Control Strategy For Actuators Research Articles

Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints.

Autonomous Underwater Vehicles (AUVs) play a significant role in ocean-related research fields as tools for human exploration and the development of marine resources. However, the uncertainty of the underwater environment and the complexity of underwater motion pose significant challenges to the fault-tolerant control of AUV actuators. This paper presents a fault-tolerant control strategy for AUV actuators based onTakagi and Sugeno (T-S) fuzzy logic and pseudo-inverse quadratic programming under control constraints, aimed at addressing potential actuator faults. Firstly, considering the steady-state performance and dynamic performance of the control system, a T-S fuzzy controller is designed. Next, based on the redundant configuration of the actuators, the propulsion system is normalized, and the fault-tolerant control of AUV actuators is achieved using the pseudo-inverse method under thrust allocation. When control is constrained, a quadratic programming approach is used to compensate for the input control quantity. Finally, the effectiveness of the fuzzy control and fault-tolerant control allocation methods studied in this paper is validated through mathematical simulation. The experimental results indicate that in various fault scenarios, the pseudo-inverse combined with a nonlinear quadratic programming algorithm can compensate for the missing control inputs due to control constraints, ensuring the normal thrust of AUV actuators and achieving the expected fault-tolerant effect.

Model-Free Adaptive Positioning Control of the Bidirectional Stick-Slip Piezoelectric Actuator with Coupled Asymmetric Flexure-Hinge Mechanisms.

A model-free adaptive positioning control strategy for piezoelectric stick-slip actuators (PSSAs) with uncertain disturbance is proposed. The designed controller consists of a data-driven self-learning feedforward controller and a model-free adaptive feedback controller with a radial basis function neural network (RBFNN)-based observer. Unlike the traditional model-based control methods, the model-free adaptive control (MFAC) strategy avoids the complicated modeling process. First, the nonlinear system of the PSSA is dynamically linearized into a data model. Then, the model-free adaptive feedback controller based on a data model is designed to avoid the complicated modeling process and enhance the robustness of the control system. Simultaneously, the data-driven self-learning feedforward controller is improved to realize the high-precision control performance. Additionally, the convergence of the tracking error and the boundedness of the control output signal are proved. Finally, the experimentally obtained results illustrate the advantages and effectiveness of the developed control methodology on the bidirectional stick-slip piezoelectric actuator with coupled asymmetric flexure-hinge mechanisms. The positioning error through the proposed controller reaches 30 nm under the low-frequency condition and 200 nm under the high-frequency condition when the target position is set to 100 μm. In addition, the target position can be accurately tracked in less than 0.5 s in the presence of a 100 Hz frequency.

Modeling and Control Strategies for Liquid Crystal Elastomer-Based Soft Robot Actuator

Liquid crystal elastomer is a type of soft material with unique physical and chemical properties that offer a variety of possibilities in the growing field of soft robot actuators. This type of material is able to exhibit large, revertible deformation under various external stimuli, including heat, electric or magnetic fields, light, etc., which may lead to a wide range of different applications such as bio-sensors, artificial muscles, optical devices, solar cell plants, etc. With these possibilities, it is important to establish modeling and control strategies for liquid crystal elastomer-based actuators, to obtain the accurate prediction and description of its physical dynamics. However, so far, existing studies on this type of the actuators mainly focus on material properties and fabrication, the state of art on the modeling and control of such actuators is still preliminary. To gain a better understanding on current studies of the topic from the control perspective, this review provides a brief collection on recent studies on the modeling and control of the liquid crystal elastomer-based soft robot actuator. The review will introduce the deformation mechanism of the actuator, as well as basic concepts. Existing studies on the modeling and control for the liquid crystal elastomer-based actuator will be organized and introduced to provide an overview in this field as well as future insights.

Controlling Soft Fluidic Actuators Using Soft DEA-Based Valves

Fluidic soft actuators have been widely used for applications where compliance is desirable – such as in delicate robotic manipulation. As their operation is based on pressurization, fluidic actuators typically rely on bulky, rigid pumps, valves, and pressure regulators for control. This dependence on rigid components hinders the development of compact and fully-soft robots. Soft regulation systems designed for control of these actuators have been recently developed based on soft valves using dielectric elastomer actuators, but precise control has not been achieved. In this work, we leverage these valves to introduce a soft regulation system capable of precise closed-loop position control of a soft hydraulic actuator with multiple controllers. We also achieve open-loop trajectory tracking based on a data-driven model of the fluidic system. Finally, we combine the valve system with wearable strain sensors to create the first teleoperated fluidic circuit where the sensor, actuator, and regulation system are all soft. This work presents control strategies for fluid-driven actuators with soft sensors and regulation systems, showing the potential for future all-soft motion control of soft hydraulic robots.

