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  • 期刊名称:

    Control Engineering Practice

  • 中文名称: 控制工程实践
  • 刊频: 1.943
  • ISSN: 0967-0661
  • 出版社: -
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  • 机译 对二氧化铈涂层汽油微粒过滤器内部的热和碳烟氧化动力学建模
    摘要: Gasoline particulate filters (GPFs) are practically adoptable devices to mitigate particulate matter emissions from vehicles using gasoline direct ignition engines. This paper presents a newly developed control-oriented model to characterize the thermal and soot oxidation dynamics in a ceria-coated GPF. The model utilizes the GPF inlet exhaust gas temperature, exhaust gas mass flow rate, the initial GPF soot loading density, and air- fuel ratio to predict the internal GPF temperature and the amount of soot oxidized during regeneration events. The reaction kinetics incorporated in the model involve the rates of both oxygen- and ceria-initiated soot oxidation reactions. Volumetric model parameters are calculated from the geometric information of the coated GPF, while the air-fuel ratio is used to determine the volume fractions of the exhaust gas constituents. The exhaust gas properties are evaluated using the volume fractions and thermodynamic tables, while the cordierite specific heat capacity is identified using a clean experimental data set. The enthalpies of the regeneration reactions are calculated using thermochemical tables. Physical insights from the proposed model are thus enhanced by limiting the number of parameters obtained from fitting to only those which cannot be directly measured from experiments. The parameters of the model are identified using the particle swarm optimization algorithm and a cost function designed to simultaneously predict both thermal and soot oxidation dynamics. Parameter identification and model validation are performed using independent data sets from laboratory experiments conducted on a ceria-coated GPF. This work demonstrates that the proposed model can be successfully implemented to predict ceria-coated GPF dynamics under different soot loading and temperature conditions.
  • 机译 使用潜在变量动态模型集成生产计划和过程控制
    摘要: Given their increasing participation in fast-changing markets, the integration of scheduling and control is an important consideration in chemical process operations. This generally involves computing optimal production schedules using dynamic models, which is challenging due to the nonlinearity and high-dimensionality of the models of chemical processes. In this paper, we begin by observing that the intrinsic dimensionality of process dynamics (as relevant to scheduling) is often much lower than the number of model state and/or algebraic variables. We introduce a data mining approach to "learn" closed-loop process dynamics on a low-dimensional, latent manifold. The manifold dimensionality is selected based on a tradeoff between model accuracy and complexity. After projecting process data, system identification and optimal scheduling calculations can be performed in the low-dimensional, latent-variable space. We apply these concepts to schedule an air separation unit under time-varying electricity prices. We show that our approach reduces the computational effort, while offering more detailed dynamic information compared to previous related works.
  • 机译 非线性系统相对程度的自动识别:在滑模控制设计和实验评估中的应用
    摘要: This paper deals with the design and the experimental-based assessment of a scheme to identify the relative degree of a system in order to correctly design the controller. The system is assumed to have an unknown dynamics, and the output is measured in a discrete-time fashion. Provided that a prescribed input signal is applied, it is proven that a set of inequalities holds only for the rth time derivative of the output, where r is the relative degree. A practical algorithm for the relative degree identification is also formulated, which is written in a pseudo-code notation. In the paper, a special reference is made to the design of sliding mode controllers. Specifically, a self-configuring sliding mode control strategy is presented, which automatically selects the controller in case of changes to the relative degree. The scheme is implemented in a practical set-up composed of a lab-scale overhead crane mechanically coupled with a 12 Volts DC motor. The aim is to identify the relative degree of the position of the crane (the output), with respect to the DC motor armature voltage (the control input). The experimental results reveal the high accuracy of the proposed strategy for the identification of the relative degree.
