Mechatronics最新文献_第7页

Robotized Incremental Sheet Forming trajectory control using deep neural network for force/torque compensator and task-space error tracking controller 基于深度神经网络的力/扭矩补偿器和任务空间误差跟踪控制器的自动化增量成形轨迹控制

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-19 DOI: 10.1016/j.mechatronics.2025.103360

Xuan Dung To , Jefferson Roman Blanco , Sandra Zimmer-Chevret , Ghinwa Ouaidat , Thibaut Raharijaona , Farid Noureddine , Micky Rakotondrabe

In Robotized Incremental Sheet Forming (ISF), achieving precise geometrical accuracy is a challenging task due to trajectory tool center point (TCP) position errors at the forming tool attached to the robot’s end-effector. These errors primarily arise from external disturbance forces and torques generated during the interaction between the forming tool and the elastic metal sheet. While joint-torque space controllers can mitigate reaction forces and torques through dynamic modeling, joint-space control has inherent limitations, particularly for industrial high-load robots like the ABB IRB 8700. To overcome these challenges, this work implements an external force/torque (F/T) compensator in task-space using a deep neural network. The network predicts trajectory errors induced by reaction forces and torques measured via a 6-axis F/T sensor. Additionally, the forming tool’s trajectory is precisely monitored using a laser tracker, which serves as a feedback mechanism in a closed-loop task-space error-tracking controller. This controller detects and corrects trajectory deviations in real time. By integrating the F/T compensator and the task-space error-tracking controller, the proposed approach effectively compensates for reaction forces and torques while addressing additional errors introduced by other process-related factors. This integration results in significantly enhanced accuracy in robotic incremental forming processes.

在机器人增量成形（ISF）中，由于机器人末端执行器上的成形工具存在轨迹刀具中心点（TCP）位置误差，实现精确的几何精度是一项具有挑战性的任务。这些误差主要是由成形工具与弹性金属板相互作用过程中产生的外部扰动力和扭矩引起的。虽然关节-扭矩空间控制器可以通过动态建模来减轻反作用力和扭矩，但关节-空间控制具有固有的局限性，特别是对于像ABB IRB 8700这样的工业高负载机器人。为了克服这些挑战，本工作使用深度神经网络在任务空间中实现了外部力/扭矩（F/T）补偿器。该网络预测由反作用力和通过6轴F/T传感器测量的扭矩引起的轨迹误差。此外，使用激光跟踪器精确监测成形工具的轨迹，该跟踪器作为闭环任务空间误差跟踪控制器中的反馈机制。该控制器实时检测和纠正轨迹偏差。通过集成F/T补偿器和任务空间误差跟踪控制器，该方法有效地补偿了反作用力和扭矩，同时解决了由其他过程相关因素引入的附加误差。这种集成结果显著提高了机器人增量成形过程的精度。

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引用次数: 0

Adaptive backstepping finite-time output feedback control for path tracking of autonomous vehicle with asymmetric dead-zone 非对称死区自动驾驶汽车路径跟踪的自适应反演有限时间输出反馈控制

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-17 DOI: 10.1016/j.mechatronics.2025.103362

Sucai Zhang , Yongfu Wang , Gang Li

A finite time adaptive output feedback control scheme with state constraint is proposed for the path tracking control of autonomous vehicle considering the asymmetric dead-zone. Firstly, the vehicle dynamics model and path tracking model are established by combining the dead-zone model, and the adaptive law is designed to approximate the parameters of dead-zone model. On this basis, an adaptive backstepping controller with output-constrained feedback control is designed by combining the filtering error compensation mechanism and the finite time technique, introducing the barrier Lyapunov function and the backstepping control technique. In order to save communication resources, a dynamic threshold event triggering mechanism is introduced. Finally, a rigorous stability analysis based on Lyapunov stability theory is presented to ensure that all signals of the closed-loop system are bounded in finite time. The effectiveness of the proposed method is verified by different simulations, hardware-in-the-loop experiments and real-time vehicle experiments. The results show that the proposed method is effective under different working conditions. The results of real-time vehicle experiments show that the controller can effectively improve the accuracy of path tracking control and reduce the maximum lateral position error to 0.1752 m compared with other methods, and the scheme can provide a theoretical reference for the control practice of autonomous vehicle.

