Control Engineering Practice最新文献

英文中文

Robust adaptive dynamic control of electromagnetically actuated soft-tethered robots for medical intervention 用于医疗干预的电磁致动软系机器人的鲁棒自适应动态控制

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-05 DOI: 10.1016/j.conengprac.2024.106107

Chengxiang Liu , Yehui Li , Zhiwei Cui , Heng Zhang , Yichong Sun , Zheng Li

Electromagnetically actuated soft-tethered robots (EASTRs) exhibit significant potential for medical intervention applications due to their compact size and minimal invasiveness. However, their inherent nonlinear behavior and susceptibility to unexpected disturbances present challenges for achieving robust control performance. To address this issue, in this paper, a dynamic model for EASTRs is first established, which encompasses the actuation model of the magnetic tip and the dynamic model of the soft tether. Subsequently, a robust adaptive dynamic controller is designed to compensate for the inaccuracy of the established dynamic model, thus ensuring robust control performance. The proposed approach integrates adaptive laws based on the Lyapunov method to effectively handle time-varying parameters and disturbances. Experimental results present an excellent control accuracy of the proposed scheme in trajectory tracking tasks, showcasing its superior performance compared to passive schemes and classical proportional–derivative control. This research contributes valuable insights into advancing the control capabilities of EASTRs for diverse applications in medical practices.

电磁致动软系留机器人（EASTR）因其体积小巧、侵入性极低，在医疗干预应用中展现出巨大的潜力。然而，它们固有的非线性行为和对意外干扰的敏感性为实现稳健的控制性能带来了挑战。为解决这一问题，本文首先建立了 EASTR 的动态模型，其中包括磁头的致动模型和软系绳的动态模型。随后，设计了一种稳健的自适应动态控制器，以补偿所建立动态模型的不准确性，从而确保稳健的控制性能。所提出的方法集成了基于 Lyapunov 方法的自适应法则，可有效处理时变参数和干扰。实验结果表明，在轨迹跟踪任务中，所提出的方案具有出色的控制精度，与被动方案和经典的比例-衍生控制相比，性能更加优越。这项研究为提高 EASTR 在医疗实践中各种应用的控制能力提供了宝贵的见解。

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引用次数: 0

On the selection of control structures using process operability analysis 利用过程可操作性分析选择控制结构

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-05 DOI: 10.1016/j.conengprac.2024.106117

Victor Alves, Fernando V. Lima

This work aims to develop a generalizable framework for control structure selection using process operability analysis. Current approaches for selecting controlled variables in chemical processes are limited to assessing system attributes individually, focusing on controller performance or the economic impact based on a constant setpoint policy. However, the competitive industrial manufacturing market requires a holistic approach for control structure selection in large-scale plants that takes into account multiple factors. In particular, process operability can help to enable a generalizable approach that is able to select control structures that are operable considering economic and performance factors simultaneously. To achieve this goal, a framework that uses the Operability Index (OI) as a metric for ranking the achievability of the control objectives for the selected control structures is developed. To test the framework, a depropanizer distillation column is investigated as a case study associated with large-scale energy systems. This work thus introduces novel formulations and algorithms for the control structure selection problem, enhancing the design, operations, and synthesis of existing and future industrial systems.

这项工作旨在利用过程可操作性分析为控制结构选择开发一个通用框架。目前在化工过程中选择受控变量的方法仅限于单独评估系统属性，重点关注控制器性能或基于恒定设定点策略的经济影响。然而，在竞争激烈的工业制造市场中，大规模工厂的控制结构选择需要综合考虑多种因素。特别是，过程可操作性有助于实现一种通用方法，能够同时考虑经济和性能因素，选择可操作的控制结构。为了实现这一目标，我们开发了一个框架，使用可操作性指数（OI）作为衡量标准，对所选控制结构的控制目标的可实现性进行排序。为了测试该框架，我们将脱丙烷精馏塔作为与大型能源系统相关的案例进行了研究。因此，这项工作为控制结构选择问题引入了新的公式和算法，从而提高了现有和未来工业系统的设计、运行和综合能力。