Simulation-Based Testing of Subsystems for Autonomous Vehicles at the Example of an Active Suspension Control System

Automated driving functions are expected to increase both the safety and ride comfort of future vehicles. Ensuring their functional safety and optimizing their performance requires thorough testing. Costs and duration of tests can be reduced if more tests can be performed numerically in a feasible simulation framework. This simulation setup must include all subsystems of the autonomous vehicle, which significantly interact with the system under test. In this paper, a modular model chain is presented, which is developed for testing systems with an impact on vehicle motion. It includes trajectory planning, motion control, and a model of the vehicle dynamics in a closed loop. Each subsystem can easily be exchanged to adapt the model chain with respect to the simulation objectives. As a use case, the testing of an active suspension control system is discussed. It is designed directly for use in autonomous cars and uses inputs from the vehicle motion planning subsystem for planning the suspension actuator motion. Using the presented closed-loop model chain, the effect of different actuator control strategies on ride comfort is compared, such as curve tilting. Furthermore, the impact of the active suspension system on lateral vehicle motion is shown.

Electromechanical Actuator Design and Control Strategy for UAV Landing Gear

UAV is becoming more and more prevalent not only in the military field but also in the civilian field, whose flight safety and performance is of top concern. The landing gear system is undoubtedly a determining factor in UAV taking off and landing. In recent days, the all-electric trend in UAV design is not irreversible. As a result, the hydraulic actuator is replaced by EMA in the landing system. The electromechanical actuator for UAV landing system is designed in this paper. The detailed actuator system design is introduced in the beginning. And then communication protocol between the actuator system and the flight control computer is presented, serving as the basis of control strategy, which is the main content to study. The control strategy mainly deals with normal landing and emergency landing process. At last, the conclusion part summarizes its applications. The EMA devised in this paper and its corresponding control strategy provide a new idea in the landing system design of UAV.

Hybrid active flow induced vibration control of a circular cylinder equipped with a wake-mounted smart piezoelectric bimorph splitter plate

A two-dimensional numerical study on active flow induced vibration (FIV) suppression of an elastically suspended circular cylinder fitted with a thin smart flexural-mode (bender-type) piezoelectric bimorph splitter plate on its wake side in real-time collaboration with a conventional base force actuator is carried out in laminar cross-flow condition (Re=100) for a wide range of reduced flow velocities (4≤U∗≤40). The numerical model is based on a strongly-coupled partitioned two-way iteratively implicit Fluid–Structure Interaction (FSI) routine implemented in a multiphysics simulation framework that interactively connects a CFD-based finite volume solver with a nonlinear transient computational structural dynamics (CSD) finite-element solver. A single-input-multi-output (SIMO) direct displacement feedback control law is introduced into the coupled transient dynamic simulation framework through an internal subroutine written in APDL command language. Three distinct feedback control configurations are implemented and compared, namely, the force-actuated, the piezo-actuated, and the hybrid actuation control systems, primarily aiming at suppression of cylinder transverse displacement amplitude. Further improvements on the controller performance are achieved by incorporating two modified hybrid actuation control strategies particularly designed for mitigation of excessive temporal oscillations of the drag and lift coefficients. Extensive numerical simulations reveal the important effects of splitter plate length, reduced velocity, and controller configuration on the key structural/flow-field parameters and flow structure. The hybrid actuation control configurations are found to provide a largely better displacement response control performance than the single-alone force-actuated or piezo-actuated systems. Also, the overall success of the modified hybrid control strategies in effective alleviation of the highly erratic lift and drag forces experienced by the smart cylinder-plate assembly is demonstrated. Lastly, it is concluded that if one primarily aims at prompt and forceful suppression of the base cylinder motion regardless of lift and drag force variations, the originally designed hybrid actuation control system is sufficiently adequate, while if one is specifically concerned with the severe temporal fluctuations in the lift and drag coefficients, the modified hybrid control configurations should be employed.

Control Strategies for Soft Robot Systems

Soft robots have recently attracted increased attention because their characteristics of low‐cost fabrication, durability, and deformability make them uniquely suited for applications in bio‐integrated systems. Being fundamentally different from traditional rigid robots, soft robots exhibit properties of infinite degrees of freedom (DOF) and nonlinear materials properties that require innovations in control systems. With the rapid development of materials science, robotics, and artificial intelligence, the diversification of actuator mechanisms and algorithms has enabled a wide range of unique control strategies. This review summarizes the basics of actuator mechanisms and control strategies, including open‐loop control, closed‐loop control, and autonomous control, and discusses their implementation from diversified perspectives. Control strategies are evaluated based on their compatibility with materials sets, application goals, and implementation route. The emerging directions are forecasted from the perspectives of interfacing between controller and actuator, underactuated control strategies, and implementation of artificial intelligence (AI).

