Actuators

Research

22 pages, 2186 KiB

Open AccessArticle

Deep Reinforcement Learning-Based Enhancement of Robotic Arm Target-Reaching Performance

by Ldet Honelign, Yoseph Abebe, Abera Tullu and Sunghun Jung

Actuators 2025, 14(4), 165; https://doi.org/10.3390/act14040165 - 26 Mar 2025

Viewed by 523

This work investigates the implementation of the Deep Deterministic Policy Gradient (DDPG) algorithm to enhance the target-reaching capability of the seven degree-of-freedom (7-DoF) Franka Pandarobotic arm. A simulated environment is established by employing OpenAI Gym, PyBullet, and Panda Gym. After 100,000 training time [...] Read more.

This work investigates the implementation of the Deep Deterministic Policy Gradient (DDPG) algorithm to enhance the target-reaching capability of the seven degree-of-freedom (7-DoF) Franka Pandarobotic arm. A simulated environment is established by employing OpenAI Gym, PyBullet, and Panda Gym. After 100,000 training time steps, the DDPG algorithm attains a success rate of 100% and an average reward of −1.8. The actor loss and critic loss values are 0.0846 and 0.00486, respectively, indicating improved decision-making and accurate value function estimations. The simulation results demonstrate the efficiency of DDPG in improving robotic arm performance, highlighting its potential for application to improve robotic arm manipulation. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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17 pages, 2078 KiB

Open AccessArticle

Adaptive Output Regulation for PMSM Speed Servo System via Time-Varying Internal Model Approach

by Hui Song, Zhaowu Ping, Jiaze Hui, Yunzhi Huang and Jun-Guo Lu

Actuators 2025, 14(3), 158; https://doi.org/10.3390/act14030158 - 20 Mar 2025

Viewed by 234

Abstract

This article investigates the adaptive output regulation problem of a permanent magnet synchronous motor (PMSM) speed servo system with unknown time-varying exosystems and aims to achieve multiple objectives including speed tracking, disturbance rejection, and robustness simultaneously. Existing linear or nonlinear internal model designs [...] Read more.

This article investigates the adaptive output regulation problem of a permanent magnet synchronous motor (PMSM) speed servo system with unknown time-varying exosystems and aims to achieve multiple objectives including speed tracking, disturbance rejection, and robustness simultaneously. Existing linear or nonlinear internal model designs are not applicable to the output regulation problem under the time-varying situation. Hence, we first construct a time-varying internal model to transform this control problem into a robust stabilization problem for a time-varying augmented system, and then design a stabilization controller integrating robust control and adaptive control techniques to stabilize this system. Finally, the validity of the proposed approach is verified through simulations and experiments. It is worth mentioning that our approach can achieve high-precision speed tracking of PMSM under parameter uncertainties and load torque disturbance with unknown time-varying frequencies. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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16 pages, 4776 KiB

Open AccessArticle

Integrated Analytical Modeling and Numerical Simulation Framework for Design Optimization of Electromagnetic Soft Actuators

by Hussein Zolfaghari, Nafiseh Ebrahimi, Yuan Ji, Xaq Pitkow and Mohammadreza Davoodi

Actuators 2025, 14(3), 128; https://doi.org/10.3390/act14030128 - 6 Mar 2025

Viewed by 586

Abstract

The growing interest in soft robotics arises from their unique ability to perform tasks beyond the capabilities of rigid robots, with soft actuators playing a central role in this innovation. Among these, electromagnetic soft actuators (ESAs) stand out for their fast response, simple [...] Read more.

The growing interest in soft robotics arises from their unique ability to perform tasks beyond the capabilities of rigid robots, with soft actuators playing a central role in this innovation. Among these, electromagnetic soft actuators (ESAs) stand out for their fast response, simple control mechanisms, and compact design. Analytical and experimental studies indicate that smaller ESAs enhance the force per unit cross-sectional area (F/CSA) without compromising force efficiency. This work uses the magnetic vector potential (MVP) to calculate the magnetic field of an ESA, which is then used to derive the actuator’s generated force. A mixed integer non-linear programming (MINLP) optimization framework is introduced to maximize the ESA’s F/CSA. Unlike prior methods that independently optimized parameters, such as ESA length and permanent magnet diameter, this study jointly optimizes these parameters to achieve a more efficient and effective design. To validate the proposed framework, finite element-based COMSOL 5.4 is used to simulate the magnetic field and generated force, ensuring consistency between MVP-based calculations and the physical model. Additionally, simulation results demonstrate the effectiveness of MINLP optimization in identifying the optimal design parameters for maximizing the F/CSA of the ESA. The data and code are available at GitHub Repository. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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16 pages, 2656 KiB

Open AccessArticle

Ground Motion Modeling and Adaptive Joint Control for Large-Scale UAVs

by Bo Wang, Wensheng Wang, Xiaodan Cui and Xiaoxiong Liu

Actuators 2025, 14(1), 6; https://doi.org/10.3390/act14010006 - 27 Dec 2024

Viewed by 543

Abstract

Aiming at the problem of lateral deviation of large-scale long-endurance solar-powered UAVs relative to the runway during takeoff or landing, a UAV ground motion control structure based on the combination of engine differential and rudder was proposed. According to the structural characteristics of [...] Read more.