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引用次数: 0

Robust adaptive PID control of functional electrical stimulation for drop-foot correction 功能性电刺激的鲁棒自适应 PID 控制，用于足下垂矫正

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-04 DOI: 10.1016/j.conengprac.2024.106090

Ghazal Tanhaei , Hamed Habibi , William Holderbaum , Noureddin Nakhostin Ansari

A robust, adaptive proportional–integral–derivative (PID) control strategy is presented for controlling ankle movement using a functional electrical stimulation (FES) neuroprosthesis. The presented control strategy leverages the structurally simple PID controller. Moreover, the proposed PID controller automatically tunes its gains without requiring prior knowledge of the musculoskeletal system. Thus, in contrast to previously proposed control strategies for FES, the proposed controller does not necessitate time-consuming model identification for each patient. Additionally, the computational cost of the controller is minimized by linking the PID gains and updating only the common gain. As a result, a model-free, structurally simple, and computationally inexpensive controller is achieved, making it suitable for wearable FES-based neuroprostheses. A Lyapunov stability analysis proves uniformly ultimately bounded (UUB) tracking of the joint angle. Results from the simulated and experimental trials indicate that the proposed PID controller demonstrates high tracking accuracy and fast convergence.

本文介绍了一种稳健的自适应比例积分派生（PID）控制策略，用于使用功能性电刺激（FES）神经假体控制踝关节运动。所提出的控制策略利用了结构简单的 PID 控制器。此外，所提出的 PID 控制器可自动调整其增益，而无需事先了解肌肉骨骼系统。因此，与之前提出的 FES 控制策略相比，所提出的控制器无需对每位患者进行耗时的模型识别。此外，通过连接 PID 增益并只更新公共增益，控制器的计算成本也降到了最低。因此，我们实现了一种无模型、结构简单、计算成本低廉的控制器，使其适用于基于 FES 的可穿戴式神经义肢。Lyapunov 稳定性分析证明了对关节角度的均匀最终有界（UUB）跟踪。模拟和实验结果表明，所提出的 PID 控制器跟踪精度高，收敛速度快。

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引用次数: 0

Adaptive tracking control method for shearer cutting trajectory based on the combined strategy 基于组合策略的剪板机切割轨迹自适应跟踪控制方法

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-04 DOI: 10.1016/j.conengprac.2024.106116

Dong Wei , Houzhe Wang , Xia Liu , Xin Li , Jinheng Gu , Xiaoyu Zou , Chao Tan , Lei Si

Adaptive tracking control method for shearer remains challenging caused by the contradiction between coal recovery rate and equipment safety under current technological limitations, has drawn more and more attention over the past decades due to its important role in reducing personnel, increasing safety, and improving efficiency for underground mining. Therefore, a novel adaptive tracking control method for shearer cutting trajectory based on the combined strategy is proposed, whose core is the switching method of the sub-strategies based on the linear quadratic regulator (LQR) and error band control (EBC) with switching threshold determined by the Multi-strategy Marine Predator Algorithm. The performance of the proposed method is demonstrated by comparing with the existing methods reported. The experimental results reveal that the proposed method maintains a high recovery rate while improving coal mining efficiency.

在目前的技术条件下，煤炭回收率与设备安全性之间的矛盾所导致的剪板机自适应跟踪控制方法仍然具有挑战性，由于其在井下采矿中减少人员、增加安全性和提高效率方面的重要作用，在过去几十年中引起了越来越多的关注。因此，本文提出了一种基于组合策略的新型剪切机切割轨迹自适应跟踪控制方法，其核心是基于线性二次调节器（LQR）和误差带控制（EBC）的子策略切换方法，切换阈值由多策略海洋捕食者算法确定。通过与现有方法的比较，证明了所提方法的性能。实验结果表明，所提方法在提高采煤效率的同时，还保持了较高的回收率。

引用次数: 0

Robust motion control for an underactuated wheeled bipedal robot utilizing sliding mode strategy 利用滑动模式策略实现欠驱动轮式双足机器人的鲁棒运动控制

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-03 DOI: 10.1016/j.conengprac.2024.106108