An Overview of Micronanoswarms for Biomedical Applications.

Micronanoswarms have attracted extensive attention worldwide due to their great promise in biomedical applications. The collective behaviors among thousands, or even millions, of tiny active agents indicate immense potential for benefiting the progress of clinical therapeutic and diagnostic methods. In recent years, with the development of smart materials, remote actuation modalities, and automatic control strategies, the motion dexterity, environmental adaptability, and functionality versatility of micronanoswarms are improved. Swarms can thus be designed as dexterous platforms inside living bodies to perform a multitude of tasks related to healthcare. Existing surveys summarize the design, functionalization, and biomedical applications of micronanorobots and the actuation and motion control strategies of micronanoswarms. This review presents the recent progress of micronanoswarms, aiming for biomedical applications. The recent advances on structural design of artificial, living, and hybrid micronanoswarms are summarized, and the biomedical applications that could be tackled using micronanoswarms are introduced, such as targeted drug delivery, hyperthermia, imaging and sensing, and thrombolysis. Moreover, potential challenges and promising trends of future developments are discussed. It is envisioned that the future success of these promising tools will have a significant impact on clinical treatment.

Precision open-loop control of piezoelectric actuator

Due to space constraints, some micro-assemblies and micro-operating systems cannot install sensors, so it is challenging to achieve closed-loop control. For this reason, a precision open-loop control strategy for piezoelectric actuators is proposed. Firstly, based on the PI model and the proposed threshold partition method, the hysteresis model of the piezoelectric actuator with rate-dependent and few operators is established. Then the hysteresis error of the piezoelectric actuator is compensated by the inverse model obtained. Secondly, the creep model of the logarithmic piezoelectric actuator with simple expression and few parameters is established. Then, a creep controller without demand inverse is designed to compensate for the creep error of the piezoelectric actuator. Finally, a ZVD (Zero Vibration Derivative) input shaping method with good robustness is given to eliminate the oscillation generated by the piezoelectric actuator under the action of the step signal. The experimental results show that the displacement error of piezoelectric actuator is reduced from −9.07 to 9.46 μm to −1.22 to 1.78 μm when the maximum displacement is 120 μm after hysteresis compensation; after creeping compensation, within the action time of the 1200 s, the displacement creep of the piezoelectric actuator was reduced from 5.5 μm before compensation to 0.3 μm; after the oscillation control, the displacement overshoot of the piezoelectric actuator is reduced to 0.6% of that before control.

Mixed Sensitivity-Based Robust H∞ Control Method for Real-Time Hybrid Simulation

Real-time hybrid simulation (RTHS), dividing the emulated structure into numerical substructures (NS) and physical substructures (PS), is a powerful technique to obtain responses and then to assess the seismic performance of civil engineering structures. A transfer system, a servo-hydraulic actuator or shaking table, is used to apply boundary conditions between the two substructures. However, the servo-hydraulic actuator is inherently a complex system with nonlinearities and may introduce time delays into the RTHS, which will decrease the accuracy and stability of the RTHS. Moreover, there are various uncertainties in RTHS. An accurate and robust actuator control strategy is necessary to guarantee reliable simulation results. Therefore, a mixed sensitivity-based H∞ control method was proposed for RTHS. In H∞ control, the dynamics and robustness of the closed-loop transfer system are realized by performance weighting functions. A form of weighting function was given considering the requirement in RTHS. The influence of the weighting functions on the dynamics was investigated. Numerical simulations and actual RTHSs were carried out under symmetric and asymmetric dynamic loads, namely sinusoidal and earthquake excitation, respectively. Results indicated that the H∞ control method used for RTHS is feasible, and it exhibits an excellent tracking performance and robustness.

