Control Actuators Research Articles

A three-stage plasma model based on one-way coupling of plasma dynamics, ionic motion, and fluid flow: Application to DBD plasma actuators

The scope of this paper is to present a comprehensive approach for simulating low-temperature atmospheric dielectric barrier discharge plasmas. The proposed methodology categorizes the primary physical phenomena: (i) discharge dynamics, (ii) ionic motion, and (iii) fluid flow, according to their respective time scales and simulates each independently. This allows for the use of distinct solution procedures tailored to each of the three stages of the problem. Such separation offers significant flexibility in choosing appropriate models and numerical schemes for each stage, enabling the simulation of complex geometries and large-scale applications without the excessive computational costs associated with a monolithic approach. As a case study, we apply the proposed algorithm to the surface dielectric barrier discharge plasma actuator for flow control, which is powered by alternating high voltages. The algorithm successfully described the actuator’s behavior while maintaining low computational cost. Additionally, a parametric study is conducted to examine the effect of key input parameters on the generated electrohydrodynamic force and the resulting velocity. Finally, an overall assessment of the three-stage model is provided, highlighting its efficiency and accuracy.

The elastic frontier: Dielectric elastomer actuators in healthcare technology

Abstract Dielectric elastomer actuators (DEAs) have emerged as a groundbreaking technology in the field of medical applications, offering unique advantages such as
high flexibility, low weight, and excellent biocompatibility. This review provides a comprehensive examination of the latest advancements in DEAs, highlighting their potential to revolutionize various medical devices and applications. We explore the fundamental principles of DEA operation, including the electro-mechanical coupling that enables their functionality. Key application areas discussed among others include biomedical devices, rehabilitation tools, and in-vivo implants, where DEAs replicate natural muscle movements, enabling precise and controllable actuation. Additionally, wearable health monitors benefit from their flexibility and high sensitivity. In addition, we address the challenges facing the widespread adoption of DEAs in the medical field, such as material durability, power consumption, and integration with existing medical technologies. By synthesizing current research and identifying future directions, this review underscores the transformative impact of dielectric elastomer actuators on the development of next-generation medical devices.

Predefined-time control for spacecraft rendezvous maneuver with quantized input

PurposeThe purpose of this paper is to solve the problem of adaptive predefined-time control for spacecraft rendezvous maneuver with input quantization and unknown parameters.Design/methodology/approachA significant error-shifting function is established to ensure that the limitation of the initial condition can be ignored. Then, a combination of neural networks method and minimum-learning-parameter method is used to mitigate the adverse effects caused by nonlinear system dynamics. An input quantization method is applied to improved efficiency of data communication between controller and actuator in rendezvous maneuver control system.FindingsThe simulation results verify the correctness and effectiveness of the designed control strategy which can effectively overcome the disadvantages caused by coupling nonlinear system dynamics.Originality/valueThis paper designs an adaptive predefined-time control method for spacecraft rendezvous maneuver control with input quantization based on backstepping control method.

A practical and online trajectory planner for autonomous ships’ berthing, incorporating speed control

Abstract Autonomous ships are designed and equipped to perceive their internal and external environments and subsequently take appropriate actions based on predefined objective(s) without human intervention. Consequently, trajectory-planning algorithms for autonomous berthing must consider factors such as system dynamics, ship actuators, environmental disturbances, and operational safety. In this study, trajectory planning for an autonomous ship was modeled as an optimal control problem (OCP), which was transcribed into a nonlinear programming problem (NLP) using direct multiple shooting. To enhance berthing safety, wind disturbances, speed control guidelines, actuator limitations, and collision avoidance features were incorporated as constraints in the NLP, which was then solved using the sequential quadratic programming (SQP) algorithm in MATLAB. Finally, the performance of the proposed planner was evaluated through (i) comparison with an existing method, (ii) trajectory planning for different harbor entry and berth approach scenarios, and (iii) a feasibility study using predefined as well as stochastically generated initial conditions. The simulation results indicate improved berthing safety as well as practical and computational feasibility.