Biao Lu , Haixin Cao , Yongchun Fang , Jing Zhang , Yunsong Hao

In recent years, wheeled bipedal robots (WBRs) have become one of the frontier fields of robotic research, attracting immense interest from scholars globally. They can not only move rapidly on flat ground through wheels but also possess satisfactory adaptability to uneven terrain due to the introduction of legs. With concise structure and strong agility, WBRs have broad prospects of application in logistics, routing inspection, home service, and so on. However, the inherent underactuation of such robots presents a significant challenge in terms of balance control, particularly in the face of uncertainties and external disturbances. To address this problem, this paper presents a sliding mode control strategy for WBRs, which guarantees robust balance performance even under the influence of various external disturbances. Specifically, the dynamic equations of WBRs are first rearranged in cascaded form, facilitating targeted control design. After that, the wheel torque and leg supporting force are carefully devised to ensure that the sliding surfaces converge to zero within a fixed time. Rigorous Lyapunov-based analysis has shown that the desired equilibrium point is asymptotically stable. Finally, extensive hardware experiments are undertaken, providing convincing evidence of the superior balance control performance achieved by the proposed method.

近年来，轮式双足机器人（WBR）已成为机器人研究的前沿领域之一，吸引了全球学者的极大兴趣。它们不仅能通过轮子在平地上快速移动，而且由于引入了腿，对不平坦地形的适应性也令人满意。由于结构简洁、灵活性强，WBR 在物流、路由检测、家政服务等领域有着广阔的应用前景。然而，这类机器人固有的动力不足问题给平衡控制带来了巨大挑战，尤其是在面对不确定性和外部干扰时。为解决这一问题，本文提出了一种用于 WBR 的滑模控制策略，即使在各种外部干扰的影响下，也能保证稳健的平衡性能。具体来说，首先以级联形式重新排列 WBR 的动态方程，便于进行有针对性的控制设计。然后，精心设计车轮扭矩和支腿支撑力，确保滑动面在固定时间内趋于零。基于 Lyapunov 的严格分析表明，理想的平衡点是渐近稳定的。最后，还进行了大量的硬件实验，令人信服地证明了拟议方法所实现的卓越平衡控制性能。

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引用次数: 0

Combined simple adaptive and integral terminal sliding mode control for industrial feed drive systems 用于工业给料驱动系统的简单自适应和积分终端滑动模式组合控制

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-02 DOI: 10.1016/j.conengprac.2024.106109

Haryson Johanes Nyobuya , Naoki Uchiyama

In the manufacturing industry, feed drive systems are utilized for various applications in industrial machines. These systems are crucial components for ensuring precision in motion control and are, therefore, expected to offer high tracking performance. This study focuses on application of integral terminal sliding mode control (ITSMC) to a feed drive system because of its robustness against disturbances and convergence of the tracking error in finite-time. However, its design requires plant dynamics model. To alleviate this concern, a solution of modifying the original ITSMC law to adaptive ITSMC law based on simple adaptive control (SAC) technique is used. To implement SAC-like adaptive law to a real plant, a property of “almost strictly positive real (ASPR)” is required to be satisfied. ASPR property is satisfied using velocity-based augmented output signal that ensures the stability. In experimental results, the adaptive controller follows the reference trajectory more precisely than conventional methods.

在制造业中，进给驱动系统被用于工业机器的各种应用中。这些系统是确保运动控制精度的关键部件，因此有望提供较高的跟踪性能。本研究的重点是在进给驱动系统中应用积分终端滑动模式控制（ITSMC），因为它具有抗干扰能力强、跟踪误差在有限时间内收敛的特点。然而，其设计需要工厂动力学模型。为了缓解这一问题，我们采用了一种基于简单自适应控制（SAC）技术的解决方案，将原始 ITSMC 法则修改为自适应 ITSMC 法则。要在实际工厂中实施类似 SAC 的自适应法则，必须满足 "几乎严格正实数（ASPR）"的属性。基于速度的增强输出信号可确保稳定性，从而满足 ASPR 特性。在实验结果中，自适应控制器比传统方法更精确地遵循参考轨迹。

引用次数: 0

Multi-phase weighted stator current tracking using a hyper-plane partition of the control set 利用控制集的超平面分割进行多相加权定子电流跟踪