针对非对称死区问题，提出了一种带状态约束的有限时间自适应输出反馈控制方案。首先，结合死区模型建立车辆动力学模型和路径跟踪模型，设计自适应律逼近死区模型参数；在此基础上，将滤波误差补偿机制与有限时间技术相结合，引入势垒Lyapunov函数和反演控制技术，设计了具有输出约束反馈控制的自适应反演控制器。为了节省通信资源，引入了动态门限事件触发机制。最后，基于李雅普诺夫稳定性理论进行了严格的稳定性分析，以保证闭环系统的所有信号在有限时间内是有界的。通过不同的仿真、硬件在环实验和实时车辆实验验证了该方法的有效性。结果表明，该方法在不同工况下都是有效的。实时车辆实验结果表明，与其他方法相比，该控制器能有效提高路径跟踪控制精度，最大横向位置误差降至0.1752 m，该方案可为自动驾驶车辆的控制实践提供理论参考。

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引用次数: 0

Dynamics modeling and μ synthesis for a parallel - suspension type inertially stabilized platform 并联悬架型惯性稳定平台动力学建模与μ综合

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-16 DOI: 10.1016/j.mechatronics.2025.103363

Yin Sun, Feng Zhao, Zhenjing Guo, Xiaojun Yan

The parallel-suspension type inertially stabilized platform utilizes a unique flexible support structure and non-contact linear actuators to enable simultaneous high-efficiency vibration suppression control of optical payloads across multiple degrees of freedom. Compared to traditional series – gimbals type stabilized platforms, it offers a higher payload-to-weight ratio and rapid response characteristics. In this paper, a 6-degree-of-freedom dynamic model for the parallel-suspension inertially stabilized platform is established, a control method is designed, and an actual engineering prototype is constructed. Specifically, a flexible support element model that accounts for column instability phenomenon is developed. Based on the parallel mount configuration a complete 6-degree-of-freedom dynamic model of the entire platform is constructed. Furthermore, due the variable parameter characteristics of flexible elastic elements, a μ synthesis control method considering the uncertainty of model parameters is designed. The experimental results show that the μ controller can effectively reduce the external sinusoidal angular disturbance to less than 25 % and the linear vibration disturbance to less than 3 % of the original disturbance while maintaining the robustness. Both simulation and experimental results verify the correctness and effectiveness of the proposed model and method.

并联悬架式惯性稳定平台采用独特的柔性支撑结构和非接触式线性致动器，可同时对多个自由度的光学有效载荷进行高效抑振控制。与传统的串联万向节型稳定平台相比，它具有更高的有效载荷重量比和快速响应特性。本文建立了并联悬架惯性稳定平台的6自由度动力学模型，设计了控制方法，并构建了实际工程样机。具体而言，建立了考虑柱失稳现象的柔性支撑单元模型。在并联安装结构的基础上，建立了整个平台完整的六自由度动力学模型。此外，针对柔性弹性元件的变参数特性，设计了一种考虑模型参数不确定性的μ综合控制方法。实验结果表明，该控制器在保持鲁棒性的同时，能有效地将外部正弦角扰动和线性振动扰动分别降低到原扰动的25%和3%以下。仿真和实验结果验证了所提模型和方法的正确性和有效性。

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引用次数: 0

A robust feedback-linearization MPC with artificial target for UGVs 基于人工目标的ugv鲁棒反馈线性化MPC

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-14 DOI: 10.1016/j.mechatronics.2025.103358

Bruno S.S. Pereira , Tito L.M. Santos , Andre G.S. Conceicao

This paper proposes a new robust feedback-linearization MPC for a class of Unmanned Ground Vehicles. A robust MPC for trajectory tracking with an artificial target is combined with a suitable constraint mapping to ensure robust constraint satisfaction and recursive feasibility despite the effect of bounded disturbances. The artificial reference provides a potentially enlarged domain of attraction, and an analytical target modification is used to achieve the convergence of the tracking error to a minimal robust positively invariant set. The feedback-linearization trade-off concerning the transformed constraints is also analyzed. A case study demonstrating the control strategy’s performance is presented using the Clearpath Husky A200 UGV and the OptiTrack motion capture system.