  • 机译 探针显微镜中用于原子力重建的超扭曲观察器
    摘要: This paper presents a new methodology, employing a super-twisting sliding mode observer, to reconstruct un-measureable atomic-forces at nano-Newton precision in a Vertically Oriented Probe Microscope (VOPM). The VOPM senses the deflection of a vertically oriented cantilever, caused by shear-force interaction with a confined water layer above the sample-substrate. The paper describes the development of a model and the subsequent experimental process for computing its parameters. This forms the basis for the design of a super-twisting observer to estimate the unknown shear-forces. The reconstructed force can be decomposed into elastic and viscous components, which are important in biological research.
  • 机译 用于软传感器的非线性概率潜变量回归模型:从浅层到深层结构
    摘要: Probabilistic latent variable regression models have recently caught much attention in the process industry, particularly for soft sensor applications. One of the main challenges for those models is how to effectively extract nonlinear features for latent variable regression. This paper proposes a nonlinear probabilistic latent variable regression (NPLVR) model based on the features extracted by variational auto-encoder. To extend the NPLVR model from shallow to deep structure, a hierarchical form of NPLVR model is proposed to extract deeper nonlinear information by stacking VAE. Under the same modeling framework, a semi-supervised version of hierarchical NPLVR model is further developed to handle the problem of scarce amount of labeled data samples, which is quite common in practical applications. Two industrial case studies are provided to demonstrate the effectiveness and superiority of the developed models.
  • 机译 基于分层二次规划的多车系协调
    摘要: This paper presents an optimization-based control scheme for generating online multi-vehicle coordination behaviors to accomplish missions in indoor environments. The proposed control scheme relies on the use of hierarchical task functions in terms of the multi-vehicle configuration variables. The task functions are related to individual and group obstacle avoidance, reaching fixed targets, group trajectory tracking, maintaining formations, enclosing the group within a geometric area, among others. The stack of hierarchical tasks automatically handles possible conflicts between them. Quadratic programs are formulated for explicitly solving inequality and equality task constraints at any hierarchy. In addition, a finite state machine is employed to build complex group behaviors for successfully fulfilling group missions. The proposed control scheme is demonstrated on two experiments with static and moving obstacles where a group composed by six vehicles tracks a predefined trajectory for the center of mass of the group. In the second experiment, the group is asked to clean the workspace by pushing movable objects.
  • 机译 故障检测和识别结合了过程测量和统计警报
    摘要: Classification-based methods for fault detection and identification can be difficult to implement in industrial systems where process measurements are subject to noise and to variability from one fault occurrence to another. This paper uses statistical alarms generated from process measurements to improve the robustness of the fault detection and identification on an industrial process. Two levels of alarms are defined according to the position of the alarm threshold: level-1 alarms (low severity threshold) and level-2 alarms (high severity threshold). Relevant variables are selected using the minimal-Redundancy-Maximal-Relevance criterion of level-2 alarms to only retain variables with large variations relative to the level of noise. The classification-based fault detection and identification fuses the results of a discrete Bayesian classifier on level-1 alarms and of a continuous Bayesian classifier on process measurements. The discrete classifier offers a practical way to deal with noise during the development of the fault, and the continuous classifier ensures a correct classification during later stages of the fault. The method is demonstrated on a multiphase flow facility.
  • 机译 起重机系统通过人工神经网络通过“反馈控制仿真”进行逆动态控制
    摘要: Cranes are systems highly used in industrial applications to transport heavy loads. The nonlinear behavior, and the crane own dynamic produce vibrations during the motion. In order to improve the system performance and specifically to ensure stability and a control with minimum vibrations, this work proposes a new strategy based on IDCS (Inverse Dynamic Control Simulation) using machine learning with Artificial Neural Networks ANN that gives the possibility to learn the inverse dynamic model of the crane and apply the feedback information based on the inverse dynamic control simulation. IDCS allows a suitable signal control avoiding noise and need for extra sensors in the feedback loop. The ANN creates the inverse dynamic model of the crane. The training architecture is developed to learn the inverse dynamic model of the crane in different operational points, and is used as feedforward control with the feedback dynamic in the IDCS scheme. Simulations and experiments are conducted with an industrial crane, and results show that the proposed method decreases vibration and position error. The proposed ANN-IDCS showed suitable performance compared to other controllers such as analytical inverse model control (AIC), Dual Matching Control (DMM) and shaped reference in feedforward (FRC).
