Virtual Sensor Design Research Articles

PCR virtual temperature sensor design based on system modeling and identification

The reaction results of Polymerase chain reaction (PCR) are highly sensitive to temperature accuracy, but the reaction liquid temperature is hard to be measured directly. In this paper, a virtual temperature sensor is creatively designed to directly obtain the reaction liquid temperature using a model-switching approach. This study first establishes the mathematical models of the temperature control system and obtains precise system models for the heating and cooling stages. Based on this, a virtual sensor is constructed, and a closed-loop fuzzy PID control system is established. Furthermore, the accuracy of the designed virtual temperature sensor is verified through simulation and experimentation. Simulation results show that the fuzzy PID control method has higher temperature accuracy, with a deviation of 0.23 °C, making it more suitable for Peltier systems, as Peltier systems suffer from inconsistent temperature rise and fall models. The experimental results show that the control method using the virtual sensor achieves higher precision in liquid temperature control, with an accuracy of ±0.21 °C. Finally, standard PCR procedures are performed for designed chip, and the results indicate that the temperature sensor and control system designed in this study exhibit significantly higher amplification efficiency, approximately 16 times greater than traditional control methods.

Method of Virtual Sensor Design for Faulty Physical Sensor Replacement

The paper considers the problem of virtual sensor design for nonlinear dynamic systems with non-smooth nonlinearities described by continuous-time models for faulty physical sensor replacement. The main purpose of virtual sensors is generating the estimates of the unmeasured components of the considered system to provide additional information for effective control and fault diagnosis. Besides, virtual sensors can be used for faulty physical sensor replacement. The methods of virtual sensor design for solving this problem differ from standard procedure since information from faulty physical sensor does not use to design the virtual sensor replacing this sensor. It is assumed that to solve the problem, the system is equipped by diagnostic system allowing detecting faulty sensor. For every such a sensor, the virtual sensor generating estimate replacing the faulty sensor is designed. To solve the problem, so-called logic-dynamic approach is used which does not guarantee optimal solution but uses only methods of linear algebra to solve the problem for systems with non-smooth nonlinearities. This approach contains three steps. Initially, the nonlinear term is removed from system and linear model is designed. Then, a possibility to estimate the faulty sensor and to insert in the model the transformed nonlinear term is checked. Finally, stability of sensor is provided. The virtual sensor can be designed in identification canonical form or Jordan canonical form. The advantage of the first form is a standard procedure of the virtual sensor design while Jordan form allows obtaining simpler solution. The relations allowing designing the virtual sensor as in identification canonical as Jordan canonical form are derived.

Virtual Sensor Design for Replacement the Faulty Physical Sensors

Abstract: The paper considers the problem of virtual sensor design for nonlinear dynamic systems with non-smooth nonlinearities described by continuous-time models for faulty physical sensor replacement. It is assumed that to solve the problem, the system is equipped by diagnostic system allowing detecting and isolating the faulty sensor. For every such a sensor, the virtual sensor generating estimate replacing the faulty sensor is designed. To solve the problem, so-called logic-dynamic approach is used which does not guarantee optimal solution but uses only methods of linear algebra to solve the problem for systems with non-smooth nonlinearities. The virtual sensor can be designed in the identification canonical form or Jordan canonical form. The advantage of the first form is a standard procedure of the virtual sensor design while Jordan form allows obtaining a simpler solution. The relations allowing designing the virtual sensor both in identification and in Jordan canonical form are derived.

Virtual Sensors for Nonlinear Discrete-Time Dynamic Systems

The problem of virtual sensor design for nonlinear systems under the disturbance is investigated. Two different mathematical techniques are used to solve the problem: the algebra of functions and the logic-dynamic approach. The first one allows obtaining a general solution while the second one produces a solution for nonlinear systems by linear algebra methods. The virtual sensors are designed to be insensitive to the disturbance based on invariant functions. They estimate the prescribed function of the original system state vector. The practical example illustrates theoretical results.