针对一类无人地面车辆，提出了一种新的鲁棒反馈线性化MPC。结合合适的约束映射，提出了一种用于人工目标轨迹跟踪的鲁棒MPC，以保证鲁棒约束的满足和在有界扰动影响下的递归可行性。人工参考提供了一个潜在的扩大吸引域，并使用解析目标修正来实现跟踪误差收敛到最小鲁棒正不变集。分析了变换约束下的反馈-线性化权衡问题。以Clearpath Husky A200 UGV和OptiTrack运动捕捉系统为例，展示了该控制策略的性能。

引用次数: 0

Comfort-enhanced longitudinal control for DDEVs: A robust brake coordination approach leveraging reactive anti-dive forces DDEVs纵向舒适控制：一种利用反俯冲力的稳健制动协调方法

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-14 DOI: 10.1016/j.mechatronics.2025.103357

Yanjun Ren , Tong Shen , Mingzhuo Zhao , Fanxun Wang , Liwei Xu , Guodong Yin

Distributed drive electric vehicles actuated by in-wheel motors and brake-by-wire systems enable tracking target motion while improving extra vehicle performance. Outboard brake torque allocated on front and rear wheels generates diverse vertically reactive anti-dive forces, providing an innovative approach to mitigate brake dive without requiring active suspensions. However, the differing dynamics of regenerative and hydraulic braking, along with multiple uncertain vehicle parameters, pose significant challenges to achieving robustness under mixed uncertainties. Moreover, pitch-induced bias in onboard acceleration measurements further degrades control accuracy. To address above problems, this paper proposes a robust, comfort-enhanced longitudinal control system with coordinated braking. A three-degree-of-freedom vehicle dynamics model is developed to incorporate the effect of anti-dive forces. For accurate feedback, a robust

H_{2} / H_{\infty}

observer is designed to compensate pitch-variation-related acceleration measurement biases. By integrating dynamic and parametric uncertainties into the control-oriented model, the mixed

μ

-synthesis is employed to design a two-degree-of-freedom controller to robustly optimize the acceleration tracking and anti-dive performance. Compared to the controller designed by standard

μ

-synthesis, the proposed approach achieves a 10% improvement in robust performance. Real-vehicle experiments validate the system’s effectiveness, demonstrating over a 27% reduction in pitch angle while maintaining satisfactory acceleration responses under blended braking conditions.

分布式驱动电动汽车由轮内电机和线控制动系统驱动，能够跟踪目标运动，同时提高车辆的额外性能。分配在前轮和后轮上的外侧制动扭矩产生不同的垂直反俯冲力，提供了一种在不需要主动悬架的情况下减轻制动俯冲的创新方法。然而，再生制动和液压制动的不同动力学特性，以及多种不确定的车辆参数，对实现混合不确定性下的鲁棒性提出了重大挑战。此外，机载加速度测量中的俯仰引起的偏差进一步降低了控制精度。为了解决上述问题，本文提出了一种鲁棒性、舒适性增强的纵向协调制动控制系统。建立了考虑抗俯冲力影响的三自由度飞行器动力学模型。为了获得准确的反馈，设计了一个鲁棒H2/H∞观测器来补偿与俯仰变化相关的加速度测量偏差。通过将动态不确定性和参数不确定性集成到面向控制的模型中，采用混合μ综合方法设计了二自由度控制器，对加速度跟踪和抗俯冲性能进行了鲁棒优化。与采用标准μ合成方法设计的控制器相比，该方法的鲁棒性能提高了10%。实车试验验证了该系统的有效性，表明在混合制动条件下，俯仰角降低了27%以上，同时保持了令人满意的加速响应。

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引用次数: 0

Machine learning for automation of 3-DoF control of magnetically-levitated microrobots 基于机器学习的磁悬浮微型机器人三自由度控制自动化

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-11 DOI: 10.1016/j.mechatronics.2025.103356

Joseph Nofech, Mir Behrad Khamesee

This study presents a novel methodology for achieving three-degree-of-freedom (3-DoF) control for an attractive-type magnetically-levitated (maglev) microrobot using machine learning. Contact micromanipulation methods face challenges associated with friction, backlash, and maintenance requirements; particularly in delicate applications such as cell injection. The frictionless and low-maintenance nature of attractive-type maglev makes it a viable alternative to traditional methods, but achieving precise 3-DoF control for such systems is not straightforward due to the complexity of their magnetic fields. This research addresses this problem by introducing a machine learning-based methodology that automates the learning of levitation dynamics across the workspace, effectively bypassing a major challenge associated with cross-disciplinary applications of attractive-type maglev.

