Control Engineering Practice最新文献_第6页

Robust electro-hydraulic control for aircraft anti-skid systems with full validation from test bench to flight 稳健的电液控制飞机防滑系统，从试验台到飞行的全面验证

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-28 DOI: 10.1016/j.conengprac.2026.106814

José Joaquín Mendoza Lopetegui, Mara Tanelli

In modern aviation, anti-skid systems are fundamental in preventing wheel-locking conditions and maximizing braking performance. To achieve airworthiness, these systems must be robust, fault-tolerant, and comply with existing standards and regulations. Existing solutions fall short in addressing important aspects for a successful practical implementation, as testified by the lack of flight testing verification in the literature. This paper proposes a novel aircraft anti-skid system that leverages robust control techniques to enhance safety and performance. The proposed architecture integrates a fault-tolerant design that accounts for measurement noise, hydraulic system asymmetries, and pressure transducer faults, while maintaining stability despite uncertainties in the electro-hydraulic brake dynamics. A cascaded control structure combining robust pressure regulation with wheel deceleration control and supervisory logic enables resilient performance under varying operating conditions. The pressure controller’s stability is verified by a Kharitonov-type stability check, whereas the proposed gain-scheduled deceleration controller is analyzed under a Linear Parameter-Varying system formulation, checked for stability by a collection of Linear Matrix Inequalities under assumptions of rate-bounded variability of the involved parameters. The approach is validated on a hydraulic test bench, an aeronautic dynamometer, and flight test experiments, demonstrating practical applicability and alignment with the demands of modern hydraulic control systems.

在现代航空中，防滑系统是防止轮锁状况和最大化制动性能的基础。为了实现适航性，这些系统必须具有鲁棒性、容错性，并符合现有的标准和法规。现有的解决方案在解决成功的实际实施的重要方面不足，正如文献中缺乏飞行测试验证所证明的那样。本文提出了一种新的飞机防滑系统，利用鲁棒控制技术来提高安全性和性能。该架构集成了容错设计，考虑了测量噪声、液压系统不对称和压力传感器故障，同时在电液制动动力学不确定的情况下保持稳定性。级联控制结构将鲁棒压力调节与车轮减速控制和监督逻辑相结合，使其在不同的操作条件下具有弹性性能。通过kharitonov稳定性检验验证了压力控制器的稳定性，而在线性变参数系统公式下分析了所提出的增益调度减速控制器，并在相关参数的速率有界可变性假设下通过线性矩阵不等式的集合检查了稳定性。该方法在液压试验台、航空测功机和飞行试验中得到了验证，证明了该方法的实用性和符合现代液压控制系统的要求。

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引用次数: 0

Parallel robot with proprioceptive actuation for low-impedance sensorless pHRI 具有本体感觉驱动的并联机器人低阻抗无传感器pHRI

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-24 DOI: 10.1016/j.conengprac.2026.106800

Arda Yiğit , Simon Foucault , Thierry Laliberté , David Breton , Zhou Zhou , Clément Gosselin

This paper presents a kinematically redundant 9-DoF parallel robot engineered for seamless, sensorless physical human-robot interaction. The robot features three identical 3-DoF RU/2-RUS legs that connect a reconfigurable platform to the base via spherical joints. By configuring all actuators on the base, the robot achieves significantly lower moving mass and inertia. By employing backdrivable direct-drive motors, the system realizes proprioceptive actuation, enabling an intuitive, low-impedance, and high-bandwidth interaction. An impedance control strategy is developed on

SE (3) \times R^{3}

, and a stability analysis using singular perturbation theory highlights the crucial role of actuator dynamics and thus the significance of the choice of the actuation strategy. Experimental results confirm the robot’s stability, extended workspace, and effective human-robot interaction performance.