Novel Virtual Speed Sensor Design for Fault-Tolerant Vector Control for Induction Motor Drives Based on the Non-Linear Unscented Kalman Filter

Novel Virtual Speed Sensor Design for Fault-Tolerant Vector Control for Induction Motor Drives Based on the Non-Linear Unscented Kalman Filter

Virtual Sensor Design for Linear and Nonlinear Dynamic Systems

Abstract: The problem of virtual sensors design in linear and nonlinear systems is studied. The problems is solved in three steps: at the first step, the linear model invariant with respect to the disturbance is designed; at the second step, a possibility to take into account the nonlinear term and to estimate the given variable is checked; finally, stability of the observer is achieved. The relations allowing to design virtual sensor of minimal dimension estimating prescribed component of the state vector of the system are obtained. The theoretical results are illustrated by practical example.

Methods of robust virtual sensor design

Methods of robust virtual sensor design

DLSense: Distributed Learning-Based Smart Virtual Sensing for Precision Agriculture

This work presents the design of an efficient edge-empowered sensor-cloud architecture equipped with a smart virtual sensing scheme for precision agriculture. Traditionally, in agricultural sensor-cloud, sensor nodes send raw sensed data periodically to the cloud, resulting in higher latency and higher energy and bandwidth consumption. The environment-dependent nature of agricultural parameters also limits the serviceability of sensor-cloud in regions with damaged or unemployed sensors. Moreover, agricultural sensor-cloud suffers from privacy issues due to the sharing of sensitive farming data across third-party service providers. To address these drawbacks, we first propose a modified sensor-cloud architecture using edge devices as the middleware layer for sensor virtualization, thereby reducing service provisioning latency and resource consumption. Next, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DLSense</i> , a novel intelligent virtualization scheme to aid in the design of virtual sensors in the absence of working sensor nodes in a region. DLSense utilizes correlation theory and distributed learning in the edge devices to predict sensor data and enables the sharing of information of the trained models instead of raw sensed data, thus imparting privacy. Finally, we evaluate the performance of the DLSense scheme through extensive simulations and an experimental case study of an agricultural application. Results demonstrate that our proposed scheme reduces latency and service cost by 81% and 66%, respectively, and increases service availability by 39% compared to the state-of-the-art methods.

Fault tolerant control for linear parameter varying systems: An improved robust virtual actuator and sensor approach

This paper presents a robust Fault-Tolerant Control (FTC) methodology for the design of virtual sensors and virtual actuators for discrete-time Linear Parameter Varying (LPV) systems. Conditions based on Linear Matrix Inequalities (LMIs) are proposed for the synthesis of a reconfiguration block composed of a virtual actuator and a virtual sensor, guaranteeing input-to-state stability (ISS). The main contribution of the proposed FTC approach is to deal with LPV models where input and output matrices can be parameter-dependent. Moreover, differently from results found in the literature, a single reconfiguration block can be designed to be robust to different kinds and magnitudes of faults. Real-time level-control experiments illustrate the efficiency of the proposed procedure; the system used in the experiments consists of a nonlinear two coupled tanks with two inputs and two outputs, represented by an LPV model subject to sensor and actuator faults. Experimental results and comparisons with results in the literature indicate that the proposed approach is able to mitigate the fault effects with better performance indices than the literature approaches.

