Open-loop Observer Research Articles

A Hierarchical approach for isolating sensor faults from un-stealthy attacks in large-scale systems

This paper proposes a novel hierarchical-adaptive threshold abnormal behavior discrimination scheme (HATAD) for Lipschitz nonlinear large-scale systems with disturbances and uncertain dynamics. Two layers of groups of interlinked observers, namely the supervisor and local layers, are designed. The local layer using open loop observers, switching technique, and local controllers is first developed to protect the physical system from the attack effects, where the proposed switching technique can connect the plant to the local controller under the attack conditions. At the supervisor layer, the main controllers and three types of observers are constructed to detect and discriminate the abnormal behaviors and determine the faulty unit. This architecture leads to less restrictive mathematical conditions and analyses, which ensure the stability and the L2−L∞ performance of the estimation error dynamics. To demonstrate the effectiveness of the proposed approach, a simulation study has been conducted on a large-scale system of two units of benchmark continuous stirred tank reactor (CSTR).

Average density estimation for urban traffic networks: Application to the Grenoble network

This paper deals with the problem of the average density estimation in large-scale traffic networks, without requiring to know the density of each individual road. This is achieved by the design of a reduced-order open-loop observer. In general, this type of observers requires some specific graph properties, but we show that it is possible to find a virtual representation of the network that satisfies these conditions, by diving each road into a number of cells of specific length. The virtual network is shown to provide close approximations to the average density of the real system for large enough networks. Algorithms to efficiently calculate the observer parameters are proposed. This approach is based on the assumption that traffic dynamics are linear, and is applied at first in free-flow regime. Using microscopic simulations and real data we evaluate the observer performance even when congestion is present in the network.

Detection and isolation of current-sensor and open-switch faults in electric traction drives

In this work, a strategy for detection and isolation of current-sensors and open-switch faults in electric traction drives is proposed. An induction motor drive with only two current sensors is considered for the design of the proposed strategy. The current estimations from a simple open-loop observer are used to perform the fault detection and isolation. In addition, the same observer estimates the rotor flux angle required in a vector control strategy. Simulation results analyze the sensitivity to parametric and operating point variations. Moreover, the performance of the proposed approach is validated in the event of different types of faults, considering the dynamic behavior of an electric vehicle. Performed tests include gain and disconnection sensor faults and open-switch faults in the inverter.

Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries

Batteries are everywhere, in all forms of transportation, electronics, and constitute a method to store clean energy. Among the diverse types available, the lithium-iron-phosphate (LiFePO4) battery stands out for its common usage in many applications. For the battery’s safe operation, the state of charge (SOC) and state of health (SOH) estimations are essential. Therefore, a reliable and robust observer is proposed in this paper which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates. For this purpose, a battery model was developed by establishing an equivalent-circuit model with the ambient temperature and the current as inputs, while the measured output was adopted to be the voltage where current and terminal voltage sensors are utilized. Another vital contribution is formulating a comprehensive model that combines three parts: a thermal model, an electrical model, and an aging model. To ensure high accuracy rates of the proposed observer, we adopt the use of the dual extend Kalman filter (DEKF) for the SOC and SOH estimation of LiFePO4 batteries. To test the effectiveness of the proposed observer, various simulations and test cases were performed where the construction of the battery system and the simulation were done using MATLAB. The findings confirm that the best observer was a voltage-temperature (VT) observer, which could observe SOC accurately with great robustness, while an open-loop observer was used to observe the SOH. Furthermore, the robustness of the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters. The results demonstrate the reliability and robustness of the proposed observer for simultaneously estimating the SOC and SOH of LiFePO4 batteries.

A Seamless Transition Scheme of Position Sensorless Control in Industrial Permanent Magnet Motor Drives With Output Filter and Transformer for Oil Pump Applications

This article proposes a position sensorless control scheme for the induction and permanent magnetic low-voltage (LV) motor drives with an output filter and transformer for an electric submersible pump (ESP) and progressive cavity pump (PCP). The proposed sensorless strategy covers the full-speed range for ESP drives. An open velocity loop, current regulated sensorless controller is utilized to drive induction and permanent magnet motors (PMMs) during starting and at low speeds. A field-oriented controller (FOC) that utilizes an estimated rotor position based upon motor back electromotive force (EMF) is utilized to drive the motor at higher speeds. A seamless transition between controllers for the two operational modes, i.e., low-speed control and high-speed control, is proposed in this article. With velocity mode control over the full-speed range and mode control hysteresis, a smooth transition between open loop and EMF-based observer control can be achieved. The sensorless control scheme presented in this article has been implemented in a commercial drive for an ESP (deep well) application.

