Actuator Dynamics Research Articles

Modeling and simulation of magnetostrictive actuators based on ΔE effect Preisach model

Based on the classical Preisach model, combined with the magneto-mechanical coupling effect of Giant magnetostrictive materials (GMM), this paper introduces the Everett function to optimize the classical Preisach hysteresis model and improve its accuracy. By importing dynamic parameters, the dynamic Preisach hysteresis model is established. Combined with the constitutive model of GMM, a dynamic Preisach hysteretic nonlinear magnetostrictive actuator model based on the ΔE effect is established. Then, the finite element simulation is carried out by Comsol software and compared with the theoretical model simulation. The results show that the error between the magnetostrictive strain of the established hysteresis model and the finite element simulation results is less than 100 ppm, which verifies the accuracy of the proposed model. Finally, the curves of magnetic field intensity, magnetic induction intensity, magnetization, magnetostrictive strain and ΔE effect of GMA are obtained by using this model.

A Novel Attitude Control Strategy for a Quadrotor Drone with Actuator Dynamics Based on a High-Order Sliding Mode Disturbance Observer

In the attitude control of quadrotor drones, it is necessary to cope with matched and unmatched disturbances caused by nonlinear couplings, model uncertainties, and external disturbances, as well as to consider the effects caused by actuator dynamics. Aiming to accurately track desired trajectories under the above factors, a novel control strategy is proposed by combining a state feedback control with a high-order sliding mode disturbance observer (HOSMDO). The HOSMDO is motivated by the higher-order sliding mode (HOSM) differentiator and extended state observer (ESO) technique, allowing for the exact robust estimation of disturbances and their arbitrary order derivatives in finite time. Unlike the control schemes based on back-stepping methods, the proposed controller is designed with a holistic mindset. Specifically, a baseline feedback framework is constructed firstly, and the disturbances and relevant derivatives required for the baseline framework are then generated by the HOSMDOs to obtain the overall control scheme. The stability conditions of the controllers designed with and without considering the actuator dynamics are analyzed separately. In the latter case, the actuator dynamics imposed additional constraints on the control parameters. Numerical simulations validate the effectiveness of the proposed control strategy.

Event‐triggered based finite‐frequency control for vehicle electrohydraulic suspension with force tracking

AbstractThis study investigates the problem of event‐triggered based finite‐frequency control for vehicle electrohydraulic suspensions with force tracking. A novel hierarchical control methodology is proposed by designing event‐triggered finite frequency and active force tracking controllers to improve the suspension performance. In practical application, active suspension system can be constructed as the network control system under consideration of the electrohydraulic actuator's nonlinear dynamics and parametric uncertainties, and in‐vehicle network delay in a unified framework. Then, due to the more sensitiveness of the human body to vertical vibrations in 4–8 Hz and limited in‐vehicle network communication resource, an event‐triggered finite frequency controller is developed based on the generalized KYP lemma and Lyapunov stability theory. The triggered condition is designed for the network control system with in‐vehicle network delay. Other physical constraints including suspension working space, tire dynamic load and actuator saturation are also introduced in this controller design. It can generate the target force to satisfy suspension performance requirements under each triggered instant period. Furthermore, since the nonlinearity and uncertainty always exist in the electrohydraulic actuator, a filter‐based adaptive sliding mode control method is employed to design the active force tracking controller. It can precisely drive electrohydraulic actuator to track the target constant force generated by event‐triggered finite frequency controller. Finally, the results validate the effectiveness and saving communication resource capability of the proposed control methodology.