Minimal mass design of active tensegrity structures

Tensegrity structures have been widely utilized as lightweight structures due to their high stiffness-to-mass and strength-to-mass ratios. Minimal mass design of tensegrity structures subject to external loads and specific constraints (e.g., member yielding and buckling) has been intensively studied. However, all the existing studies focus on passive tensegrity structures, i.e., the structural members cannot change their lengths actively and the structure has to passively resist external loads. An active tensegrity structure equipped with actuators can actively adapt its internal forces and nodal positions and thus can actively resist external loads. Therefore, it is expected that active tensegrity structures use less material compared to passive tensegrity structures thus leading to a smaller mass. Due to the integration of the active control system, the design of active tensegrity structures is different from passive tensegrity structures. This study proposes a general approach for the design of minimal mass active tensegrity structures based on a mixed integer programming scheme, in which the member cross-sectional areas, prestress, actuator layout and control strategies (i.e., actuator length changes) are designed simultaneously. The member cross-sectional areas, prestress level, and actuator control strategies are treated as continuous variables and the actuator layout is treated as a binary variable. The equilibrium condition, member yielding, cable slackness, strut buckling, and the limitations on the nodal displacements as well as other practical requirements are formulated as constraints. Three typical active tensegrity structures are designed through the proposed approach and the results are benchmarked with the equivalent minimal mass passive designs. It is illustrated that the active designs can significantly decrease the material consumption compared with the equivalent passive designs thus leading to more lightweight tensegrity structures.

Development of an Actuator for Translatory Movement by Means of a Detented Switching Shaft Based on a Shape Memory Alloy Wire for Repeatable Mechanical Positioning

Actuators based on the shape memory effect have recently become more and more economically important due to the many advantages of shape memory alloys (SMAs), such as their high energy density. SMAs are usually used to control the end/maximum positions, thus the actuators always move between two positions. The repeatable control of intermediate positions has so far proven difficult, because in most cases, external sensors are necessary to determine the length of the SMA element. Additionally control strategies for SMA actuators are rather complex due to the non-linear behavior of this material. The SMA actuator presented here is able to control intermediate positions with repeatable accuracy without the need of a separate control technology. The integrated control unit is based on a mechanical principle using a shaft with a circumference groove. This groove has a height profile that turns the shafts rotation, generated by the SMA, into a translational movement. Therefore, the SMA wire generates a partial stroke at each complete activation, turning the shaft partially. With several activation cycles in a row, the stroke adds up until reaching the maximum. A further activation cycle of the wire resets the actuators stroke to its initial position. Each part of the stroke can, thereby, be controlled precisely and repeatedly within the scope of each complete cycle of the actuator. Based on an integrated ratchet, each stroke of the actuator can hold energy free.

Velocity Sensor for Real-Time Backstepping Control of a Multirotor Considering Actuator Dynamics.

A real-time implementation of a control scheme for a multirotor, based on angular velocity sensors for the actuators, is presented. The control scheme is composed of two loops: an inner loop for the actuators and an outer loop for the unmanned aerial vehicle (UAV). The UAV control algorithm is designed by means of the backstepping technique and a robust sliding mode differentiator, and the actuator control strategy is based on a standard proportional-integral-derivative (PID) controller. A robust exact differentiator, based on high order sliding modes, is used to estimate the complex derivatives present in the proposed control law. As the measurements of the propeller’s angular velocities are required for the control law, velocity sensors are mounted in the axles of the rotors to retrieve them and a signal conditioning stage is implemented. In addition, dynamical models for the actuators of the aircraft were calculated by means of transfer functions obtained via experimental measurements in a test bench developed for this purpose. This test bench permits to characterize the parameters of the transfer functions by comparing the forces computed using the nominal parameter to the measured forces. To this end, it is assumed that the loads in the actuators of the vehicle are insignificant during flight. The effectiveness of the proposed sensor, its signal conditioning, and the overall control scheme are validated by means of simulation results and real-time experiments.

Asymptotically Stable Disturbance Observer-Based Compliance Control of Electrohydrostatic Actuators

This article proposes a disturbance observer (DOB)-based compliance control strategy for electrohydrostatic actuators (EHAs), particularly those with high gear reductions and long hydraulic pipelines, which could lead to a high performance interactive robot system. EHAs suffer significantly from internal leakage and friction, which hampers the application of existing compliance control methods to EHAs. Therefore, a two-degree-of-freedom (DoF) DOB is introduced to compensate for both undesirable effects separately; one degree of freedom handles friction observations and the other monitors internal leakage. Then, a compliance controller is designed without affecting the closed-loop stability. To this end, the state of the nominal plant, not the real plant, is used in the designs of the internal leakage observer and the compliance controller as it guarantees closed-loop stability. The asymptotic convergence of the closed-loop system is evaluated via simulations and experiments.