Our presented approach introduces an automated system for generating training data with minimal human intervention, allowing a machine learning model to quantify the levitated microrobot’s physical response to system inputs while accounting for position-dependent variations in levitation dynamics across the workspace. This model is then used to establish 3-DoF position control of the levitated microrobot. In addition to simplifying the setup process for new and newly-modified attractive-type levitation platforms, this new data-driven methodology is demonstrated to improve performance over conventional methods; achieving up to a 20% reduction in root mean square error during trajectory tracking and up to a 36% reduction in step response settling times.

The results demonstrate the ability of our automated methodology to significantly reduce the accessibility barriers associated with establishing and modifying attractive-type maglev platforms; effectively replacing the usual methods of finite element simulation, precise magnetic field measurements, and/or analytical calculations while providing enhanced levitation control over traditional methods. This advancement contributes to the field of micromanipulation and microforce sensing by offering a more accessible and efficient approach to achieving precise control in attractive-type maglev systems.

本研究提出了一种利用机器学习实现吸引型磁悬浮微型机器人三自由度控制的新方法。接触微操作方法面临与摩擦、间隙和维护要求相关的挑战；特别是在精细的应用，如细胞注射。吸引型磁悬浮的无摩擦和低维护特性使其成为传统方法的可行替代方案，但由于其磁场的复杂性，为此类系统实现精确的3-DoF控制并不简单。这项研究通过引入一种基于机器学习的方法来解决这个问题，该方法可以自动学习整个工作空间的悬浮动力学，有效地绕过了与吸引型磁悬浮的跨学科应用相关的主要挑战。我们提出的方法引入了一个自动化系统，以最少的人为干预生成训练数据，允许机器学习模型量化悬浮微型机器人对系统输入的物理响应，同时考虑整个工作空间中悬浮动力学的位置相关变化。然后利用该模型建立悬浮微型机器人的三自由度位置控制。除了简化新的和新修改的吸引力型悬浮平台的设置过程外，这种新的数据驱动方法被证明比传统方法提高了性能；在轨迹跟踪过程中，均方根误差减少20%，阶跃响应稳定时间减少36%。结果表明，我们的自动化方法能够显著减少与建立和修改吸引型磁悬浮平台相关的可达性障碍；有效地取代了通常的有限元模拟、精确磁场测量和/或分析计算方法，同时提供了比传统方法更好的悬浮控制。这一进展有助于微操作和微力传感领域，为实现吸引型磁悬浮系统的精确控制提供了更方便和有效的方法。

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引用次数: 0

Modeling and prediction of nonlinear cable slab dynamics using Koopman operators 基于Koopman算子的非线性索板动力学建模与预测

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-07 DOI: 10.1016/j.mechatronics.2025.103353

Michael Pumphrey , Almuatazbellah M. Boker , Mohammad Al Saaideh , Natheer Alatawneh , Yazan M. Al-Rawashdeh , Khaled Aljanaideh , Mohammad Al Janaideh

A novel approach for modeling the nonlinear dynamics of cable slabs using Koopman operator theory is presented. Cable slab dynamics are a critical challenge in precision motion systems, as the cables can induce undesired vibrations and disturbances on motion stages. To address this, a higher-dimensional state-space model with nonlinear observable functions is developed to approximate the cable slab dynamics. The proposed model achieves a prediction error within

\sim 1

% over the specified motion range and demonstrates robustness in predicting untrained, randomized, acyclic cable slab motions. A systematic evaluation of various observable functions was conducted to minimize the modeling errors, leading to an optimized model with fractional-order exponents. When compared with a neural network-based state-space model (NN-SS), the Koopman approach demonstrated faster training and better performance. For force prediction, the Koopman approach achieved a reduction of three-quarters in maximum error when compared with the NN-SS method. This work offers a concise and experimentally validated analytical framework specifically for developing accurate predictive models of nonlinear cable slab dynamics.