Aiming at the problem of lateral deviation of large-scale long-endurance solar-powered UAVs relative to the runway during takeoff or landing, a UAV ground motion control structure based on the combination of engine differential and rudder was proposed. According to the structural characteristics of large-scale long-endurance solar-powered UAVs, a ground motion model of a three-point layout UAV including landing gear was established, and the ground rolling dynamics and modal characteristics were analyzed. In order to accurately correct the trajectory error, the outer loop designs a trajectory correction control law and gives the inner loop desired control instructions. In order to solve the problem of environmental disturbance and small heading damping, the inner loop adopts the adaptive back-stepping control method. The disturbance signal is estimated through the adaptive law and compensated into the control system to achieve balanced control of speed and rolling correction. Finally, medium-speed and high-speed sliding tests were designed to verify the rationality of the proposed control scheme and control structure, as well as the efficiency of the control law design method adopted. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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20 pages, 3401 KiB

Open AccessArticle

Incremental Nonlinear Dynamics Inversion and Incremental Backstepping: Experimental Attitude Control of a Tail-Sitter UAV

by Alexandre Athayde, Alexandra Moutinho and José Raul Azinheira

Actuators 2024, 13(6), 225; https://doi.org/10.3390/act13060225 - 17 Jun 2024

Viewed by 1309

Abstract

Incremental control strategies such as Incremental Nonlinear Dynamics Inversion (INDI) and Incremental Backstepping (IBKS) provide undeniable advantages for controlling Uncrewed Aerial Vehicles (UAVs) due to their reduced model dependency and accurate tracking capacities, which is of particular relevance for tail-sitters as these perform [...] Read more.

Incremental control strategies such as Incremental Nonlinear Dynamics Inversion (INDI) and Incremental Backstepping (IBKS) provide undeniable advantages for controlling Uncrewed Aerial Vehicles (UAVs) due to their reduced model dependency and accurate tracking capacities, which is of particular relevance for tail-sitters as these perform complex, hard to model manoeuvres when transitioning to and from aerodynamic flight. In this research article, a quaternion-based form of IBKS is originally deduced and applied to the stabilization of a tail-sitter in vertical flight, which is then implemented in a flight controller and validated in a Hardware-in-the-Loop simulation, which is also made for the INDI controller. Experimental validation with indoor flight tests of both INDI and IBKS controllers follows, evaluating their performance in stabilizing the tail-sitter prototype in vertical flight. Lastly, the tracking results obtained from the experimental trials are analysed, allowing an objective comparison to be drawn between these controllers, evaluating their respective advantages and limitations. From the successfully conducted flight tests, it was found that both incremental solutions are suited to control a tail-sitter in vertical flight, providing accurate tracking capabilities with smooth actuation, and only requiring the actuation model. Furthermore, it was found that the IBKS is significantly more computationally demanding than the INDI, although having a global proof of stability that is of interest in aircraft control. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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18 pages, 8899 KiB

Open AccessArticle

A Sparse Neural Network-Based Control Method for Saturated Nonlinear Affine Systems

by Jing Zhang, Baoqun Yin, Jianwen Huo, Hongliang Guo and Zhan Li

Actuators 2024, 13(6), 204; https://doi.org/10.3390/act13060204 - 29 May 2024

Viewed by 1025

Abstract

Saturated nonlinear affine systems are widely encountered in many engineering fields. Currently, most control methods on saturated nonlinear affine systems are not specifically designed based on sparsity-based control methodologies, and they might require sparse identification at the beginning stage and applying tracking control [...] Read more.