Average density detectability in traffic networks using virtual road divisions

In this paper, we demonstrate the existence of a reduced-order open-loop observer to estimate the average density in a region of a large scale traffic network. We show that traffic networks are not generally average detectable, but that it is possible to find a virtual representation of the network using inhomogeneous road divisions such that the observer converges to the true values. We express the conditions for the required number of cells per road and their lengths such that the system is average detectable in terms of the network’s topology and physical parameters. Moreover, we propose a method to calculate these divisions and give asymptotic bounds on the quality of the approximations.

Observer-based compensation of thermal disturbances for linear displacement sensors

A compensation method is proposed that enables the correction of temperature disturbance effects on the mechanical structure of linear displacement sensors, when measuring in environments with moderately changing temperatures. Based on the surface temperature information of the sensor housing, an open loop observer estimates the thermal error, considering the clamping configuration of the sensor with respect to the target surface. Correspondingly, the indicated value is corrected by the estimated thermal error. The validity of the correction after calibration is checked by various experiments, in which setup settings are varied and different time-temperature-sequences are tested.

Error bounds for Kalman filters on traffic networks

This work analyzes the estimation performance of the Kalman filter (KF) on transportation networks with junctions. To facilitate the analysis, a hybrid linear model describing traffic dynamics on a network is derived. The model, referred to as the switching mode model for junctions, combines the discretized Lighthill-Whitham-Richards partial differential equation with a junction model. The system is shown to be unobservable under nearly all of the regimes of the model, motivating attention to the estimation error bounds in these modes. The evolution of the estimation error is investigated via exploring the interactions between the update scheme of the KF and the intrinsic physical properties embedded in the traffic model (e.g., conservation of vehicles and the flow-density relationship). It is shown that the state estimates of all the cells in the traffic network are ultimately bounded inside a physically meaningful interval, which cannot be achieved by an open-loop observer.

Periodic Disturbance Rejection Control Based on Observer and Switching in Photo-Conductor Drum with Planetary Gear System

A servo control architecture is proposed for the photo-conductor drum drive using planetary gears in a production printer. The velocity fluctuation of the photo-conductor drum is one of the main causes of color banding. Most of the velocity fluctuations come from gear eccentricity that is particularly large in injection molded plastic gear. In order to obtain high image quality, a servo controller design for periodic disturbance reduction is needed. Feedback and feedforward controllers are used to achieve higher performance. This paper proposes a new feedforward control strategy to reduce the effects of the periodic disturbances that are caused by the transmission error of the planetary gears. The proposed control strategy, based on a switching scheme and an open-loop observer, compensates the periodic disturbances. The advantage of the proposed method is that periodic disturbances can be reduced without sacrificing feedback performance. An experiment on a prototype is carried out to verify the control performances. The results show that 90[%] of periodic disturbances are reduced by the proposed control algorithm.

Improved sensor fault detection, isolation, and mitigation using multiple observers approach

ABSTRACTTraditional fault detection and isolation (FDI) methods analyze a residual signal to detect and isolate sensor faults. The residual signal is the difference between the sensor measurements and the estimated outputs of the system based on an observer. The traditional residual-based FDI methods, however, have some limitations. First, they require that the observer has reached its steady state. In addition, residual-based methods may not detect some sensor faults, such as faults on critical sensors that result in an unobservable system. Furthermore, the system may be in jeopardy if actions required for mitigating the impact of the faulty sensors are not taken before the faulty sensors are identified. The contribution of this paper is to propose three new methods to address these limitations. Faults that occur during the observers' transient state can be detected by analysing the convergence rate of the estimation error. Open-loop observers, which do not rely on sensor information, are used to detect faults on critical sensors. By switching among different observers, we can potentially mitigate the impact of the faulty sensor during the FDI process. These three methods are systematically integrated with a previously developed residual-based method to provide an improved FDI and mitigation capability framework. The overall approach is validated mathematically, and the effectiveness of the overall approach is demonstrated through simulation on a five-state suspension system.