本文提出了一种运动冗余的9自由度并联机器人，用于无缝、无传感器的物理人机交互。该机器人具有三个相同的3-DoF RU/2-RUS腿，通过球面关节将可重构平台连接到基座。通过在基座上配置所有执行器，机器人的运动质量和惯性显著降低。通过采用可反向驱动的直接驱动电机，该系统实现了本体感知驱动，实现了直观、低阻抗和高带宽的交互。在SE(3)×R3上提出了一种阻抗控制策略，并利用奇异摄动理论进行了稳定性分析，强调了作动器动力学的关键作用，从而说明了作动器策略选择的重要性。实验结果证实了该机器人的稳定性、扩展的工作空间和有效的人机交互性能。

引用次数: 0

ODKP: A multivariate time series predictor based on orthogonal dynamic Koopman operator for blast furnace permeability index prediction 基于正交动态Koopman算子的多变量时间序列预测器用于高炉渗透率指数预测

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-08 DOI: 10.1016/j.conengprac.2025.106749

Mingyang Gao , Lina Wang , Xiangrong Song , Zhuoqing Li , Dazhong Ma

In blast furnace (BF) smelting, the permeability index (PI) is a key metric for evaluating whether the process is progressing toward optimal operating conditions. However, developing an effective prediction method for PI is challenging due to the influence of entangled temporal dependencies and the intrinsic non-stationarity of BF time series data. To address these challenges, a multivariate time series predictor based on orthogonal dynamic Koopman for BF PI prediction is proposed in this paper. Firstly, a feature decoupling (FD) module is designed, which uses a data-adaptive transformation based on an orthogonal matrix to effectively mitigate the impact of redundancy introduced by coupled variables. The feature decoupling module can be incorporated into the predictor to more effective the encoding and decoding within the decorrelated feature space. Subsequently, the multivariate BF time series, segmented using a sliding-window strategy, are projected into the Koopman embedding space via a multi-layer perceptron to extract interpretable dynamic modes. Furthermore, context-aware Koopman operator calculations are adaptively performed using extended dynamic mode decomposition (eDMD) across different temporal windows. This approach enables the approximation of non-stationary dynamics as locally linear, capturing the temporal evolution within each segment. Finally, comparative simulations with state-of-the-art models demonstrate that the proposed method achieves superior PI prediction performance.

在高炉冶炼中，渗透系数（PI）是衡量冶炼过程是否朝着最佳运行状态发展的关键指标。然而，由于BF时间序列数据的纠缠时间依赖性和固有非平稳性的影响，开发一种有效的PI预测方法是具有挑战性的。为了解决这些问题，本文提出了一种基于正交动态库普曼的多元时间序列预测器用于BF PI预测。首先，设计了特征解耦（FD）模块，采用基于正交矩阵的数据自适应变换，有效减轻了耦合变量引入的冗余影响；在预测器中加入特征解耦模块，可以在去相关特征空间内更有效地进行编码和解码。然后，使用滑动窗口策略分割多元BF时间序列，通过多层感知器将其投影到Koopman嵌入空间中以提取可解释的动态模式。此外，使用扩展动态模式分解（eDMD）跨不同时间窗口自适应地执行上下文感知的Koopman算子计算。这种方法使非平稳动态近似为局部线性，捕获每个段内的时间演变。最后，与最先进的模型进行了对比仿真，结果表明该方法具有较好的PI预测性能。

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引用次数: 0

Desired compensation adaptive robust control of remotely operated vehicles through integrated attitude and depth design 基于姿态与深度集成设计的遥控车辆期望补偿自适应鲁棒控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-05 DOI: 10.1016/j.conengprac.2025.106748