  • 机译 通过基于物理的NMPC改善工业MDF闪蒸干燥机的操作
    摘要: Nonlinear model predictive control (NMPC) has increased popularity thanks to the availability of black-box models, systematically obtained from plant data via machine-learning procedures. Although this may be a good approach in the medium term, pure data-driven models quickly become outdated with changes in the process operation, so re-identification (training) routines are periodically required. Moreover, if the NMPC includes any economic objective to drive the process to a more efficient operation, these models often go beyond their validity range, which translates in a degraded control performance (high plant-model mismatch). In this work, the above issues are considered to model the drying section of an industrial medium density fibreboard (MDF) plant. The main contribution of this work is proposing a lumped-parameter grey-box model built upon first principles and completed with experimental equations, obtained from constrained regression with plant data. Upon this model, a moving-horizon estimator (MHE) is designed to estimate unmeasured inputs and states. Then, a mixed economic-tracking NMPC, which explicitly considers actuator-stiction compensation, is proposed to drive the dryer to the humidity setpoint by the most efficient path. Both optimisations are solved within the system sampling interval thanks to an efficient discretisation of the system dynamics by orthogonal collocation, and to the high computational performance achieved by modern software tools for numerical optimal control. The controller was firstly tested in simulation with a rigorous model of a generic MDF dryer, and it is currently implemented in the actual plant achieving significant performance improvements.
  • 机译 输出缺失的连续时间状态空间模型的核模子空间识别
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Feb.期
    摘要: Subspace identification methods using Generalized Poisson Moment Functionals (GPMF) have been proposed previously to tackle the problem of derivative estimation in continuous time (CT) systems. In this paper, a convergence result underpinning the GPMF methods for continuous time identification is detailed. Based on this, a CT-MOESP method is proposed to estimate the system matrices in state-space models. Since these results hold in the asymptotic case where the number of data points tend to infinity, Nuclear Norm Minimization (NNM) is used to integrate the low rank approximation step in subspace identification with a goodness of fit criterion. This paper extends these existing discrete time methods to continuous time by formulating the NNM optimization into the framework of the Alternating Direction Method of Multipliers (ADMM) algorithm. On the numerical front, the accuracy of the proposed method is demonstrated with the help of simulations on two systems frequently cited in literature. An industrial dryer application is considered in order to demonstrate the practical applicability of proposed method.
  • 机译 点脚的功能性电刺激的点对点重复控制
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Mar.期
    摘要: Drop-Foot is a common problem resulting from a range of neurological conditions, and prevents normal leg swing during gait, leading to abnormal, inefficient motion with an increased risk of falling. It damages the quality of life of over 122,000 people in the US and 11,400 people in the UK every year. Functional electrical stimulation (FES) addresses drop-foot by artificially contracting the tibialis anterior, and has had considerable success both clinically and commercially. However current commercial controllers are open loop and have long set-up times. The few controllers in the research domain are predominantly open-loop, lack accuracy, and struggle with muscle delays, non-linearities and the onset of fatigue. More advanced controllers require extensive sensor data and/or are highly dependent on an identified model. Recent developments have shown model based controllers combined with learning can facilitate higher accuracy, however previous attempts employed batch-wise learning, and led to disjointed control signals. This paper applies repetitive control (RC) to drop-foot for the first time, facilitating a continuous, smooth process of learning with no resetting. To maximise performance, a comprehensive extension to the traditional RC framework is undertaken to enable only isolated time points to be tracked, improving robustness and reducing memory and communication requirements. Experimental data confirms that RC can achieve normal gait when applied to FES-assisted gait with no voluntary effort. The new 'point-to-point' RC framework outperformed traditional RC, while using only 5 data points per gait cycle and minimal control effort.