Single-Layer Learning-Based Predictive Control With Echo State Network for Pneumatic-Muscle-Actuators-Driven Exoskeleton

This article presents a single-layer learning-based predictive control strategy for pneumatic muscle actuators (PMAs)-driven lower limb exoskeleton. Although PMAs are promising for rehabilitation robots, they suffer from nonlinearities, unmodeled uncertainties, hysteresis, etc. As a consequence, the mechanism actuated by PMAs rarely involves complex dynamics, and the related precise control remains a challenging problem. Hence, considering the global approximation capability of neural networks, we use an echo state network (ESN) to approximate the dynamics of the PMAs-driven exoskeleton with a nonlinear autoregressive exogenous model and forecast its behaviors by constructing training and testing data sets. Through the model predictions, the idea of single-layer learning solves a quadratic programming problem based on the principle of predictive control over a finite future horizon. After that, the control strategy turns out to be asymptotically stable when the ESN is capable of approximating the dynamics of the exoskeleton. Passive gait training experiments are conducted with six healthy subjects to verify the effectiveness of the proposed control strategy. Compared with the traditional strategies, the proposed control strategy achieves higher tracking accuracy for passive gait training tasks.

Active synchronising control of dual-mode coupling transmission for electric vehicles

Since the drive motor of electric vehicles has powerful speed and torque adjustment capabilities, the feasibility of replacing the synchroniser with an engagement sleeve from a clutchless automatic mechanical transmission (AMT) for electric vehicles is a problem worthy of study. In this paper, an active synchronising control is devised for a novel two-speed AMT named dual-mode coupling transmission. A speed-current double-closed-loop controller for regulating the drive motors' speed is constructed, and a sliding mode observer (SMO) is developed for the estimation of the state feedback information. An odd-even tooth strategy based on particle swarm optimisation is designed to reduce the angle difference. The shift control simulation illustrates that the active synchronising control can reduce the reliance on the synchroniser to a large degree, but the impact is still large after cancelling the synchroniser rings, so the engagement sleeve structure and actuator control strategy must be optimised before replacing the synchroniser.

Active synchronising control of dual-mode coupling transmission for electric vehicles

Since the drive motor of electric vehicles has powerful speed and torque adjustment capabilities, the feasibility of replacing the synchroniser with an engagement sleeve from a clutchless automatic mechanical transmission (AMT) for electric vehicles is a problem worthy of study. In this paper, an active synchronising control is devised for a novel two-speed AMT named dual-mode coupling transmission. A speed-current double-closed-loop controller for regulating the drive motors' speed is constructed, and a sliding mode observer (SMO) is developed for the estimation of the state feedback information. An odd-even tooth strategy based on particle swarm optimisation is designed to reduce the angle difference. The shift control simulation illustrates that the active synchronising control can reduce the reliance on the synchroniser to a large degree, but the impact is still large after cancelling the synchroniser rings, so the engagement sleeve structure and actuator control strategy must be optimised before replacing the synchroniser.

Deep Reinforcement Learning-Based Traffic Signal Control Using High-Resolution Event-Based Data.

Reinforcement learning (RL)-based traffic signal control has been proven to have great potential in alleviating traffic congestion. The state definition, which is a key element in RL-based traffic signal control, plays a vital role. However, the data used for state definition in the literature are either coarse or difficult to measure directly using the prevailing detection systems for signal control. This paper proposes a deep reinforcement learning-based traffic signal control method which uses high-resolution event-based data, aiming to achieve cost-effective and efficient adaptive traffic signal control. High-resolution event-based data, which records the time when each vehicle-detector actuation/de-actuation event occurs, is informative and can be collected directly from vehicle-actuated detectors (e.g., inductive loops) with current technologies. Given the event-based data, deep learning techniques are employed to automatically extract useful features for traffic signal control. The proposed method is benchmarked with two commonly used traffic signal control strategies, i.e., the fixed-time control strategy and the actuated control strategy, and experimental results reveal that the proposed method significantly outperforms the commonly used control strategies.

Developing an actuated signal control strategy to improve the operations of contraflow left-turn lane design at signalized intersections

Contraflow left-turn lane (CLL) design has been increasingly used in China to help relieve traffic congestion associated with left-turning vehicles at signalized intersections. With the CLL design, one or multiple left-turn lanes are setup in the opposing through lanes adjacent to the median. The basic idea of the CLL design is to provide additional capacity to left-turning vehicles by making use of the opposing through lanes. The primary objective of the present study was to propose an actuated signal control strategy to improve the operations of the CLL design at signalized intersections. The proposed control strategy introduced an extra stage between the pre-signal and the main signal at the signalized intersection with the CLL design. Two detectors were installed: one at the upstream median opening and the other at the contraflow lane. A procedure was proposed for optimizing the distance between the upstream median opening and the main signal, such that the discharge rate of the left-turning vehicles and the utilization rate of the contraflow lane can be maximized. Simulation experiments were conducted to compare the performance of the proposed actuated control strategy versus the fixed time control strategy. The results show that the proposed design concept outperforms the fixed time control strategy in increasing capacity and reducing delay for left-turning vehicles.