Xin Hu , Yiyang Zheng , Deqing Mei , Zheng Chen

The increasing reliance on remotely operated vehicles (ROVs) for critical subsea operations necessitates accurate attitude and position control in complex underwater environments. In addition to seabed operations, ROVs frequently perform hovering tasks that require control of different attitude angles. However, the hovering operation pattern and movements of mounted tools such as manipulators generate additional disturbances, resulting in unsatisfactory performance of conventional dynamic positioning controllers. As a solution, this paper proposes a desired compensation adaptive robust control scheme. The controller is based on a partially decoupled dynamic model of ROVs which retains the coupling effects among depth and attitude angles. A parameter adaptation law is proposed to cope with parameter uncertainties. Coupling and nonlinearity are compensated through model compensation. Additionally, robust feedback is designed to address underwater disturbances, model uncertainties, and residual coupling due to model decomposition. The feasibility and capability of the proposed control scheme are experimentally validated. Experiments are conducted including simultaneous depth and attitude control with tilted postures and control during horizontal movements. The results show substantial improvement in tracking error and response time.

在关键的水下作业中，越来越多地依赖远程操作车辆（rov），这就需要在复杂的水下环境中进行精确的姿态和位置控制。除了海底作业，rov还经常执行需要控制不同姿态角的悬停任务。然而，悬停操作方式和安装工具（如机械手）的运动产生额外的干扰，导致传统的动态定位控制器性能不理想。为此，本文提出了一种理想补偿自适应鲁棒控制方案。该控制器基于rov部分解耦的动力学模型，该模型保留了深度和姿态角之间的耦合效应。提出了一种参数自适应律来处理参数的不确定性。通过模型补偿对耦合和非线性进行补偿。此外，鲁棒反馈设计用于解决水下干扰、模型不确定性和模型分解引起的剩余耦合。实验验证了所提控制方案的可行性和性能。实验包括倾斜姿态下的深度和姿态同步控制以及水平运动时的控制。结果表明，在跟踪误差和响应时间方面有了很大的改进。

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引用次数: 0

Realistic process simulator for control strategy evaluation in continuous direct compaction tablet manufacturing 面向连续直接压片生产控制策略评价的逼真过程模拟器

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-08 DOI: 10.1016/j.conengprac.2025.106712

Dana Copot, Bora Ayvaz, Erhan Yumuk

This study introduces a mechanistic, high-fidelity simulation environment for continuous direct compaction (CDC) tablet manufacturing, integrating feeders, blender, hopper, and tablet press models into a unified framework. The platform realistically captures material flow dynamics, residence time effects, and multivariable interactions, providing a robust virtual environment for in silico control design and testing. A disturbance-aware feedforward-feedback control architecture is evaluated across realistic scenarios, including upstream flowrate and concentration disturbances, raw material variability (±10-20% bulk density changes), and model-plant mismatch. Results demonstrate the platform’s capability to systematically assess control performance and robustness, supporting safe optimization of manufacturing processes. This work lays the foundation for scalable, model-informed control development and de-risking of future plant-wide control strategies, aligning with the Pharma 4.0 vision of predictive and adaptive continuous pharmaceutical manufacturing.

本研究为连续直接压实（CDC）片剂生产引入了一个机械的、高保真的仿真环境，将给料机、搅拌器、料斗和压片机模型集成到一个统一的框架中。该平台逼真地捕捉了物料流动动力学、停留时间效应和多变量相互作用，为硅控制设计和测试提供了一个强大的虚拟环境。干扰感知的前馈-反馈控制架构在现实场景中进行评估，包括上游流量和浓度干扰、原材料可变性（±10-20%体积密度变化）以及模型-工厂不匹配。结果表明，该平台能够系统地评估控制性能和鲁棒性，支持制造过程的安全优化。这项工作为可扩展的、模型知情的控制开发和未来全厂控制策略的降低风险奠定了基础，与预测和自适应连续制药制造的制药4.0愿景保持一致。

引用次数: 0

Robust control of interleaved boost converter with active disturbance compensation 具有自干扰补偿的交错升压变换器鲁棒控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-06 DOI: 10.1016/j.conengprac.2025.106746

Giovanni Garraffa , Daniele Scirè , Francesco Alonge , Filippo D’Ippolito , Giuseppe Lullo , Giuseppe Costantino Giaconia , Alessandro Busacca , Gianpaolo Vitale , Antonino Sferlazza