Stabilizing a Bio-Inspired Rotating Empennage Fighter Aircraft in Multiple Trim Scenarios

This paper considers the problem of stabilizing a bio-inspired fighter aircraft at its Air Combat Maneuver Condition in steady-level and coordinated-turning flight. The aircraft equations of motion are linearized, and an infinite-horizon linear quadratic regulator design is conducted. The open-loop system is unstable in the short-period and Dutch roll modes. This is mitigated in the closed-loop system, which is analyzed in the time and frequency domains. Included in the simulation dynamics are first-order actuator models, actuator deflection limits, and actuator rate limits. These are particularly important for this bio-inspired aircraft because control actuation requires rotation of the empennage, which has relatively large inertia. Simulation responses to initial condition dispersions, aerodynamic model error, and atmospheric turbulence are analyzed to characterize time-domain properties: settling time, region of attraction, control saturation, and robustness. Due to poor singular values for the throttle setting and rotating tail inputs, analysis is dedicated to control designs with these inputs fixed at trim values. Within the scope of these analyses, fixing the rotating tail at trim does not significantly degrade system performance.

4D-printed programmable sample-/eluent-actuated solid-phase extraction device for trace metal analysis.

To integrate valves, manifolds, and solid-phase extraction (SPE) columns into a compact device is technically difficult. Four-dimensional printing (4DP) technologies, employing stimuli-responsive materials in three-dimensional printing (3DP), are revolutionizing the fabrication, functionality, and applicability of stimuli-responsive analytical devices that can show time-dependent shape programming to enable more complex geometric designs and functions. However, 4D-printed stimuli-responsive actuators and valves utilized to control flowing streams in SPE applications remain rare. The tunable stimuli-responsive 4D-printed flow control actuators and valves with the capability of the programmable actuation can be used to manipulate flowing streams and simplify the automation of a conventional SPE scheme. We employed digital light processing three-dimensional printing (3DP), bisphenol A ethoxylate dimethacrylate-based photocurable resins, and 2-carboxyethyl acrylate (CEA)-incorporated flexible photocurable resins to fabricate an SPE column positioned between two [H+]-responsive flow-actuated needle valves. The two valves sequentially close after loading an alkaline sample (pH>pKa of CEA) due to swelling of the stem. Subsequently, they sequentially open upon loading an acidic eluent (pH<pKa of CEA; deswelling of the stem). The optimized device enabled a semi-automatic SPE scheme for Mn, Co, Ni, Cu, Zn, Cd, and Pb ions and showed competitive performance when coupled with inductively coupled plasma mass spectrometry-with the method detection limits ranging from 0.5 to 5.9ngL-1. We validated the reliability and applicability of this method by analyzing the metal ions in reference materials (CASS-4, SLRS-5, 1643f, and Trace Elements Urine L-2) and spike analyses of natural water and human urine samples. To the best of our knowledge, our device is the first demonstration of an SPE scheme performed by the programmable actuation of 4D-printed stimuli-responsive flow control valves, highlighting the analytical applicability of the tunable stimuli-responsive 4D-printed parts and the promising capability of 4DP technologies in advancing conventional sample pretreatment devices.

Stabilization of a cyclic network of strings by nodal control

We consider a network of coupled strings that contains a cycle. We show that boundary feedback stabilization that uses only data of the state at boundary nodes that are not contained in the cycle is in general impossible. We demonstrate that also with control actuators that act at the interior nodes contained in the cycle with certain standard control laws that use only Neumann control action the situation does not improve and the system is still not stable. We prove that with an actuator that uses also Dirichlet control action and is located within the cycle, exponential stabilization is possible.

Enhanced Control of Nonlinear Systems Under Control Input Constraints and Faults: A Neural Network-Based Integral Fuzzy Sliding Mode Approach.