Virtual Diagnostic Sensors Design for an Automated Guided Vehicle

In recent years, Automated Guided Vehicles (AGVs) have been playing an increasingly important role in producing industry and infrastructure and will soon arrive to other areas of human life such as the transportation of goods and people. However, several challenges still aggravate the operation of AGVs, which limit the amount of implementation. One major challenge is the realization of reliable sensors that can capture the different aspects of the state of an AGV as well as its surroundings. One promising approach towards more reliable sensors is the supplementary application of virtual sensors, which are able to generate virtual measurements by using other sources of information such as actuator states and already existing sensors together with appropriate mathematical models. The focus of the research described in this paper is the design of virtual sensors determining forces and torques acting on an AGV. The proposed novel approach is using a quadratic boundedness approach, which makes it possible to include bounded disturbances acting on the AGV. One major advantage of the presented approach is that the use of complex tire models can be avoided. Information from acceleration and yaw rate sensors is processed in order to realize reliable virtual force and torque sensors. The resulting force and torque information can be used for several diagnostic purposes such as fault detection or fault prevention. The presented approach is explained and verified on the basis of an innovative design of an AGV. This innovative design addresses another major challenge for AGVs, which is the limited maneuvering possibilities of many AGV designs. The innovative design allows nearly unlimited maneuvering possibilities but requires reliable sensor data. The application of the approach in the AGV resulted in the insight that the generated estimates are consistent with the longitudinal forces and torques obtained by a proven reference model.

Sensors Faults: A YJBK Approach for Compensation

The focus in this paper is on compensation for sensor faults. Virtual sensors or compensation using the YJBK controller architecture (after Youla, Jabr, Bongiorno and Kucera) are two ways to compensate sensor faults without changing the nominal controller directly. Design of virtual sensors is quite simple due to the separation between the nominal controller and the virtual sensor. A short analysis of the virtual sensor in connection with the YJBK controller architecture is given.Further, a reformulation of the YJBK controller architecture is given and the connection with the Bezout equation is described. It is shown that this new formulation makes it easy to change the sensors in the system without changing the nominal controller, but only extend the included system matrices. System uncertainties in connection with sensor faults will also be considered in connection with the YJBK controller architecture.

Design of diagnostic estimators for an automated guided vehicle

The paper deals with the design of virtual sensors of longitudinal forces as well as torques acting onto an automated guided vehicle. These virtual sensors are based on a measurement set associated with accelerations, velocities and yaw rate sensors mounted on the robot. Subsequently, the estimated forces and torques are used for diagnostic purposes concerning their appropriate distributions. The main novelty of the proposed approach is that it eliminates the necessity of incorporating wheel models, which usually impairs the performance of the approaches proposed in the literature. The final part of the paper presents experimental results, which clearly exhibit the performance of the proposed approach.

Aircraft virtual sensor design via a Time-dependent Functional Pooling NARX methodology

A Time-dependent Functional Pooling Nonlinear AutoRegressive with eXogenous excitation (TFP-NARX) methodology for aircraft virtual sensor design is introduced. The methodology is unique in establishing a single but global nonlinear dynamical model, referred to as TFP-NARX, from data obtained from several individual flights, each corresponding to different flight conditions and aircraft configurations. This model structure is demonstrated to be capable of accurately representing the aircraft nonlinear dynamics under various flight conditions and aircraft configurations in terms of aircraft weight and center of gravity. Based on this model structure, three individual designs are postulated: A “fixed” design pertaining to a single aircraft weight and center of gravity configuration, as well as two more involved designs, a “basic” and an “extended” one, that account for various aircraft configurations. The three designs are subsequently employed for the development of angle-of-attack virtual sensors for the main flight regimes (landing, take-off, clean flight) of a small commercial aircraft. The performance of the developed virtual sensors is examined via a number of validation flights within a nonlinear simulation environment and are shown to meet the requirements of low mean and peak error.

NOx virtual sensor design via in-cylinder pressure feature extraction

In this paper, a novel approach for NOx generation modeling in heavy-duty (HD) Diesel engines is proposed. Only the indicated pressure and the speed measurements are used, standing on the assumption that all combustion phenomenona are reflected by the crank angle resolved pressure trajectory. A principal component analysis is performed to describe the information included in the pressure by means of a limited set of variables; this enables the use of simple identification techniques to derive a simple and reliable predictor, also suited for on-line estimation. The proposed strategy is implemented on a off-road HD Diesel engine and validated on a standard test cycle.

