exhibit. In this paper, the defection of an eccentric soft fluidic actuator is characterized in terms of the dynamic displacement using both integer and fractional order (FO) models. The actuator, which is cylindrical in shape, is made of a silicone polymer called polydimethylsiloxane (PDMS) from a water-soluble mold and a rod that, when placed eccentrically, allows to create the internal chamber of the actuator. Experimental results are presented to show that the best fitting is obtained with FO models. In fact, the dynamics of the actuator can be fully described with a two-parameter model, namely a fractional integrator of order of about 1.2 with a gain.