Many existing control techniques proposed in the literature tend to overlook faults and physical limitations in the systems, which significantly restricts their applicability to practical, real-world systems. Consequently, there is an urgent necessity to advance the control and synchronization of such systems in real-world scenarios, specifically when faced with the challenges posed by faults and physical limitations in their control actuators. Motivated by this, our study unveils an innovative control approach that combines a neural network-based sliding mode algorithm with fuzzy logic systems to handle nonlinear systems. This proposed controller is further enhanced with an intelligent observer that takes into account potential faults and limitations in the control actuator, and it integrates a fuzzy logic engine to regulate its operations, thus reducing system chatter and increasing its adaptability. This strategy enables the system to maintain regulation in the face of control input constraints and faults and ensures that the closed-loop system will achieve convergence within a finite-time frame. The detailed explanation of the control design confirms its finite-time stability. The robust performance of the proposed controller applied to autonomous and non-autonomous systems grappling with control input limitations and faults demonstrates its effectiveness.

Synthetic Jet Actuators for Active Flow Control: A Review

A synthetic jet actuator (SJA) is a fluidic device often consisting of a vibrating diaphragm that alters the volume of a cavity to produce a synthesized jet through an orifice. The cyclic ingestion and expulsion of the working fluid leads to a zero-net mass-flux and the transfer of linear momentum to the working fluid over an actuation cycle, leaving a train of vortex structures propagating away from the orifice. SJAs are a promising technology for flow control applications due to their unique features, such as no external fluid supply or ducting requirements, short response time, low weight, and compactness. Hence, they have been the focus of many research studies over the past few decades. Despite these advantages, implementing an effective control scheme using SJAs is quite challenging due to the large parameter space involving several geometrical and operational variables. This article aims to explain the working mechanism of SJAs and provide a comprehensive review of the effects of SJA design parameters in quiescent conditions and cross-flow.

Fault-tolerant observer-based leader-following consensus control for LPV multi-agent systems using virtual actuators

This paper introduces a fault-tolerant consensus control approach for a continuous multi-agent system with actuator faults. The faults in the multi-agent system are modelled as additive and multiplicative actuator faults. The objective is to design a leader-following control for consensus-based Linear Parameter Varying (LPV) multi-agent systems. The proposed control approach employs a leader-following strategy, where the dynamics of the LPV virtual leader are defined. The synchronisation error between the followers and the virtual leader is considered, and a consensus control law is introduced. The fault-tolerant mechanism involves the design of a distributed LPV observer and an LPV virtual actuator. Fault-tolerance is achieved through the redistribution of control inputs based on the effectiveness of actuators and dynamic virtual actuators. The primary focus is on establishing Linear Matrix Inequalities (LMIs) conditions ensuring the existence of LPV consensus control, LPV observers, and LPV virtual actuator gains. To demonstrate the effectiveness of the proposed fault-tolerant control, simulation results considering a team of Unmanned Aerial Vehicles (UAVs) in formation under actuator faults are presented.

Rotationary feedback control of the cylinder wake flow using a linear dynamic model

This study presents an active feedback control of the Kármán vortex shedding flow past a circular cylinder at low Reynolds numbers. The cylinder's rotational motion functions as the control actuator, while the transverse velocities of points along the wake axis serve as the feedback signals. First, using the autoregressive with exogenous input method, a linear reduced-order model (ROM) for the unstable flow is developed to capture the input–output behavior between the cylinder's rotational displacement and the feedback signals. This model is then utilized for controller design using the proportional and linear quadratic regulator (LQR) control methods, respectively, with their effectiveness analyzed and validated through high-fidelity numerical simulations. The results show that both methods can effectively suppress the unstable vortex shedding flow, while proportional control exhibits strong sensitivity to monitoring point locations and time delays. The ROM-based model can accurately predict the stability characteristics of the control system, providing valuable guidance for selecting optimal feedback signals. Moreover, we show that by appropriately adjusting the phase angle between the control input and feedback signals via time delays, the performance of proportional control can be significantly enhanced. Lastly, based on the ROM, an output-feedback suboptimal control law is designed using the LQR method. This suboptimal feedback control transforms unstable fluid modes into stable ones, resulting in complete suppression of the unsteady vortex shedding. It is further revealed that the inherent mechanism of suboptimal flow control is to construct an optimal phase shift through the linear superposition of multiple feedback signals. Overall, model-based analysis results agree well with those obtained from direct numerical simulations, confirming the validity of the proposed ROM-based feedback control procedure.