Improved Fault-Tolerant Control for Brushless Permanent Magnet Motor Drives With Defective Hall Sensors

Brushless permanent magnet motor drives based on Hall sensors have received significant attention in recent years. In this area, the faults of Hall sensors become a new concern and several fault-tolerant control (FTC) methods have been proposed. However, most of the state-of-the-art FTC methods require some time to reconstruct the correct Hall sensor signals, which results in significant transient currents and speed dip during fault diagnostic process (FDP). In this paper, a new and improved FTC scheme based on FDP and vector-tracking observer is proposed. A method to identify the duration of FDP is proposed based on the analysis of acceleration estimation and the fault diagnosis results. During FDP, the method defaults to an open-loop observer control, which removes the undesirable current/torque transient. After that, the close-loop observer is re-enabled and the motor operation is restored. The proposed FTC is demonstrated in detailed simulations and experimentally on 120° brushless dc motor drives and sinusoidal PM motor drives. For both types of drives, a significant improvement is achieved in steady state and transient operation with faults of up to two Hall sensors, which has not been possible with available alternative FTC approaches (unless a sensorless control is used).

感光体ドラム駆動に対応した高精度遊星歯車における周期変動補正制御技術

A new planetary gear using plastic gear and control system for photo-conductor (PC) drum drive in production printing is proposed. In order to obtain high image quality at low cost, driving technology using plastic gear to keep the PC velocity constant is needed. A feedback (FB) and feedforward (FF) controller is adapted to achieve ever higher performance. This paper proposed a new FF control strategy for reducing the periodic disturbance that is caused by transmission error of the planetary gears. The proposed control strategy reject the periodic disturbance based on switching scheme and open-loop observer. The advantage of proposed method is that periodic disturbance can be rejected without sacrifice of feedback performance. An experiment on prototype is carried out to verify the control performance. The experiment show that 90[%] periodic disturbance is reduced by the proposed control algorithm.

Robust Diagnosis Method Based on Parameter Estimation for an Interturn Short-Circuit Fault in Multipole PMSM under High-Speed Operation.

This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates the q-axis inductance (Lq) of the faulty PMSM to solve this problem. The proposed method also estimates the faulty phase and the value of G, which serves as an index of the severity of the fault. The q-axis current is used to estimate the faulty phase, the values of G and Lq. For this reason, two open-loop observers and an optimization method based on a particle-swarm are implemented. The q-axis current of a healthy PMSM is estimated by the open-loop observer with the parameters of a healthy PMSM. The Lq estimation significantly compensates for the estimation errors in high-speed operation. The experimental results demonstrate that the proposed method can estimate the faulty phase, G, and Lq besides exhibiting robustness against parameter uncertainties.

Model recovery anti-windup for output saturated SISO linear closed loops

We define model recovery anti-windup for SISO linear control systems with output saturation. We address the problem by relying on a hybrid modification of the linear closed loop which employs a suitable logic variable to activate/deactivate various components of a control scheme. The scheme relies on a finite-time observation law, an open-loop observer and an open-loop input generator which is capable of driving the plant output within the saturation limits. Then the control scheme is based on suitable (hybrid) resetting laws allowing the controller to operate on the artificial output signal generated by the open-loop observer when the actual plant output is outside the saturation limits. Unlike existing results, not only we prove uniform global asymptotic stability of the closed loop, but we also prove the local preservation and global recovery properties, typical of model recovery anti-windup paradigms. We also illustrate the proposed technique on an example study.

Rotor Temperature Modeling of an Induction Motor using Subspace Identification

Knowledge of the rotor temperature is important for an efficient and secure operation of induction motors, especially in electric vehicles. However, in vehicle applications, measuring the rotor temperature is not possible, making a model-based estimation necessary. In this paper, the modeling of the rotor temperature is presented based on subspace identification, a black-box system identification method. The performed steps to achieve a high quality model are described in detail, including a systematic selection of inputs from the large amount of available signals. The resulting model is applied as an open-loop observer and evaluated using measurements of a specially equipped induction motor on a test bench, where the rotor temperature was measurable. Finally, some remarks are given regarding the on-board implementation of the identified model into a vehicle control unit for open-loop observation of the rotor temperature.