Nowadays, extensive research is conducted on interleaved DC-DC boost converters due to their ability to minimize current ripple and enhance fault tolerance. In this article, we present a control methodology that achieves effective output voltage regulation while demonstrating robustness against uncertainties in parameters, variations in the source supply voltage, and deviations in load. These objectives are achieved by developing an equivalent circuit model for the interleaved boost converter and formulating a linear representation using the exact linearization technique. Subsequently, trajectory tracking control strategies are employed, incorporating a sliding mode element to manage parameter uncertainties and compensate for disturbance errors. The controller, applied to the equivalent boost converter model, adjusts the duty cycle of each individual MOSFET command signal. This control mechanism utilizes the output voltage and the sum of the currents within the converter’s branches as feedback variables. Experimental results illustrate the effectiveness and feasibility of the presented methodology.

交错DC-DC升压变换器具有减小电流纹波和提高容错能力的优点，目前得到了广泛的研究。在本文中，我们提出了一种控制方法，可以实现有效的输出电压调节，同时展示了对参数不确定性、电源电压变化和负载偏差的鲁棒性。这些目标是通过开发交错升压转换器的等效电路模型和使用精确线性化技术制定线性表示来实现的。然后，采用轨迹跟踪控制策略，结合滑模单元来管理参数不确定性并补偿干扰误差。该控制器应用于等效升压变换器模型，调整每个MOSFET命令信号的占空比。这种控制机制利用输出电压和变换器分支内电流的总和作为反馈变量。实验结果证明了该方法的有效性和可行性。

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引用次数: 0

An enhanced quality prediction method incorporating operator interventions via dual-branch feature extraction and its application to a hot strip rolling mill process 基于双分支特征提取的质量预测方法及其在热连轧过程中的应用

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-28 DOI: 10.1016/j.conengprac.2026.106807

Kai Zhang , Yali Wang , Kaixiang Peng

In the hot strip rolling mill (HSRM) process, the steel quality indices that serve as important performance indicators should be precisely predicted. Most existing methods are developed either based on process mechanisms or solely considering ordinary process variables (OPVs), which may perform poorly for cases with operator interventions. To address this problem, this paper proposes an enhanced quality prediction method by incorporating various operator interventions’ information. Firstly, the inter-variable and temporal features of OPVs are captured using a gated recurrent unit (GRU) combined with the attention mechanism. Secondly, the abrupt change features and trend features of operator intervention variables (OIVs) are extracted via a dual-branch convolution neural network (CNN) and the gating mechanism, which are guided by operator intervention types. Then, the features extracted from OIVs further induce the output of the GRU in the OPV feature extraction part through an inductive mechanism, and both features extracted from both OPVs and OIVs are finally fused to construct the quality prediction model. The proposed method is trained, validated, and tested using actual HSRM data that cover different operator intervention cases and various strip steels. It is shown from the experiment results that compared with those without considering OIVs and transformer-based methods, this method can decrease the prediction error of the steel crown by 19.48%, and the prediction-hit rate can reach 94% when operator interventions occur. The applicability is further examined using a cloud-edge-end prototype system with real-time HSRM process data, which shows that the real-time performance can be achieved.

在热连轧过程中，作为重要性能指标的钢材质量指标需要进行准确的预测。大多数现有方法要么是基于过程机制开发的，要么仅仅考虑了普通过程变量（opv），这可能在操作员干预的情况下表现不佳。为了解决这一问题，本文提出了一种结合各种作业者干预信息的增强质量预测方法。首先，利用门控循环单元（GRU）结合注意机制捕获opv的变量间和时间特征；其次，以算子干预类型为导向，通过双分支卷积神经网络（CNN）和门控机制提取算子干预变量（OIVs）的突变特征和趋势特征；然后，从OIVs中提取的特征通过归纳机制进一步诱导出OPV特征提取部分的GRU输出，最后将从OPV和OIVs中提取的特征融合构建质量预测模型。所提出的方法经过了训练、验证，并使用实际的HSRM数据进行了测试，这些数据涵盖了不同的操作人员干预案例和各种带钢。实验结果表明，与不考虑OIVs和基于变压器的方法相比，该方法可将钢冠的预测误差降低19.48%，当有操作员干预时，预测命中率可达94%。利用云边缘原型系统实时HSRM过程数据进一步验证了该方法的适用性，结果表明该方法能够实现实时性。