An embedded piezoelectric actuator for active vibration control: Concept, modeling, simulation, and investigation

An embedded piezoelectric actuator for active vibration control: Concept, modeling, simulation, and investigation

Periodic Event-Triggered Model Predictive Control for Networked Nonlinear Uncertain Systems With Disturbances.

This article investigates the event-triggered model predictive control (MPC) problem for a class of networked nonlinear uncertain systems subject to time-varying disturbances. Different from the traditional MPC, the proposed periodic event-triggered MPC (PETMPC) method does not generate new control sequence unless a predesigned periodic event-triggering mechanism (PETM) is violated. First, a generalized proportional-integral observer (GPIO) is developed to estimate the unknown state and disturbance information by using the sampled-data output of controlled system. Then, the disturbance predictions for future finite steps are obtained based on forward Euler method. After that, with the help of prediction model, the optimal control sequence, including the future finite step predicted control inputs, is generated and dexterously exploited during the interevent interval by storing it in a buffer installed between the control sequence generator and actuator, thereby leading to the further reduction of signal transmission number and the frequency of control sequence computations. Through a rigorous stability analysis, it can be proved that the closed-loop hybrid control system is globally bounded stable under the nominal PETMPC law. Finally, numerical simulations are conducted to substantiate the feasibility and superiority of the proposed PETMPC method.

Active Vibration Suppression of Lift-Offset Coaxial Rotorcraft Using Multicyclic Control

This study explores the best vibration reduction method using a multicyclic controller with an individual blade control (IBC) actuation scheme for a lift-offset coaxial helicopter during high-speed flight. The rotorcraft dynamics model consists of coaxial three-bladed counter-rotating rotors and a finite element fuselage stick model constructed based on the measured data of the XH-59A helicopter. The two-way coupled rotor–body vibration analysis results exhibited excellent correlation with the test data for the rotor hub loads and airframe vibrations. The best actuation scenarios are sought for the minimum vibration of the vehicle using either an open- or closed-loop control scheme. IBC actuation is shown to effectively reduce the vibrations of the rotorcraft. Coreduction of the three per rotor revolution (3P) and 6P vibrations of the rotorcraft is achieved using multicyclic control with offline system identification. Multicyclic harmonic IBC actuation enables the suppression of rotorcraft vibration at the rotor hub and pilot seat by 81.4%, and 3P cockpit vibration by 92% compared with the uncontrolled case, leading to a significantly reduced vibration level (below 0.05g) of the rotorcraft. The closed-loop multicyclic control using the identified system and aircraft model shows good correlation, ensuring the suitability of the present optimal control simulations.

Nonlinear pitch oscillation and control of a gravitational stabilized sailcraft perturbed by solar pressure torque

The sailcraft based space missions is deeply influenced by its attitude dynamics since the solar radiation pressure force for propellantless orbital maneuver is dependent on its orientation with respect to the sun line. Therefore, it is essential to explore the attitude motion evolution of a sailcraft and understand its attitude dynamic characteristics. To address this, nonlinear pitch dynamics of a sailcraft in an Earth orbit with a sliding mass as an attitude control actuator is focused on. Firstly, the Lagrange equation method is adopted to establish the pitch dynamics of a sailcraft subjected to the gravitational gradient torque, solar radiation pressure torque considering the Earth's occlusion of sunlight, damping torque, and the attitude control torque (this torque is generated by positioning the sliding mass at proper location). Secondly, the possible occurrence of chaotic pitch motion free of control torque is analytically predicted for the sailcraft in the circular and elliptical orbits using the Melnikov method respectively. The effectiveness of the Melnikov method is verified using various numerical methods such as phase plane, Poincaré sections, and power spectrum density. Furthermore, the influence of various parameters on the chaotic evolution is analyzed in detail. Lastly, to control the chaotic pitch motion onto the selected unstable periodic orbit obtained using the close return pairs, a sliding mode controller based on control input anti-saturation considering the position restriction of the sliding mass is developed. The effectiveness of the developed pitch chaos stabilization controller is verified by two numerical simulation cases.