Dynamic performance prediction and experimental analysis of wet clutch actuator considering thermal flow characteristics

The hydraulic actuator system (HAS) for wet clutches in heavy-duty vehicle transmissions is required to have a fast response and high precision in the pressure regulation procedure. Conventional pressure control valves for HAS are almost slide spool structures, which perform a large flow force at a high flow rate. An open-center spool structure is designed and developed in this paper, which is a combination of a traditional slide spool and a valve sleeve. It has an orifice-groove combination throttling orifice, which can take into account the large through-flow capacity and small flow force. Firstly, to deeply understand the mechanism of pressure variation in the clutch chamber, a high-fidelity dynamic characteristic mathematical model of HAS considering the oil temperature is proposed. Secondly, the functional relationship between the oil temperature on the medium physical property parameters and the orifice thermal flow parameters in the model is deduced in detail. An experimental bench to measure the pressure valve dynamic performance and actuator pressure regulation characteristics in a wide temperature domain is then designed and implemented to validate the accuracy of the simulation model. Finally, the mechanisms of oil temperature and system pressure on pressure impact and pressure response are quantitatively analyzed in association with a supervised learning algorithm. The feasible domains of the two adjustable variables are also explored. This study provides a new perspective on dynamic control and energy saving of HAS pressure valves and a new method for the prediction of HAS performance under complicated operating conditions.

Research on Compliance Control of Electro-Hydraulic Loading Experimental System

This article discusses the challenges in preventing workpiece damage due to impacts in electro-hydraulic loading systems, especially in unknown environments. We propose an innovative compliance control strategy, synergizing a series elastic actuator with impedance control to significantly mitigate impact forces between the mechanism and test workpieces. The controller consists of two loops: an internal loop and an outer loop. The internal loop integrates a position loop utilizing a radial basis function observer within a backstepping control framework, effectively countering the nonlinear dynamics of hydraulic actuators and ensuring precise trajectory tracking. The outer loop advances traditional impedance control by adaptively modifying the damping coefficient, resulting in a straightforward and easily implementable damping control law. For the unknown environment parameters, our system employs a parameter estimation law to estimate the unknown environmental stiffness and position parameters. The effectiveness of this strategy has been verified through comparative simulation with traditional impedance control, indicating that the proposed method can not only effectively reduce contact shock in unknown environments, improve response speed, and reduce overshoot, but also improve steady-state accuracy. We provided a feasible control scheme for similar systems to ensure precise and safe operation.

Resilient coordination of multi-agent systems in the presence of unknown heterogeneous actuation efficiency and coupled dynamics: distributed approaches

To guarantee the stability and performance of an overall heterogeneous multi-agent system, feedback control structures must be capable of addressing the presence of heterogeneous agent-based nonlinear uncertainties, unknown actuation performance, and coupling effects. Additionally, some tasks require agents to track the leader's state and reach different states in a distributed way. Therefore, this paper proposes a distributed adaptive controller that drives a set of agents to user-assigned positions in the presence of the mentioned heterogeneous system anomalies. To address actuator dynamics, a hedging-based reference model is used to decouple adaptive updating from the actuator dynamics. To deal with the coupled dynamics, an observer-based estimation algorithm is proposed. Finally, the low-frequency learning method is used to deal with the high-frequency control response and, therefore, to obtain a better transient performance. The overall closed-loop system's stability is investigated using the Lyapunov Stability Theory, and the Linear Matrix Inequalities (LMI) technique is employed to identify stability limits regarding the actuator bandwidths of each agent. Illustrative numerical examples are presented to demonstrate the designed controller's performance in a heterogeneous uncertain multi-agent system's dynamics with unknown actuation capabilities and coupled dynamics.

Path-Following Sliding Mode Controller for an Electric Vehicle Considering Actuator Dynamics

This study introduced a novel path-following controller tailored to electric vehicles equipped with a steer-by-wire system, i.e., the steering angle of the vehicle was defined by an electrical actuator. The control objective was to force the proper steering angle of the vehicle, which permits following a desired path. The system presupposed that an external algorithm that utilized sensor data provided the lateral movement references while maintaining a steady longitudinal velocity for the vehicle. The proposed control scheme was based on a robust sliding mode steering controller to manage the vehicle’s lateral movement. Furthermore, a brushless DC (BLDC) motor was considered as the steering actuator, which was controlled by a field-oriented controller (FOC), which was based on four internal proportional–integral (PI) control loops for precise steering actuation. To assess the performance of the proposed control scheme, numerical simulations were obtained, which demonstrated its effectiveness in achieving the control objective.