  • 机译 基于时间序列数据聚类的铁矿石烧结过程运行模式识别
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Mar.期
    摘要: Operators often make different control decisions for different operating modes to meet the production requirement of the iron ore sintering process. Recognizing the operating modes is important to improve the quality and quantity of the sinter ore. An operating mode recognition method based on the clustering of time series data for the iron ore sintering process is presented in this paper. First, the Spearman rank correlation analysis and the information entropy analysis are combined to select parameters. Next, the operating mode recognition submodel is built by the fuzzy C-Means clustering method based on dynamic time warping distance and the naive Bayesian classifier method. Then, the outputs of the submodels are fused to obtain the final recognized operating mode. Finally, the productivity and combustion efficiency are regarded as the classification criteria, and the raw data collected from an iron and steel plant are used for the experiment. The experimental results show that the proposed method can effectively recognize the operating mode of the sintering process.
  • 机译 管道中多个泄漏位置的水力梯度自适应估计
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Feb.期
    摘要: A scheme is proposed for detecting and locating multiple sequential leaks, based on a combination of an adaptive observer to identify the hydraulic gradient in real time and a leak location observer to estimate the leak position and its outflow. The main contribution is the use of an equivalent leak model which switches with an identification function for the hydraulic gradient without input excitation. Experimental results of a pilot pipeline showed a satisfactory estimation in spite of operation changes and leaks. Moreover they revealed that if leaks must be located, a precise knowledge of the hydraulic gradient is required.
  • 机译 数据驱动的废水处理过程决策
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Mar.期
    摘要: Membrane fouling has become a serious issue for the safe operation of wastewater treatment process (WWTP). To deal with this problem, this paper proposes a data-driven decision-making method to reduce the incidence of membrane fouling in WWTP. The main novelties of this proposed data-driven decision-making method are threefold. First, a long-term prediction method, based on a self-organizing deep belief network (SDBN) and the multi-step prediction strategy, is developed to predict the membrane permeability. Second, a multi-warning method, based on an independent component analysis-principal component analysis (ICA-PCA) algorithm, is proposed to detect and warn membrane fouling with multiple indicators. Third, a multi-category diagnosis method, based on the kernel function, is designed to diagnose membrane fouling for providing the decision support. Finally, an intelligent decision-making system, consisting the above methods and required sensors, is developed for some real wastewater treatment plants. The experimental results demonstrated the efficiency and effectiveness of the proposed data-driven decision-making method.
  • 机译 范围控制MPC及其在蒸汽压缩循环中的应用
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Mar.期
    摘要: A range control MPC formulation is presented for control of Vapor Compression Cycles (VCC). Variation in system dynamics is handled through application of range control which is a generalization of a tracking problem whereby the set-point for the system output is replaced by a funnel (time-varying upper and lower bounds on the system output) which is implemented as a set of soft constraints. Vapor cycle is optimized to maximize device efficiency while ensuring feasibility of operation. Experimental validation of the control design, embedded in a heat-pump controller, is presented.
  • 机译 六速干式双离合器变速器升档时离合器执行器电机的容错控制
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Feb.期
    摘要: As the working hours of dual clutch transmission (DCT) increase, the probability of a fault occurring in the clutch actuator motor increases. If no fault-tolerant control is adopted after an actuator motor fault occurs, it will lead to shifting failure and even damage the actuator motor. This study devises corresponding fault-tolerant control strategies for 6-speed DCT vehicle when the actuator motor of one of the clutches malfunctions in the upshift process. In those strategies, once the actuator motor fails, the vehicle is designed to disengage the fault clutch and engage the no-fault clutch, after which the vehicle can be driven either in the current gear or in higher/lower gear by jumping upshift with single clutch depending upon the driver demand. This ensures that the vehicle maintains better power performance and fuel economy even after a fault occurs in one clutch actuator motor. Lastly, the strategies were verified in the DCT hardware-in-the-loop test bench.
