A pulp mill benchmark problem for control: application of plantwide control design

A heuristic for design of plantwide control strategies is introduced and applied to the millwide control of a previously presented pulp mill benchmark. Two control strategies (decentralized control and unit-based model predictive control) are compared according to their capacity to reduce the total error and maximize the operating profits. The control strategies are studied through closed-loop simulations of the process including several disturbances and setpoint changes in the digester, oxygen reactor, bleach plant, recausticizing plant and lime kiln.     

Control structure selection and model predictive control of the Weyerhaeuser digester problem

The Weyerhaeuser digester problem (WDP) is a simplified digester model which captures the major dynamic characteristics of a continuous pulp digester and has been offered to the research community as an industrial challenge problem. The control objective is to minimize variations in the Kappa # for unmeasured disturbances. A systematic approach to selecting the manipulated inputs and secondary measurements using robust control analysis tools has been successfully applied to the WDP. A multi-rate data-sampling linear model predictive controller using the selected input/measurement pairings provided robust closed-loop performance for the rejection of both deterministic and stochastic unmeasured disturbances.     

LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.     

Output feedback control of nonlinear systems subject to sensor data losses

In this work, we focus on output feedback control of nonlinear systems subject to sensor data losses. We initially construct an output feedback controller based on a combination of a Lyapunov-based controller with a high-gain observer. We then study the stability and robustness properties of the closed-loop system in the presence of sensor data losses for both the continuous and sampled-data systems. We state a set of sufficient conditions under which the closed-loop system is guaranteed to be practically stable. The theoretical results are demonstrated using a chemical process example.     

Data mining to support anaerobic WWTP monitoring

The stable and efficient operation of anaerobic wastewater treatment plants (WWTPs) is a major challenge for monitoring and control systems. Support for distributed anaerobic WWTPs through remotely monitoring their data was investigated in the TELEMAC framework. This paper describes how the accumulating filtered sensor data was mined to contribute to the refining of expert experience for insights into digester states. Visualisation techniques were used to present cluster analyses of digester states. A procedure for determining prediction intervals is described together with its application for volatile fatty acid concentrations; this procedure enables prediction risk assessment.     

Soft computing and signal processing based active fault tolerant control for benchmark process

Ideally, when faults happen, the closed-loop system should be capable of maintaining its present operation. This leads to the recently studied area of fault-tolerant control (FTC). This paper addresses soft computing and signal processing based active FTC for benchmark process. Design of FTC has three levels: Level 1 comprises a traditional control loop with sensor and actuator interface and the controller. Level 2 comprises the functions of online fault detection and identification. Level 3 comprises the supervisor functionality. Online fault detection and identification has signal processing module, feature extraction module, feature cluster module and fault decision module. Wavelet analysis has been used for signal processing module. In the feature extraction module, feature vector of the sensor faults has been constructed using wavelet analysis, sliding window, absolute maximum value changing ratio and variance changing ratio as a statistical analysis. For the feature cluster module, the self-organizing map (SOM), which is a subtype of artificial neural network has been applied as a classifier of the feature vector. As a benchmark process three-tank system has been used. Control of the three-tank system is provided by fuzzy logic controller. Faults are applied to three level sensors. Sensor faults represent incorrect reading from the sensors that the system is equipped with. When a particular fault occurs in the system, a suitable control scheme has been selected on-line by supervisor functionality to maintain the closed-loop performance of the system. Active FTC has been achieved by switch mode control using fuzzy logic controller. Simulation results show that benchmark process has maintained acceptable performance with FTC for the sensor faults. As a result, when the system has sensor faults soft computing and signal processing based FTC helps for the best performance of the system.     

Design of failure-accommodating multiloop LQG-type controllers

This note investigates the stability of multiloop LQG-type controllers in the presence of actuator and sensor outages. For the linear quadratic state feedback (LQSF) regulator case, it is proved that the closed-loop stability can be maintained in the presence of certain actuator failure states by inserting appropriate constant gains in the control loops. The results are also applicable (via duality) to the design of state estimators which maintain stability in face of sensor failures, provided that the failure state is known or detected. This regulator-estimator combination yields an LQG-type controller which is tolerant to certain actuator and sensor failure states.     

Decentralized output-feedback control of large-scale nonlinear systems with sensor noise

This paper presents a new tool for decentralized output-feedback control design of large-scale nonlinear systems in the presence of non-smooth sensor noise. Through a recursive control design approach, the closed-loop decentralized system is transformed into a network of input-to-state stable (ISS) systems and the influences of the sensor noise are represented by ISS gains. The decentralized control objective is achieved by applying the cyclic-small-gain theorem to the closed-loop decentralized system. Moreover, the outputs of the closed-loop decentralized system can be driven arbitrarily close to the levels of their corresponding sensor noise.     