Adaptive stabilization for a class of wave equations with uncertain nonlinear boundary actuator dynamics

This paper investigates the stabilization of a wave equation with uncertain boundary actuator dynamics. The remarkable characters of the system under investigation are revealed by the essential nonlinearities involved in the boundary actuator and the serious parametric unknowns coming from anti-damping coefficient at uncontrolled boundary and those in the actuator, which result into the incapability of the traditional control methods on this topic. For this, a novel adaptive control strategy is proposed in this paper. Specifically, a Riemann variables based state transformation is first introduced to change the original system into a new one whose stabilization implies that of the original system. Then, a state-feedback controller joint with some adaptive laws which are smartly chosen for the compensation of unknown parameters is explicitly designed by a finite-dimensional backstepping procedure. Owing to the compensation of boundary actuator dynamics, the performance analysis of the closed-loop system is more complicated than that of the related literature. For this, a rigorous recursive step is given to show the stability of the resulting closed-loop system. Finally, a numerical example is provided to verify the effectiveness of the proposed theoretical results.

A Novel Distributed Adaptive Controller for Multi-Agent Systems with Double-Integrator Dynamics: A Hedging-Based Approach

In this paper, we focus on designing a model reference adaptive control-based distributed control law to drive a set of agents with double-integrator dynamics in a leader–follower fashion in the presence of system anomalies such as agent-based uncertainties, unknown control effectiveness, and actuator dynamics. In particular, we introduce a novel hedging-based reference model with second-order dynamics to allow an adaptation in the presence of actuator dynamics. We show the stability of the overall closed-loop multi-agent system by utilizing the Lyapunov Stability Theory, where we analyze the stability condition by using the Linear Matrix Inequalities method to show the boundedness of the reference model and actuator states. Finally, we illustrate the efficacy of the proposed distributed adaptive controller on an undirected and connected line graph in five cases.

Prescribed‐time constrained tracking control of a class of 2 × 2 hyperbolic PDE systems with actuator dynamics

AbstractThis article studies the problem of prescribed‐time constrained tracking control for a class of hyperbolic partial differential equation (PDE) systems with actuator dynamics, which are described by a set of nonlinear ordinary differential equations (ODEs). Since the control input only appears in the ODE subsystem rather than directly on the boundary of PDE subsystem, the control task becomes quite challenging. The most important is that for the control of such ODE controlled PDE systems we mainly make the following two contributions: (1) the controlled output of the PDE system tracks the reference signal within the prescribed time; (2) the controlled output and all the actuator states are constrained. It is the first time that such a prescribed‐time constrained tracking control problem is addressed for the PDE‐ODE coupled system considered in this article. Through rigorous theoretical proof, it is demonstrated that all the system states and control signals are bounded and sufficiently continuous by configuring appropriate design parameters. Finally, the performance is investigated via numerical simulation.

A low-cost electrowetting on dielectric semi-continuous pump for application to microfluidic reconfigurable devices

An electrowetting on dielectric (EWOD) pump is a microfluidic pump that uses electrowetting to manipulate liquid droplets in a channel, offering an alternative approach to traditional mechanical pumps. EWOD-based pumps have significant potential for various microfluidic applications. For instance, by integrating microfluidic pumps with a radio frequency (RF) device, it is possible to create a microfluidic reconfigurable RF device. However, the current microfluidic-based devices have been primarily designed based on mechanical micropumps which require expensive clean-room fabrication methods. Here, we present an analytical model for an EWOD semi-continuous pump that can offer a promising alternative actuation for microfluidic actuation. However, a literature survey of recent advances in EWOD pumping has highlighted a gap in the modeling of the relationship between the fluid mechanics and the actuation dynamics. This paper presents an analytical model of an EWOD pump that determines the flow rate and pressure generated by taking into account the competing electrowetting force, friction force, and fluid inertia force in a one-degree-of-freedom channel. The analytical model is valuable for designing and optimizing EWOD-based pumps, as it provides insights into the dominant physical processes and could enable better control. The model is validated with an EWOD experiment and the data demonstrates less than a 6 % error between the measured and predicted maximum droplet velocity and a maximum 7.4 % error in the EWOD pump static pressure.