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Abstract Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and fusion pilot plant may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

Online Task Switching and Scheduling Method for Attitude–Orbit–Shape-Distributed Control of Large Space Ring Structures

The attitude, orbit, and shape control actuators of large space structures on orbits are functional overlapping and task coupled, resulting in actuator redundancy and high-energy consumption. This paper explores the integrated attitude–orbit–shape control problem of large space ring structures and proposes an online task switching and scheduling method for multiple actuators of space structures (OTSS-MASS). An adaptive allocation framework is proposed for the task switching of distributed actuators. The objectives of attitude–orbit–shape control are decomposed into attitude adjustment, orbit change, and shape maintenance tasks through a task decomposition algorithm. Task value estimation models are designed to guide a greedy task allocation of actuators. The adaptive allocation framework achieves online task reconfiguration for multiple distributed actuators, thereby enhancing the maneuverability of large space structures, improving actuator work efficiency, and reducing energy consumption in orbit. Simulation results demonstrate that OTSS-MASS outperforms the conventional actuator distribution methods. The overall effectiveness is improved by over 24% in terms of the comprehensive index, time index, trajectory index, and shape index.

Microsensor-Internalized Fibers as Autonomously Controllable Soft Actuators.

Despite their strengths in flexibility and miniaturization, the stable operation of soft actuators under ever-changing environmental and biological conditions is hindered by the lack of applicable methods using internal sensors to detect unintentional stimuli. Here, the integration of a microscale driving source and sensors in a single fiber via thermal drawing is presented as a strategy to scalably produce autonomously responsive, feedback-controllable soft actuators. The regulation of the input electrothermal stimuli via a closed loop control system that is based on completely coupled internal sensory components enables multimodal actuation of fiber-based actuators, which is further demonstrated through preservation of actuating conditions, actuation of selected devices in their bundles, and modulation of motion characteristics. The approach to manufacturing autonomously controllable soft actuators can expand applications of soft actuators in kaleidoscopic biomedical and bioengineering fields for transportation, robotics, and prosthetics.

Data‐Driven Kinematic Modeling of Physical Origami Robots

Origami‐inspired structures facilitate the design of compliant and compact robots. However, physical origami robots possess inherent material compliance and mechanical imperfections, presenting challenges in modeling and redundant actuation for accurate control of all degree of freedom (DoF). Herein, a data‐driven kinematic modeling approach tailored for physical origami robots to effectively address the inherent compliance is introduced. This approach is applied to a multiloop origami spherical joint, which features a minimalistic design comprising two parallel waterbomb structures. This design allows for the integration of four actuators, thereby enabling full control over the structure's three DoF and its inherent compliance. It is demonstrated that a small dataset is adequate for accurately learning the forward kinematics, which then informs an optimization‐based inverse kinematics. Additionally, through trajectory tracking experiments, it is verified that the modeling method is both rapid and accurate, making it suitable for real‐time applications. To showcase a practical application, the joint and its models are utilized as a force feedback origami joystick, designed for intuitive drone control. This joystick offers an enhanced control experience and conveys crucial information about collisions and external forces to drone operators. Overall, the data‐driven modeling approach introduces a new possibility of designing controllable compliant interfaces.

Event‐Triggered Robust Control of Robot Manipulators

ABSTRACTThis paper proposes a new event‐triggered robust control system for robot manipulators, based on two event‐triggered mechanisms (ETMs), which lead to intermittent communication not only for the sensor‐to‐controller channel but also for the controller‐to‐actuator channel. The proposed control system enjoys the advantage of requiring fewer resources of data communication and less signal updating of the control actuators. The control performance of the proposed control system is analyzed based on the Lyapunov approach. Furthermore, the absence of the Zeno behavior in the triggering sequence is proved rigorously. Finally, experiments are carried out on a two‐link robot manipulator system to support the theoretical results.