  • 机译 基于转子磁通观测器的无传感器表面安装式PMSM驱动器的性能改进
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Mar.期
    摘要: Permanent magnet synchronous motor sensorless algorithms for low speed region are usually based on rotor anisotropy. Although many studies showed a good behavior of this type of control, high frequency voltage injection is required, which causes loud acoustic noise in addition to electrical losses. On the other hand, methods based on back electromotive force or rotor flux observer, which guarantee high performance in the medium-high speed region, do not required voltage injection. In this paper, a rotor flux observer based algorithm performance is analyzed, in order to extend its use also in the low speed region. Behavior both with no-load, linear torque, quadratic torque, constant torque and compressor-load torque is tested, especially focusing on motor starting. Improvements to rotor flux observer algorithms available in the scientific literature are discussed and their effectiveness is verified by experimental results.
  • 机译 具有运动动力学约束的机械手的预测关节轨迹缩放
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Feb.期
    摘要: Trajectory scaling techniques adapt online the robot timing law to preserve the desired geometric path when the desired motion does not respect the robot limits. State-of-the-art non-predictive methods typically provide far-from-optimal solutions, while high computational burdens are the main bottleneck for the implementation of receding horizon strategies. This paper proposes a predictive approach to trajectory scaling subject to joint velocity, acceleration, and torque limitations. Computational complexity is dramatically reduced by means of the parametrization of inputs and outputs and the iterative linearization of the optimal control problem around the previous output prediction. This allows the online implementation of the method for sampling periods in the order of one millisecond. Numerical and experimental results on a six-degree-of-freedom robot show the effectiveness of the method.
  • 机译 序列相关非高斯系统中用于异常事件诊断的分层密度分解
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Mar.期
    摘要: Processes in industrial practice often represent dynamic systems, which is a result of controller feedback, the presence of process noise and measured or unmeasured disturbances. To monitor dynamic systems that produce serially/time-based correlated data records, the literature has proposed numerous multivariate techniques that rely on (ⅰ) time-lagged arrangements of the recorded variables and (ⅱ) subspace-based approaches. Proposed techniques, however, may not accurately and reliably describe to what extent process variables are affected by abnormal events, which compromises the identification of potential root causes. To address this, this paper employs a state space model to describe the inherent serial correlation and introduces a joint probability density function for this model. The density function can be hierarchically decomposed into the product of multiple low-dimensional conditional densities to reduce complexity and to detect and preanalyze anomalous behavior. Using the low-dimensional densities, a correction scheme to optimally describe the effect of an abnormal event upon particular process variables is proposed. A second important benefit of the hierarchical decomposition is that no assumptions are imposed on the distribution of the random error component of the state space models. Application studies to a simulation process and recorded data from two industrial processes demonstrate that, compared to conventional methods, the hierarchical decomposition can substantially improve the diagnosis of abnormal process behavior.
  • 机译 使用基于观察者的滑模控制对液压缸进行鲁棒控制:理论发展和实验验证
    • 作者:;
    • 刊名:Control Engineering Practice
    • 2020年第Feb.期
    摘要: This paper focuses on the design of an observer-based sliding mode controller (SMC) for nonlinear hydraulic differential cylinder systems affected by uncertainties. These uncertainties include modeling errors, external disturbances, and measurement noise. The aim is to ensure suitable tracking performance and robustness against unknown inputs. The task of system state and unknown input estimation is performed using high gain Proportional-Integral-Observer (PIO). Input-output exact feedback linearization is used to linearize the system model to be applicable for linear PIO structure. Estimation of system states is directly used in calculation of sliding surface. The SMC is utilized for input-output linearized system to provide a desired performance in the presence of uncertainties and to compensate the effects of external disturbances, plant parameter changes, unmodeled dynamics, measurement noise, etc. Parameter selection of SMC is elaborately considered by defining a novel performance/energy criteria. Stability of closed-loop system is established using Lyapunov method. Furthermore, a complete robustness evaluation considering different levels of measurement noise, modeling errors, and external disturbances is investigated. Experimental results validate the advantages of introduced combined approach in comparison with standard SMC and P-controller approaches. Consequently, integration of state and unknown input estimations into the sliding mode structure leads to appropriate disturbance attenuation and increases the system performance robustness.
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