Saturated nonlinear affine systems are widely encountered in many engineering fields. Currently, most control methods on saturated nonlinear affine systems are not specifically designed based on sparsity-based control methodologies, and they might require sparse identification at the beginning stage and applying tracking control afterwards. In this paper, a sparse neural network (SNN)-based control method from an l_p-norm

(1 \leq p < 2)

optimization perspective is proposed for saturated nonlinear affine systems by taking advantage of the nice properties of primal dual neural networks for optimization. In particular, when

p = 1

, a new alternative controller based on SNN is derived, encountering computational difficulties distinct from those of another solution set in the basic dual neural network. The convergence properties of such SNN-based controllers are investigated and analyzed to find a control solution. Five illustrative examples further are shown to demonstrate the efficiency of the proposed SNN-based control method for tracking the desired references of saturated nonlinear affine systems. In the practical application scenario involving the UR5 robot control, the trajectory’s average errors are consistently confined to a minimal magnitude of 10⁻⁴ m. These findings substantiate the efficacy of the SNN-based control approach proposed for precise tracking control in saturated nonlinear affine systems. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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16 pages, 1811 KiB

Open AccessArticle

A Novel Extended Unscented Kalman Filter Is Designed Using the Higher-Order Statistical Property of the Approximate Error of the System Model

by Chengyi Li and Chenglin Wen

Actuators 2024, 13(5), 169; https://doi.org/10.3390/act13050169 - 1 May 2024

Cited by 2 | Viewed by 1576

Abstract

In the actual working environment, most equipment models present nonlinear characteristics. For nonlinear system filtering, filtering methods such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF) have been developed successively, all of which show good results. [...] Read more.

In the actual working environment, most equipment models present nonlinear characteristics. For nonlinear system filtering, filtering methods such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF) have been developed successively, all of which show good results. However, in the process of nonlinear system filtering, the performance of EKF decreases with an increase in the truncation error and even diverges. With improvement of the system dimension, the sampling points of UKF are relatively few and unrepresentative. In this paper, a novel high-order extended Unscented Kalman Filter (HUKF) based on an Unscented Kalman Filter is designed using the higher-order statistical properties of the approximate error. In addition, a method for calculating the approximate error of the multi-level approximation of the original function under the condition that the measurement is not rank-satisfied is proposed. The effectiveness of the filter is verified using digital simulation experiments. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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33 pages, 6190 KiB

Open AccessArticle

Practical System Identification and Incremental Control Design for a Subscale Fixed-Wing Aircraft

by Rasmus Steffensen, Kilian Ginnell and Florian Holzapfel

Actuators 2024, 13(4), 130; https://doi.org/10.3390/act13040130 - 4 Apr 2024

Cited by 5 | Viewed by 2408

Abstract

An incremental differential proportional integral (iDPI) control law using eigenstructure assignment gain design is tested in flight on a subscale platform to validate its suitability for fixed-wing flight control. A kinematic relation for the aerodynamic side-slip angle rate is developed to apply a [...] Read more.

An incremental differential proportional integral (iDPI) control law using eigenstructure assignment gain design is tested in flight on a subscale platform to validate its suitability for fixed-wing flight control. A kinematic relation for the aerodynamic side-slip angle rate is developed to apply a pseudo full state feedback. In order to perform the gain design and assessment, a plant model is estimated using flight test data from gyro, accelerometer, airspeed and surface deflection measurements during sine-sweep excitations. Transfer function models for the actuators and surface deflections are identified both in-flight and on the ground for several different actuators and control surfaces using hall sensor surface deflection measurements. The analysis reveals a large variation in bandwidth between the different types of servo motors. Flight test results are presented which demonstrates that the plant model estimates based on tests with good frequency excitation, high bandwidth actuators and surface deflection measurements can be used to reasonably predict the closed-loop dynamic behavior of the aircraft. The closed-loop flight test results of the iDPi control law show good performance and lays the groundwork for further development. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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16 pages, 2115 KiB

Open AccessArticle

Incremental Nonlinear Control for Aeroelastic Wing Load Alleviation and Flutter Suppression

by Roderick Schildkamp, Jing Chang, Jurij Sodja, Roeland De Breuker and Xuerui Wang

Actuators 2023, 12(7), 280; https://doi.org/10.3390/act12070280 - 9 Jul 2023

Cited by 3 | Viewed by 3264

Abstract

This paper proposes an incremental nonlinear control method for an aeroelastic system’s gust load alleviation and active flutter suppression. These two control objectives can be achieved without modifying the control architecture or the control parameters. The proposed method has guaranteed stability in the [...] Read more.

This paper proposes an incremental nonlinear control method for an aeroelastic system’s gust load alleviation and active flutter suppression. These two control objectives can be achieved without modifying the control architecture or the control parameters. The proposed method has guaranteed stability in the Lyapunov sense and also has robustness against external disturbances and model mismatches. The effectiveness of this control method is validated by wind tunnel tests of an active aeroelastic parametric wing apparatus, which is a typical wing section containing heave, pitch, flap, and spoiler degrees of freedom. Wind tunnel experiment results show that the proposed nonlinear incremental control can reduce the maximum gust loads by up to 46.7% and the root mean square of gust loads by up to 72.9%, while expanding the flutter margin by up to 15.9%. Full article

(This article belongs to the Special Issue From Theory to Practice: Incremental Nonlinear Control)

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