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引用次数: 0

Design of a fast model predictive controller based on the fully actuated system approach 基于全驱动系统方法的快速模型预测控制器设计

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-15 DOI: 10.1016/j.conengprac.2026.106762

Shijie Zhang , Yuebin Qiu , Mingzhe Hou , Xiang Wu , Hui Zhang , Jilong Wang

Nonlinear Model Predictive Control (NMPC) demonstrates strong capability in handling complex constrained systems; however, its non-convex optimization nature results in high computational complexity that limits practical implementation in real-time control scenarios. To address this computational bottleneck, this paper proposes an efficient Fully Actuated Fast Model Predictive Control (FA-FMPC) method. This method leverages the fully actuated (FA) system approach to modify the open-loop characteristics of nonlinear systems exhibiting complex nonlinearity, strong coupling, or time-delay effects, thereby constructing a linear time-invariant closed-loop system with a freely configurable characteristic structure. Based on this linear time-invariant system, a Fast Model Predictive Control (Fast MPC) method is designed. When the system constraints are convex, the NMPC problem can be transformed into a convex MPC problem. To improve computational efficiency, the Alternating Direction Method of Multipliers (ADMM) is employed to decompose the global optimization problem into multiple subproblems and solve them through alternating iterations. Meanwhile, the Riccati solution of the Linear Quadratic Regulator (LQR) is utilized to optimize the primal variable update process in ADMM, and by precomputing matrix operation components, online matrix decomposition is avoided, significantly enhancing computational efficiency. To validate the effectiveness of the proposed method, simulation verification is conducted on an under-actuated robotic system and a Universal Robots UR5 manipulator simulated in ROS Noetic with Gazebo.

非线性模型预测控制（NMPC）在处理复杂约束系统方面表现出较强的能力；然而，它的非凸优化特性导致了高计算复杂度，限制了在实时控制场景中的实际实现。为了解决这一计算瓶颈，本文提出了一种高效的全驱动快速模型预测控制（FA-FMPC）方法。该方法利用完全驱动（FA）系统方法来修改具有复杂非线性、强耦合或时滞效应的非线性系统的开环特性，从而构建具有自由配置特征结构的线性时不变闭环系统。基于该线性定常系统，设计了一种快速模型预测控制（Fast MPC）方法。当系统约束为凸时，NMPC问题可以转化为凸MPC问题。为了提高计算效率，采用乘法器交替方向法（ADMM）将全局优化问题分解为多个子问题，通过交替迭代求解。同时，利用线性二次型调节器（Linear Quadratic Regulator， LQR）的Riccati解对ADMM中的原始变量更新过程进行优化，通过预先计算矩阵运算分量，避免了在线矩阵分解，显著提高了计算效率。为了验证该方法的有效性，对欠驱动机器人系统和Universal Robots UR5机械手进行了仿真验证，并在ROS Noetic和Gazebo中进行了仿真。

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引用次数: 0

Observer-based sliding mode admittance control for ultrasound robot force-tracking in complex interaction environments 基于观测器的滑模导纳控制在复杂交互环境下的超声机器人力跟踪

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-13 DOI: 10.1016/j.conengprac.2026.106764