The state of the art in chemical process control in Japan: Good practice and questionnaire survey

In this age of globalization, the realization of production innovation and highly stable operation is the chief objective of the process industry in Japan. Obviously, modern advanced control plays an important role to achieve this target, but the key to success is the maximum utilization of PID control and conventional advanced control. This paper surveys how the three central pillars of process control – PID control, conventional advanced control, and linear/nonlinear model predictive control – have been used and how they have contributed toward increasing productivity. In addition to introducing eminently practical methods, emerging methods, and their applications, the authors point out challenging problems. In Japan, industry and academia are working in close cooperation to share their important problems and develop new technologies for solving them. Several methods introduced in this paper are results of such industry–academia collaboration among engineers and researchers in various companies and universities. Furthermore, soft-sensor or virtual sensor design is treated with emphasis on its maintenance, because soft-sensors must cope with changes in process characteristics for their continuous utilization. Maintenance is a key issue not only for soft-sensors but also for controllers. Finally, we will expand our scope and briefly introduce recent activities in tracking simulation and alarm management. A part of the results of our recent questionnaire survey of process control are also introduced; the results are extremely helpful in clarifying the state of the art in chemical process control in Japan.

The State of the Art in Advanced Chemical Process Control in Japan

In this age of globalization, the realization of production innovation and highly stable operation is the chief objective of the process industry in Japan. Obviously, modern advanced control plays an important role to achieve this target; but it is emphasized here that a key to success is the maximum utilization of PID control and conventional advanced control. This paper surveys how the three central pillars of process control – PID control, conventional advanced control, and linear/nonlinear model predictive control – have been used and how they have contributed toward increasing productivity. In addition to introducing eminently practical methods, emerging methods, and their applications, the authors point out challenging problems. In Japan, industry and academia are working in close cooperation to share their important problems and develop new technologies for solving them. Several methods introduced in this paper are results of such industry-academia collaboration among engineers and researchers in various companies and universities. Furthermore, soft-sensor or virtual sensor design is treated with emphasis on its maintenance, because soft-sensors must cope with changes in process characteristics for their continuous utilization. Maintenance is a key issue not only for soft-sensors but also for controllers. Finally, we will expand our scope and briefly introduce recent activities in tracking simulation and alarm management. A part of the results of our recent questionnaire survey of process control are also introduced; the results are extremely helpful in clarifying the state of the art in process control in Japan.

Virtual instruments in refineries

Environmental quality monitoring must have large data acquisition and distribution systems for industrial plants. In particular, refineries must comply with government laws that enforce strict limits on product specifications and pollutant emissions, thus pushing them towards adopting increasingly efficient measurement and control policies to monitor these process variables. The article presents representative examples of the design of virtual sensors devoted to the monitoring of processes in oil refining. The examples were selected to outline different aspects of the design and application of virtual sensors.

Neural virtual sensors for terrain adaptation of walking machines

When walking in realistic conditions, accurate, reliable sensorial information is critical to ensure the safe operation of legged robots. That means a large number of sensors, cabling, and electronic systems must be used, complicating the robot. On the other hand, the great complexity of the hardware of walking machines is one of the main obstacles preventing the introduction of this kind of vehicle in real applications; consequently this hardware should be simplified. These antagonistic requirements can be reconciled by the use of what are called virtual sensors. This paper addresses the design of virtual sensors for terrain adaptation developed with the aims of simplifying the hardware of the walking machine or increasing the reliability of the sensorial information available. These virtual sensors are based on neural networks and can estimate the forces exerted by the feet from data extracted from joint-position sensors, which are mandatory in all robotic systems. The force estimates are used to detect foot/ground contact. Some experiments carried out with the SILO4 walking robot are reported to prove the efficacy of this method. © 2005 Wiley Periodicals, Inc.