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-02 DOI: 10.1016/j.conengprac.2024.106114

M.R. Arahal , M.G. Satué , F. Barrero

This paper presents a new optimization technique for Finite Control Set Model Predictive Control (FCS-MPC) of multi-phase induction machines. The proposal allows for a fast computation of the control signal while simultaneously considering stator currents in the

α - β

(torque producing) plane and the

x - y

(harmonics) plane. The combinatorial search of the optimization phase is eliminated. Also, unlike previous approaches, the proposed region identification algorithm can be utilized in conjunction with weighting factors in the cost function. The optimization is done using a hyper-plane partition of the control set. The partition provides the weighted FCS-MPC solution with significantly less computation needs allowing for shorter sampling periods. The method is tested experimentally in a 5-phase induction motor showing enhanced results.

本文针对多相感应电机的有限控制集模型预测控制（FCS-MPC）提出了一种新的优化技术。该建议允许快速计算控制信号，同时考虑 α-β（产生转矩）平面和 x-y（谐波）平面上的定子电流。这样就省去了优化阶段的组合搜索。此外，与以往方法不同的是，所提出的区域识别算法可与成本函数中的加权因子结合使用。优化是通过控制集的超平面分区完成的。该分区提供了加权 FCS-MPC 解决方案，大大减少了计算需求，从而缩短了采样周期。该方法在一台五相感应电机上进行了实验测试，结果显示效果更佳。

引用次数: 0

Fuzzy adaptive impedance control for the two-layered vertical cable-driven parallel robot 双层垂直缆索驱动并联机器人的模糊自适应阻抗控制

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-01 DOI: 10.1016/j.conengprac.2024.106110

Thanh-Hai Nguyen , Kwan-Woong Gwak

This study unveils a novel two-layered vertical octahedron cable-driven parallel robot (TLVO CDPR), distinctively engineered for effective force interactions with vertical surfaces while preventing collision with cables. It pioneers an innovative control strategy integrating a position-based fuzzy adaptive impedance controller with a fuzzy Proportional – Integral – Derivative (PID) controller, adeptly managing both the pose and contact force of the robot. While dual control application is often found in rigid-link robots, it remains a largely unexplored frontier in the realm of CDPRs, despite its critical importance in sectors like manufacturing and assembly. The fuzzy adaptive mechanism significantly boosts impedance control efficacy in the face of unpredictable, non-uniform working surfaces, ensuring algorithmic stability and convergence. Concurrently, fuzzy logic is harnessed to optimize PID controller performance. The forward kinematics challenge is efficiently tackled using a least squares method coupled with an Inertial Measurement Unit (IMU), ensuring swift and precise solutions. The robustness and adaptability of the robot and its control systems are thoroughly validated through extensive experimental trials, involving diverse trajectories and varying uncertainties on vertical working surfaces.

本研究揭示了一种新型双层垂直八面体缆索驱动并联机器人（TLVO CDPR），其独特的设计可与垂直表面进行有效的力交互，同时防止与缆索发生碰撞。它首创了一种创新控制策略，将基于位置的模糊自适应阻抗控制器与模糊比例-积分-微分（PID）控制器集成在一起，对机器人的姿势和接触力进行了有效管理。虽然双控制应用通常出现在刚性连杆机器人中，但在 CDPR 领域，尽管它在制造和装配等行业中至关重要，但在很大程度上仍是一个尚未开发的前沿领域。面对不可预测、不均匀的工作表面，模糊自适应机制大大提高了阻抗控制的功效，确保了算法的稳定性和收敛性。同时，还利用模糊逻辑优化了 PID 控制器的性能。采用最小二乘法与惯性测量单元（IMU）相结合，有效地解决了前向运动学难题，确保了快速、精确的解决方案。机器人及其控制系统的鲁棒性和适应性通过广泛的实验测试得到了充分验证，包括垂直工作表面上的各种轨迹和不同的不确定性。

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引用次数: 0

Selection of alarm deadbands and delay timers with their connections based on risk indicators for removing nuisance alarms 根据风险指标选择警报死区和延迟计时器及其连接，以消除骚扰警报