Adaptive length SMA pendulum smart tuned mass damper performance in the presence of real time primary system stiffness change

In a companion paper, Pasala and Nagarajaiah analytically and experimentally validate the Adaptive Length Pendulum Smart Tuned Mass Damper (ALP-STMD) on a primary structure (2 story steel structure) whose frequencies are time invariant (Pasala and Nagarajaiah 2012). In this paper, the ALP-STMD effectiveness on a primary structure whose frequencies are time varying is studied experimentally. This study experimentally validates the ability of an ALP-STMD to adequately control a structural system in the presence of real time changes in primary stiffness that are detected by a real time observer based system identification. The experiments implement the newly developed Adaptive Length Pendulum Smart Tuned Mass Damper (ALP-STMD) which was first introduced and developed by Nagarajaiah (2009), Nagarajaiah and Pasala (2010) and Nagarajaiah et al. (2010). The ALP-STMD employs a mass pendulum of variable length which can be tuned in real time to the parameters of the system using sensor feedback. The tuning action is made possible by applying a current to a shape memory alloy wire changing the effective length that supports the damper mass assembly in real time. Once a stiffness change in the structural system is detected by an open loop observer, the ALP-STMD is re-tuned to the modified system parameters which successfully reduce the response of the primary system. Significant performance improvement is illustrated for the stiffness modified system, which undergoes the re-tuning adaptation, when compared to the stiffness modified system without adaptive re-tuning.

An Orientation Estimator for the Wheelchair's Caster Wheels

Wheelchair ergometers are a highly valuable tool in the study of the biomechanics of manual wheelchair propulsion. However, current ergometers have some drawbacks that affect their level of realism. For example, the moment of inertia of the wheelchair-user system and the caster wheels' orientation are usually neglected, despite their high influence on the wheelchair's behavior. Taking these factors into account requires a complex dynamic model, and the calibration of such a model requires on-the-field recordings of the caster wheels' orientation, which are currently difficult to obtain. In this paper, we have proposed an open-loop observer that estimates each caster wheel's orientation (CWO) based only on the rear wheels' kinematics. The model was validated by propelling the wheelchair on three different floors (vinyl, carpet, and concrete) with five different normal forces between the caster wheels and the ground. Comparison between the estimated CWO and a reference one recorded by an optoelectronic device gave an accuracy error of less than ±8°. This error reduced to ±5° when the wheelchair was propelled following straight or slightly curved patterns. This observer has implications in the design of better wheelchair ergometers and simulators, as well as in the control of electric wheelchairs.

Two-degree-of-freedom Controller Design for Uncertain Processes Using Input/output Linearization Control Technique

In this work, a new control method for uncertain processes is developed based on two-degree-of-freedom control structure. The setpoint tracking controller designed by input/output linearization technique is used to regulate the disturbance-free output and the disturbance rejection controller designed is designed by high-gain technique. The advantage of two-degree-of-freedom control structure is that setpoint tracking and load disturbance rejection controllers can be designed separately. Open-loop observer is applied to provide disturbance-free response for setpoint tracking controller. The process/disturbance-free model mismatches are fed to the disturbance rejection controller for reducing effect of disturbance. To evaluate the control performance, the proposed control method is applied through the example of a continuous stirred tank reactor with unmeasured input disturbances and random noise kinetic parametric uncertainties. The simulation results show that both types of disturbances can be effectively compensated by the proposed control method.

Output Prediction Method Based on Model and its Application in Power Systems

An output prediction method based on state space model is proposed to overcome the poor reliability of the prediction method that does not use system model. The open-loop state observer is established based on the system state space model. Then the output prediction model is built in which the prediction error is used as input and a correction module is also contained. The module is used to correct the prediction error, and then the current predicted output can be obtained by the model from the delayed output. At last, a wide-area damping controller in power systems based on output prediction is designed to verify the effectiveness of the method.

Nonlinear feedback control of a preheater-integrated molten carbonate fuel cell system

A kW-class molten carbonate fuel cell with direct internal reforming is presented. Within an additional preheating framework, the estimation and control technique is implemented to this kind of nonlinear systems. By the proposed algorithm, the steady-state optimization algorithm subject to prescribed physical constraints is used to determine the desired operating condition, an open-loop observer design provides effective state estimation, and the nonlinear feedback control ensures the bounded stack temperature regulation in spite of unknown inlet perturbations. Finally, the proposed control methodology is successfully verified by numerical simulations.