Data-driven diagnosis of sensor precision degradation in the presence of control

This paper considers the precision degradation type of sensor faults within control loops. In a closed loop, sensor faults propagate through controller to manipulated variables and disturb the other process variables, which obscures the source of sensor faults but receives less attention in existing methods of data-driven sensor fault diagnosis. With the assumption that only closed-loop data in normal condition are available, difficulty arises due to the facts that little a priori knowledge is known about closed-loop sensor fault propagation and the open-loop process model may not be identifiable. The proposed method in this paper constructs residual that is regarded as including two parts: the first part is the current sensor faults whose fault direction is known to be the identity matrix; and for the purpose of diagnosing the first part, the second part is considered as the disturbance which is affected by noises and past sensor faults due to unknown fault propagation. The disturbance variance is minimized in residual generator design to improve fault sensitivity. And the corresponding disturbance covariance is estimated and then utilized in residual evaluation. The proposed method in this paper is motivated by a pioneer work on closed-loop sensor fault diagnosis which performs principal component analysis in the feedback-invariant subspace of the closed-loop process outputs. But it is revealed by the proposed method that the feedback-invariant signal is affected by past sensor faults, leading to performance degradation of the pioneer work. The improvement of the proposed approach is due to analysis of residual dynamics and explicit handling of the disturbance in residual evaluation, which is not considered in the pioneer work. A simulated 4 × 4 dynamic process and a simulated two-product distillation column are studied to verify the effectiveness of the proposed approach compared to the existing principal component analysis method in feedback-invariant subspace.     

基于LVDS的电子星模拟器设计

为了实现卫星姿轨控地面半物理仿真试验,设计了基于LVDS的电子星模拟器,图像分辨率支持1024*1024;图像位宽支持12 bit;能够同时完成帧频10 Hz的图像上传及采集;将星敏感器作为高精度姿态测量部件引入控制系统,地面动力学通过以太网将四元数提供给电子星模拟器,电子星模拟器将生成的电子星图通过LVDS传输给星敏感器,通过地面实时系统将控制系统、星务计算机、敏感器系统组成了实时仿真验证系统;试验表明电子星模的输出接近目标值,闭环测试中星敏采集到准确的星图;通过实物在闭环回路仿真验证了上述方案的有效性,并通过指标对比分析,显示了电子星模拟器的可行性,在卫星姿轨控地面半物理仿真试验中具有良好的推广性。     

Probabilistic Constrained MPC for Multiplicative and Additive Stochastic Uncertainty

The technical note develops a receding horizon control strategy to guarantee closed-loop convergence and feasibility in respect of soft constraints. Earlier results addressed the case of multiplicative uncertainty only. The present technical note extends these to the more general case of additive and multiplicative uncertainty and proposes a method of handling probabilistic constraints. The results are illustrated by a simple design study considering the control of a wind turbine.      

Multisensor switching control strategy with fault tolerance guarantees

In this paper we propose a novel fault tolerant multisensor switching strategy for feedback control. Each sensor of the proposed multisensor scheme has an associated state estimator which, together with a state feedback gain, is able to individually stabilise the closed-loop system. At each instant of time, the switching strategy selects the sensor-estimator pair that provides the best closed-loop performance, as measured by a control-performance criterion. We establish closed-loop stability of the resulting switching scheme under normal (fault-free) operating conditions. More importantly, we show that closed-loop stability is preserved in the presence of faulty sensors if a set of conditions on the system parameters (such as bounds on the sensor noises, maximum and minimum values of the reference signal, etc.) is satisfied. This result enhances and broadens the applicability of the proposed multisensor scheme since it provides guaranteed properties such as fault tolerance and robust closed-loop stability under sensor fault. The results are applied to the problem of automotive longitudinal control.     

Set theoretic approach to fault-tolerant control of linear parameter-varying systems with sensor reintegration

In this paper, we present a fault-tolerant control scheme for linear parameter-varying systems that utilises multiple sensor switching to compensate for sensor faults. The closed-loop scheme consists of an estimator-based feedback tracking controller and sensor-estimate switching strategy which allows for the reintegration of previously faulty sensors. The switching mechanism tracks the transitions from faulty to healthy behaviour by means of set separation and pre-computed transition times. The sensor-estimate pairings are then reconfigured based on available healthy sensors. Under the proposed scheme, preservation of closed-loop system boundedness is guaranteed for a wide range of sensor fault situations. An example is presented to illustrate the performance of the fault-tolerant control strategy.     