Sen Li , Qi Chen , Weihua Li , Mingfeng Wang , Sungsung Pang , Kai Wu

Robotic ultrasound systems can improve imaging consistency and reduce operator workload by maintaining stable probe–tissue contact forces. However, variations in tissue stiffness and surface position often degrade force-tracking performance. This paper presents a disturbance observer–based sliding mode admittance control (DOSMAC) framework to address these challenges. Stiffness and position variations are uniformly modeled as lumped external disturbances, estimated online by a disturbance observer and compensated through sliding mode control. The resulting signal is introduced as a virtual input to the admittance model, enhancing robustness without requiring online stiffness identification or extensive parameter tuning. The stability of the closed-loop system is established through Lyapunov analysis. Simulations and experiments with stiffness ranging from 500 to 3500 N/m verify the effectiveness of the proposed approach. In experiments with simultaneous stiffness and position variations, DOSMAC reduces overshoot by 29.1% and 55.4%, peak force error by 4.36 N and 0.46 N, and root mean square error by 1.79 N and 0.4 N, respectively, compared with conventional admittance control and adaptive variable admittance control. These results demonstrate that the proposed method enables stable and reliable force tracking under complex time-varying conditions, supporting the clinical translation forceof robotic ultrasound.

机器人超声系统可以提高成像的一致性，并通过保持稳定的探针组织接触力来减少操作员的工作量。然而，组织刚度和表面位置的变化通常会降低力跟踪性能。本文提出了一种基于干扰观测器的滑模导纳控制（DOSMAC）框架来解决这些问题。刚度和位置变化统一建模为集总外部扰动，由扰动观测器在线估计，并通过滑模控制进行补偿。结果信号作为虚拟输入引入导纳模型，增强鲁棒性，而不需要在线刚度识别或广泛的参数调整。通过李雅普诺夫分析，建立了闭环系统的稳定性。在500 ~ 3500 N/m的刚度范围内进行了仿真和实验，验证了该方法的有效性。在刚度和位置同时变化的实验中，与传统导纳控制和自适应变导纳控制相比，DOSMAC控制的超调量分别降低29.1%和55.4%，峰值力误差分别降低4.36 N和0.46 N，均方根误差分别降低1.79 N和0.4 N。结果表明，该方法能够在复杂时变条件下实现稳定可靠的力跟踪，为机器人超声的临床平移力提供支持。

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引用次数: 0

Regenerative braking torque control with tire-force-based limiting for vehicle stability of a front-rear motor-driven EV 基于轮胎力限制的前后轮电动汽车稳定性再生制动转矩控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-22 DOI: 10.1016/j.conengprac.2026.106789

Chaeho Lim , Seonggyeong Ju , Yunjeong Hwang , Hanseon Ga , Jinseok Song , Seibum B. Choi , Sooyoung Kim

Regenerative braking is essential for improving energy efficiency in electric vehicles, yet control strategies for coasting remain underdeveloped. Existing control methods respond conservatively to wheel slip, limiting regenerative torque usage and degrading deceleration consistency and lateral stability. This study proposes an advanced regenerative braking control algorithm that maintains longitudinal slip stability, enhances yaw stability, and better preserves the driver’s intended regenerative braking. The controller integrates a slip controller, a yaw stability controller, and a torque compensator, which are coordinated based on real-time slip conditions. Simulation and vehicle experiments verify the proposed method, confirming an average 64% improvement in preserving driver braking intention and a 37% reduction in yaw rate MAE, thereby demonstrating its effectiveness and practical applicability to production EVs.

再生制动对于提高电动汽车的能源效率至关重要，但其滑行控制策略仍不发达。现有的控制方法对车轮滑移反应保守，限制了再生扭矩的使用，降低了减速一致性和横向稳定性。本研究提出了一种先进的再生制动控制算法，既能保持纵向滑移稳定性，又能增强偏航稳定性，更好地保留驾驶员的再生制动意愿。该控制器集成了滑移控制器、偏航稳定性控制器和转矩补偿器，并根据实时滑移情况进行协调。仿真和整车实验验证了该方法的有效性，在保持驾驶员制动意图方面平均提高了64%，在横摆角速度MAE方面平均降低了37%，证明了该方法在量产电动汽车上的有效性和实用性。

引用次数: 0