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-10-01 DOI: 10.1016/j.conengprac.2024.106113

Zheng Zhang, Jiandong Wang, Yan Qi

Alarm systems are crucial to the safety and efficiency of industrial processes, but they may be contaminated by massive nuisance alarms. Alarm deadbands and delay timers with their connections are often used to remove nuisance alarms. However, different process variables are with different characteristics of alarm events, so that it is necessary to determine which one of these alarm systems is the most appropriate for a given process variable. This paper proposes a method to select the most suitable alarm system for a given process variable, by formulating an indicator to evaluate the risk of missed abnormality detections. The technical challenge is about how to calculate the uncertainty of the risk indicator. The Bayesian estimation approach is utilized to yield confidence intervals of the risk indicator for addressing the technical challenge. The alarm system with the lowest risk indicator is chosen as the most appropriate one. Numerical and industrial examples are presented to support the proposed method.

报警系统对工业流程的安全和效率至关重要，但可能会受到大量骚扰报警的污染。报警死区和延迟定时器及其连接通常用于消除骚扰报警。然而，不同的过程变量具有不同的报警事件特征，因此有必要确定这些报警系统中哪一个最适合给定的过程变量。本文提出了一种为给定过程变量选择最合适报警系统的方法，通过制定一个指标来评估异常检测遗漏的风险。技术难题在于如何计算风险指标的不确定性。为解决这一技术难题，我们采用了贝叶斯估计方法来得出风险指标的置信区间。风险指标最低的报警系统被选为最合适的报警系统。为支持所提出的方法，介绍了数值和工业实例。

引用次数: 0

Data-driven adaptive and stable feature selection method for large-scale industrial systems 大规模工业系统的数据驱动自适应稳定特征选择方法

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-09-27 DOI: 10.1016/j.conengprac.2024.106097

Xiuli Zhu , Yan Song , Peng Wang , Ling Li , Zixuan Fu

Data-driven modeling is a crucial technology for the real-time monitoring of large-scale industrial systems. However, it often suffers from the redundancy of input variables, resulting in low prediction and modeling accuracy. To address this issue, a novel feature selection method, namely adaptive and stable feature selection based on a reference vector-guided evolutionary multi-objective optimization algorithm (ASFS-RVEA), is proposed in this paper. The proposed ASFS-RVEA comprehensively considers four important objectives: the number of features, prediction accuracy, the dissimilarity of selected features, and the mitigation of feature redundancy.Considering the interaction and conflict among these four objectives, a multi-objective optimization problem with an unknown Pareto front is formulated to find an optimal balance among them, thereby obtaining promising and convincing results. Furthermore, Jensen–shannon divergence (JSD) is introduced to the RreliefF algorithm to account for the data distribution information between various input features and key output variables, guiding population crossover and mutation. This greatly enhances the robustness of the algorithm when handling data with different distributions. Next, a reference vector adapting strategy is proposed to update the generation based on dynamically changing distributions, which helps accelerate convergence in the optimization process. Finally, experiments conducted on datasets collected from the Dow process and the polyester polymerization process demonstrate the effectiveness of the proposed ASFS-RVEA.

数据驱动建模是实时监控大规模工业系统的一项重要技术。然而，它往往受到输入变量冗余的影响，导致预测和建模精度较低。针对这一问题，本文提出了一种新颖的特征选择方法，即基于参考向量引导的进化多目标优化算法（ASFS-RVEA）的自适应稳定特征选择。考虑到这四个目标之间的相互作用和冲突，本文提出了一个具有未知帕累托前沿的多目标优化问题，以寻求它们之间的最佳平衡，从而获得了令人信服的结果。此外，在 RreliefF 算法中引入了 Jensen-shannon divergence (JSD)，以考虑各种输入特征和关键输出变量之间的数据分布信息，指导种群交叉和突变。这大大增强了算法在处理不同分布数据时的鲁棒性。接下来，我们提出了一种参考向量自适应策略，根据动态变化的分布更新生成量，这有助于加快优化过程的收敛速度。最后，对从陶氏化学过程和聚酯聚合过程中收集的数据集进行的实验证明了所提出的 ASFS-RVEA 的有效性。

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