Achievable closed-loop properties of systems under decentralizedcontrol: conditions involving the steady-state gain

The question of the existence of decentralized controllers for open-loop stable multivariable systems which provide particular closed-loop properties is investigated. In particular, we study the existence of decentralized controllers which provide integral action (Type I closed-loop performance) and also demonstrate one or more of: unconditional stability, integrity with respect to actuator and sensor failure, and decentralized unconditional stability. Necessary, sufficient, and, in some cases, necessary and sufficient conditions on the open-loop steady-state gain are derived such that there exists a controller which provides these desired closed-loop characteristics. These results provide the basis for a systematic approach to control structure selection for decentralized controller design     

Some considerations for estimator-based compensator design

In this paper some criteria are presented for dividing the closed-loop system poles of a feedback system between the estimator and the controller when using an estimator-based compensator. The criteria are based on frequency response considerations, but are related to some well-known facts in the time domain. It is well known, for example, that the closed-loop system poles are the poles of the estimator in union with the controller poles. It is also well known that the time response of the closed-loop plant states due to a command depends only on the closed-loop control poles, and the response of the estimate error depends only on the closed-loop estimator poles. In the frequency domain, the following can be said: the open-loop compensator transfer function from the sensor measurement to the control and the closed-loop transfer function from the sensor measurement to the system output are both independent of how the closed-loop poles are distributed between the controller and the estimator, but the closed-loop transfer function from the command to the control or system output is not. Placing the slower closed-loop poles in the controller causes the control gains to be smaller, which in turn causes the effect of the command signal to be attenuated, both at the control and at the closed-loop system output. Making use of these facts allows the closed-loop poles to be divided between the controller and the estimator on a more intelligent basis than ‘the estimator poles should be three times faster than the controller poles’. In an example, these concepts are applied to the design of a platform despin control system for a dual-spin satellite.     

一类不确定Lur''e 奇异系统的可靠鲁棒性H∞跟踪控制

The problem of reliable robust H∞ tracking control for a class of uncertain Lur'e singular systems is studied. A practical and general failure model of actuator and sensor is considered by using convex polytopic uncertainties to describe control surface impairment. Some sufficient conditions are presented for the case of actuator, sensor and control surface failures in terms of linear matrix inequalities (LMIs). The resultant control systems are reliable in that they guarantee closed-loop system robust stability with H∞ performance and the output tracking the reference signal without steady-state error when all control components are operational as well as when some control components experience failures. Finally, a numerical example is given to show the effectiveness of the proposed methods.     

组态软件与Modbus协议在矿用传感器调校装置中的应用

针对现有的传感器调校装置存在缺乏数据实时显示和处理、自动闭环控制、通信接口功能等问题,提出了一种将组态软件与Modbus通信协议应用于矿用气体传感器调校装置的方法。该方法利用串行口和Modbus通信协议将所调校的传感器通过单片机和上位机相连,可实时控制传感器调校的整个过程,并能动态采集、处理各传感器数据。实际应用表明,该方法实现了矿用气体传感器调校装置的自动化、精确化,保障了煤矿的生产安全。     

Active learning strategy for smart soft sensor development under a small number of labeled data samples

This contribution proposes a new active learning strategy for smart soft sensor development. The main objective of the smart soft sensor is to opportunely collect labeled data samples in such a way as to minimize the error of the regression process while minimizing the number of labeled samples used, and thus to reduce the costs related to labeling training samples. Instead of randomly labeling data samples, the smart soft sensor only labels those data samples which can provide the most significant information for construction of the soft sensor. In this paper, without loss of generality, the smart soft sensor is built based on the widely used principal component regression model. For performance evaluation, an industrial case study is provided. Compared to the random sample labeling strategy, both accuracy and stability have been improved by the active learning strategy based smart soft sensor.     

基于软测量的球磨机优化控制方法

针对球磨机控制的难点和不足,提出了一种基于料位软测量技术的球磨机优化控制方法.首先,在分析球磨机系统特性和振动特性的基础上,确定了料位软测量的辅助变量.其次,基于最小二乘支持向量机算法,给出了一种球磨机料位软测量方法,并通过现场实测数据进行料位检测,结果表明该软测量方法的精度较高;最后,在料位软测量的基础上,提出了一种...