A Flexible MATLAB/Simulink Simulator for Robotic Floating-base Systems in Contact with the Ground: Theoretical Background and Implementation Details

This paper presents an open-source MATLAB/Simulink physics simulator for rigid-body articulated systems, including manipulators and floating-base robots. Thanks to MATLAB/Simulink features like MATLAB system classes and Simulink Function blocks, the presented simulator combines a programmatic and block-based approach, resulting in a flexible design in the sense that different parts, including its physics engine, robot-ground interaction model, and state evolution algorithm are simply accessible and editable. Moreover, through the use of Simulink dynamic mask blocks, the proposed simulator supports robot models integrating open-chain and closed-chain kinematics with any desired number of links interacting with the ground. This simulator can also integrate second-order actuator dynamics. Furthermore, the simulator benefits from a one-line installation and an easy-to-use Simulink interface.

Implementation of real-time hybrid simulation using a large shake table with onboard actuators

In recent decades, shake table real-time hybrid simulation (RTHS) has emerged as a promising seismic testing approach for complex engineering structures. However, the current shake table RTHS systems with actuators typically install the dynamic actuators on a reaction wall outside the table, which introduce interaction issues between the dynamic actuators and the shake table. This study proposes a potential improvement by developing a shake table RTHS platform with onboard actuators. The platform incorporates a 6 m × 9 m large-scale shake table where the physical substructure, two dynamic actuators, and the reaction frame are all positioned. To validate the effectiveness of the developed platform, a two-story steel frame is tested by both full structure shake table test and substructure shake table RTHS. In the shake table RTHS, the lower part of the frame serves as the physical substructure and is simultaneously loaded by the shake table and dynamic actuators, while the upper part is numerically analyzed in OpenSees, using OpenFresco and Simulink as intermediate softwares. The test results demonstrate that the developed shake table RTHS platform provides reasonable predictions to the structural seismic responses. In addition, time delay is optimized using both inner and outer loop compensators, highlighting the effectiveness of inverse compensation and adaptive time series (ATS) compensation schemes. This paper successfully develops a shake table RTHS platform using a large shake table with onboard dynamic actuators, providing a valuable seismic testing platform for RTHS of large-scale complex engineering structures.

Computational design of ultra-robust strain sensors for soft robot perception and autonomy

Compliant strain sensors are crucial for soft robots’ perception and autonomy. However, their deformable bodies and dynamic actuation pose challenges in predictive sensor manufacturing and long-term robustness. This necessitates accurate sensor modelling and well-controlled sensor structural changes under strain. Here, we present a computational sensor design featuring a programmed crack array within micro-crumples strategy. By controlling the user-defined structure, the sensing performance becomes highly tunable and can be accurately modelled by physical models. Moreover, they maintain robust responsiveness under various demanding conditions including noise interruptions (50% strain), intermittent cyclic loadings (100,000 cycles), and dynamic frequencies (0–23 Hz), satisfying soft robots of diverse scaling from macro to micro. Finally, machine intelligence is applied to a sensor-integrated origami robot, enabling robotic trajectory prediction (<4% error) and topographical altitude awareness (<10% error). This strategy holds promise for advancing soft robotic capabilities in exploration, rescue operations, and swarming behaviors in complex environments.

Neural network adaptive control for turbo‐generator of power systems with prescribed performance and unknown asymmetric actuator dead zone

AbstractThis paper investigates a neural network adaptive controller design method for turbo‐generator of power systems with external disturbance, unknown system dynamic, prescribed performance, and unknown actuator dead zone. First, the unknown system dynamic is estimated and overcome through a neural network. Using the implicit function theorem, the unknown asymmetric dead‐zone behavior of the actuator is overcome by another static neural network. Second, the external disturbance and the reconstruction error of neural networks are handled by a robust term updated online. Moreover, there is no requirement to pre‐know or off‐line estimate the reconstruction error of neural networks and the upper bound of the system external disturbance. Third, based on Lyapunov theory, the smooth control law is proposed. In the meantime, the uniform ultimate boundedness of the networks weights is strictly proved. Furthermore, the system state error satisfies the prescribed transient performance and can converge to a small neighborhood around zero. Finally, a numerical simulation shows the effectiveness of the proposed method.