提出了一种利用库普曼算子理论建立索板非线性动力学模型的新方法。电缆板动力学是精密运动系统的一个关键挑战，因为电缆会在运动阶段引起不希望的振动和干扰。为了解决这个问题，建立了一个具有非线性可观测函数的高维状态空间模型来近似索板的动力学。所提出的模型在指定运动范围内的预测误差在1%以内，并且在预测未经训练的、随机的、无循环的电缆板运动方面表现出鲁棒性。通过对各种可观测函数进行系统评估，使建模误差最小化，得到分数阶指数优化模型。与基于神经网络的状态空间模型（NN-SS）相比，Koopman方法表现出更快的训练速度和更好的性能。对于力预测，与NN-SS方法相比，Koopman方法实现了最大误差减少四分之三。这项工作提供了一个简明的和实验验证的分析框架，专门为开发准确的非线性索板动力学预测模型。

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引用次数: 0

Residual vibration suppression of large-size flexible hydraulic manipulator under external disturbance with accurate positioning 基于精确定位的大型柔性液压机械臂外部扰动残余振动抑制

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-04 DOI: 10.1016/j.mechatronics.2025.103355

Min Cheng , Xin Zhang , Ruqi Ding , Junhui Zhang , Bing Xu

To reduce residual vibration with accurate positioning for a flexible hydraulic manipulator, this paper proposes a dual-impulse vibration suppression method to implement concrete pumping tasks. Through sealing up the load-bearing chamber and allow fluid exchange in the non-bearing chamber by individual metering control (IMC), a valve-based volume control method without position sensors is proposed to replace direct positioning control of the end point. Besides, a dual-impulse valve controller is designed for making an online tradeoff between vibration suppression and accurate positioning under a specific pumping posture. Based on only pressure feedback, the amplitude and the time width of the two impulses are determined via system identification in advance and vibration prediction in real-time. Experimental tests are carried out using a 13m-length hydraulic manipulator under three different postures. The test results show that the vibration caused by disturbance can be effectively reduced using the proposed method, and more importantly the position of the end point can be maintained accurately.

针对柔性液压机械臂在精确定位的前提下减少残余振动的问题，提出了一种实现混凝土泵送任务的双脉冲振动抑制方法。通过密封承载腔体，通过单独的计量控制（IMC）实现非承载腔体的流体交换，提出了一种基于阀门的无位置传感器容积控制方法，以取代终点的直接定位控制。此外，设计了双脉冲阀控制器，在特定泵送姿态下实现了振动抑制与精确定位的在线权衡。仅在压力反馈的基础上，通过系统的提前识别和实时振动预测来确定两个脉冲的幅值和时宽。利用长度为13m的液压机械手在三种不同的姿态下进行了实验测试。试验结果表明，采用该方法可以有效地减小扰动引起的振动，更重要的是可以准确地保持终点的位置。

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引用次数: 0

Modeling and feedforward control of hysteresis in piezoelectric actuators considering its rotation and expansion 考虑旋转和膨胀的压电作动器迟滞建模及前馈控制

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-06-04 DOI: 10.1016/j.mechatronics.2025.103354

Yunzhi Zhang , Jie Ling , Micky Rakotondrabe , Yuchuan Zhu , Dan Wang

Piezoelectric actuators (PEAs) play a key role in precision engineering, but their strong rate-dependent hysteresis affects accuracy. Existing hysteresis models fail to capture the simultaneous rotation and expansion of hysteresis at high rates. This paper proposes a modified Prandtl–Ishlinskii model in a Hammerstein-like architecture (HAMPI) aiming to model the rotation and expansion of the hysteresis at different input rates. Simulations and experiments are conducted to validate the HAMPI model across a wide range of input rates (50–500 Hz) and amplitudes (0–140 V), revealing that the proposed model has the root-mean-square error (resp. relative root-mean-square error) of 0.47

μ

m (resp. 3.07%), which is lower than the results of existing hysteresis model. Additionally, a HAMPI-based feedforward controller with the inverse multiplicative structure shows that the tracking performance RMS error (resp. NRMS error) can be kept within 0.09

μ

m (resp. 2.25%) when the operating frequency is below 150 Hz. Meanwhile, the displacement attenuation issue in feedforward control caused by the rate-dependent rotation of hysteresis loops is also successfully addressed by the proposed HAMPI model.