Dynamic braille display based on surface-structured PVC gel

Braille displays are a class of human–computer interaction electromechanical devices that display dynamic braille through an array of actuators. However, existing actuators for braille displays suffer from issues such as bulky size, heavy weight, and small tactile displacement, leading to difficulties in improving their resolution and readability. To address the above issues, we developed a novel electroactive artificial muscle actuator and applied it to braille displays. The novel actuator consists of a surface-structured PVC gel and planar electrodes. To investigate the effect of surface structure on the performance of novel PVC gel actuators, four types of surface-structured PVC gels were fabricated by a casting process, and their actuation performance was tested. The results show that the conical and frustum conical array structures are more favorable for improving the displacement of novel PVC gel actuators, while the cylindrical and quadrangular array structures are more favorable for improving their recovery forces. We observed both surface structure and dynamic electrical actuation, suggesting that the actuation of the novel actuator is mainly caused by the deformation of the surface structure of the array. We also analyzed electrowetting effects in PVC gels using the Lippmann–Young equation, to explain the differences in the performance of surface-structured PVC gels with different contact angles. Moreover, six multilayer actuators composed of PVC gels with a conical surface array structure are applied to the braille display unit to display the braille digits from 0 to 9. It has been shown that the novel PVC gel actuator has excellent mechanical properties, which makes it an ideal solution for braille displays.

Adaptive control of BLDC driven robot manipulators in task space

AbstractIn this study, task space tracking control of robot manipulators driven by brushless DC (BLDC) motors is considered. Dynamics of actuators are taken into account and the entire electromechanical system (i.e. kinematic, dynamic, and electrical models) is assumed to include parametric/structured uncertainties. A novel adaptive controller is designed and the stability of the closed loop system is ensured via novel Lyapunov type tools. To demonstrate performance and applicability of the proposed method, a simulation study is conducted using the model of a two degree of freedom, planar robotic manipulator driven by BLDC motors.

Adaptive Neural Tracking Control of a Class of Hyperbolic PDE With Uncertain Actuator Dynamics.

This article investigates the adaptive neural tracking control problem for a class of hyperbolic PDE with boundary actuator dynamics described by a set of nonlinear ordinary differential equations (ODEs). Particularly, the control input appears in the ODE subsystem with unknown nonlinearities requiring to be estimated and compensated, which makes the control task rather difficult. It is the first time to consider tracking control of such a class of systems, rendering our contributions essentially different from the existing literature that merely focus on the stabilization problem. By formulating a virtual exosystem to generate a reference trajectory, we propose a novel design of the adaptive geometric controller for the considered system where neural networks (NNs) are employed to approximately estimate nonlinearities, and finite and infinite-dimensional backstepping techniques are leveraged. Moreover, rigorously theoretical proofs based on the Lyapunov theory are provided to analyze the stability of the closed-loop system. Finally, we illustrate the results through two numerical simulations.

Deep reinforcement learning‐based active mass driver decoupled control framework considering control–structure interaction effects

AbstractControl–structure interaction (CSI) plays a significant role in active control systems. Popular methods incorporate actuator dynamics into an integrated control system to account for CSI, leading to a situation where existing structural control algorithms that ignore CSI cannot be applied directly. To address this issue, this study proposes a deep reinforcement learning (DRL) based active mass driver (AMD) decoupled control framework, in which a structural control algorithm is employed to generate the control force command without consideration of CSI, while a DRL agent is utilized to attenuate the CSI effects of AMD systems and achieve a desired control force. The DRL‐based AMD control framework is verified through a series of numerical experiments. Furthermore, the applicability of the control framework is confirmed in a wind‐excited 76‐story benchmark building. Comprehensive analysis indicates that the proposed control framework can effectively eliminate the CSI effects and apply accurate control force to the structure in various scenarios, which allows for an ideal structural response control.

Study of the effects of fractional order and damping coefficient on the dynamics of giant magnetostrictive actuators

Study of the effects of fractional order and damping coefficient on the dynamics of giant magnetostrictive actuators