压电作动器在精密工程中起着关键作用，但其较强的速率滞后影响了其精度。现有的迟滞模型无法捕捉到同时高速旋转和膨胀的迟滞。本文提出了一种改进的Hammerstein-like结构（HAMPI）中的Prandtl-Ishlinskii模型，旨在模拟不同输入速率下迟滞的旋转和扩展。通过仿真和实验验证了HAMPI模型在宽输入速率（50-500 Hz）和振幅（0-140 V）范围内的有效性，结果表明所提出的模型具有均方根误差(resp。相对均方根误差为0.47 μm。3.07%)，低于现有滞回模型的结果。此外，基于hampi的逆乘结构前馈控制器表明，该控制器的跟踪性能均方根误差(RMS error, p。NRMS误差)可控制在0.09 μm以内。2.25%)，当工作频率低于150hz时。同时，所提出的HAMPI模型也成功地解决了前馈控制中由迟滞环的速率相关旋转引起的位移衰减问题。

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引用次数: 0

Adaptive model-free control for ankle-assistive orthosis: A robust approach to real-time gait tracking 踝关节辅助矫形器的自适应无模型控制：实时步态跟踪的鲁棒方法

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics

Pub Date : 2025-05-30 DOI: 10.1016/j.mechatronics.2025.103341

Oussama Bey, Yacine Amirat, Samer Mohammed

Actuated Ankle-Foot Orthoses (AAFOs) assist dorsiflexion and plantarflexion movements at the ankle joint, supporting mobility and rehabilitation by complementing the wearer’s residual muscular activity within an assist-as-needed paradigm. Their effectiveness depends on advanced control strategies and accurate modeling of the coupled human-AAFO dynamics, which remains a challenging task. This paper presents a novel assist-as-needed control approach for an AAFO/wearer system based on an adaptive model-free framework, without the need for a dynamic model of the AAFO/wearer system. The proposed approach uses an ultra-local model, wherein a intelligent projection-based adaptive PID (iA-PID) controller is designed to achieve satisfactory tracking of a reference ankle joint trajectory. External torques affecting the AAFO/wearer system are estimated using a time-delay estimator and are compensated within the iPA-PID controller to ensure assist-as-needed control. Additionally, the projection operator constrains the evolution of the adaptive parameters, preventing actuator saturation and enabling controlled assistance delivery. Finite-time stability of the resulting closed-loop system is proven, and the final value theorem ensures that the tracking error converges to zero. The performance of the proposed approach is evaluated through simulations and real-time experiments with four healthy subjects. A comparison of tracking performance with several benchmark approaches was conducted as well as robustness tests under varying walking speeds to confirm the effectiveness and reliability of the proposed control approach.

驱动式踝足矫形器（AAFOs）辅助踝关节的背屈和跖屈运动，通过补充佩戴者的剩余肌肉活动，在需要的辅助模式下支持活动和康复。它们的有效性取决于先进的控制策略和精确的人- aafo耦合动力学建模，这仍然是一个具有挑战性的任务。本文提出了一种基于自适应无模型框架的AAFO/佩戴者系统的随需辅助控制方法，该方法无需AAFO/佩戴者系统的动态模型。该方法采用超局部模型，设计了基于智能投影的自适应PID （iA-PID）控制器，实现了对参考踝关节轨迹的满意跟踪。影响AAFO/佩戴者系统的外部扭矩使用时滞估计器进行估计，并在iPA-PID控制器内进行补偿，以确保根据需要进行辅助控制。此外，投影算子限制了自适应参数的演变，防止执行器饱和，实现可控的辅助交付。证明了闭环系统的有限时间稳定性，并利用终值定理保证了跟踪误差收敛于零。通过四名健康受试者的仿真和实时实验，对该方法的性能进行了评估。通过与几种基准方法的跟踪性能比较以及不同行走速度下的鲁棒性测试，验证了所提控制方法的有效性和可靠性。

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引用次数: 0