Nonlinear Adaptive Observer Research Articles

An interconnected adaptive observer for flying capacitor multilevel converters

A nonlinear adaptive observer for flying capacitor converters is proposed. The observer estimates simultaneously the capacitor voltages and the load resistance, which adds robustness and improves estimation when system parameters are uncertain. Proposed scheme takes advantage of the converter structure to represent the system as a set of n interconnected subsystems, which allows to overcome the unobservable condition of the original system.This observer can be used to replace the voltage sensors needed to control and monitoring the capacitor voltages. Experimental data is used to validate and evaluate the performance of the proposed scheme.

Residual generation for fault detection and isolation in a class of uncertain nonlinear systems

This article studies the problem of fault detection and isolation (FDI) for a class of uncertain nonlinear systems via a residual signal generated by a novel nonlinear adaptive observer. The considered faults are modelled by a set of time-varying vectors, in which a prescribed subset of faults are specially monitored and thus separable from the other faults. In the presence of Lipschitz-like nonlinearities and modelling uncertainties, the sensitivity of the residual signal to the monitored faults and its insensitivity to the other faults are rigorously analysed. Under a persistent excitation condition, the performances of the proposed fault diagnosis scheme, including the robustness to uncertainties, the quickness of estimation, the accuracy of estimation, the sensitivity to the monitored faults and the insensitivity to the complement faults, are quantified by a series of explicit design functions relevant to the observer parameters. It turns out that the number of faults which can be completely diagnosed is independent of the number of output sensors. A simulation example is given to illustrate the effectiveness of the proposed FDI method.

Multiple Model Adaptive Nonlinear Observer of Dynamic Positioning Ship

Considering the filtering problem of dynamic positioning (DP) ship for the slowly varying sea state, a multiple model adaptive observer (MMAO) for dynamic positioning ship is presented. The MMAO consists of a bank of nonlinear subobserver and a dynamic weighting signal generator, in which each sub-observer is designed based on different peak frequency of wave spectrum model. To improve the performance of the observer, subobserver using the measurement of position, velocity, and acceleration is used to update the estimated velocity of ship. The observer parameters are optimized using particle swarm optimization (PSO). Finally, the method is verified effective by the computer simulation.

An adaptive non-linear observer for the estimation of temperature distribution in the planar solid oxide fuel cell

Minimising the thermal gradients is extremely important in a planar solid oxide fuel cell (SOFC) for improving the cell life. The estimation of the temperature distribution in the cell is necessary to achieve this objective through suitable control, since they are not generally measurable. In this work, we have designed a non-linear adaptive observer for estimating the temperatures inside the hydrogen fed planar SOFC. The observer design is based on a lumped parameter model of the SOFC. The stability of the proposed observer is proven using the Lyapunov function method and is based on the concept of input-to-state stability for cascaded systems. The simulations show that the developed observer can track the temperature and species concentration profiles in the planar SOFC during step changes in the cell current. The adaptive observer presented is valid for a wide operating range, requires fewer variables to be measured, and is robust to fluctuations in the inlet flows.

Adaptive Nonlinear Observer for Electropneumatic Clutch Actuator With Position Sensor

This brief proposes an adaptive nonlinear observer for an electropneumatic clutch actuator. Estimates of piston velocity, chamber pressures, and dynamic friction state are made based on piston position measurement only. Parameter estimations of the clutch load characteristics and friction coefficients are treated through adaptation, and the persistence of excitation conditions for convergence of the estimation errors are derived. The performance of the adaptive observer is evaluated and is compared to experimental measurements obtained in a test truck.

Robust Adaptive Observer Design for Lipschitz Class of Nonlinear Systems

This paper addresses parameter and state estimation problem in the presence of the perturbation of observer gain bounded input disturbances for the Lipschitz systems that are linear in unknown parameters and nonlinear in states. A new nonlinear adaptive resilient observer is designed, and its stability conditions based on Lyapunov technique are derived. The gain for this observer is derived systematically using linear matrix inequality approach. A numerical example is provided in which the nonlinear terms depend on unmeasured states. The simulation results are presented to show the effectiveness of the proposed method. KeywordsAdaptive observer; linear matrix inequality, nonlinear systems; nonlinear observer; resilient observer; robust estimation.

Projective Synchronization for Brushless DC Motor (BLDCM) with Fractional-Order

Based on orthogonal neural network，a stability theorem[9] and back-stepping approach，a novel adaptive nonlinear observer is designed for a class of fractional-order chaotic system where the nonlinear portion of the structure cannt be evaluated. The projective synchronization of fractional-order BLDCM chaotic system can be achieved.

Integrated System Identification and State-of-Charge Estimation of Battery Systems

Accurate estimation of the state of charge in battery systems is of essential importance for battery system management. Due to nonlinearity, high sensitivity of the inverse mapping from external measurements, and measurement errors, SOC estimation has remained a challenging task. This is further compounded by the fact that battery characteristic model parameters change with time and operating conditions. This paper introduces an adaptive nonlinear observer design that compensates nonlinearity and achieves better estimation accuracy. A two-time-scale signal processing method is employed to attenuate the effects of measurement noises on SOC estimates. The results are further expanded to derive an integrated algorithm to identify model parameters and initial SOC jointly. Simulations were performed to illustrate the capability and utility of the algorithms. Experimental verifications are conducted on Li-ion battery packs of different capacities under different load profiles.

Reset Adaptive Observer for a Class of Nonlinear Systems

This technical note proposes a novel kind of state estimator called reset adaptive observer (ReO). A ReO is an adaptive observer consisting of an integrator and a reset law that resets the output of the integrator depending on a predefined condition. The main contribution of this technical note is that the reset element theory is applied for the first time to the nonlinear adaptive observer framework. The introduction of the reset element in the adaptive law can decrease the overshooting and settling time of the estimation process without sacrificing the rising time. The stability and convergence LMI-based analysis of the proposed ReO is addressed and, additionally, an easily computable method to determine the <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\cal L}_{2}$</tex></formula> gain of the ReO dealing with noise-corrupted systems is presented.

On the experimental implementation of a nonlinear adaptive observer

This paper deals with the implementation of an output current estimator for a DC-DC Multiplier Boost Converter (MBC). For that purpose, a real time platform is used for solving the dynamic equations of a nonlinear adaptive observer. Excellent performance is achieved even during demanding conditions. In particular, a reliable estimation is obtained when an experimental nonlinear dynamic system is utilized as an electric load connected at the converter terminals.

Adaptive scheme for DC voltages estimation in a cascaded H-bridge multilevel converter

Abstract A nonlinear adaptive observer for a cascaded H-bridge multilevel converter is proposed. Using an instantaneous model of the system arranged as a set of subsystems, to take advantage of the converter structure, an adaptive observer is designed. The proposed observer is able to work even in the presence of system parameter uncertainties. This observer scheme can be used to replace the voltage sensors needed to control and monitoring the system capacitor voltages. Simulation results are used to validate the performance of the proposed observer when the multilevel converter is used as an electrical network compensator.

A Nonlinear Adaptive Resilient Observer Design for a Class of Lipschitz Systems Using LMI

This paper addresses the parameter and state estimation problem in the presence of the observer gain perturbations for Lipschitz systems that are linear in the unknown parameters and nonlinear in the states. A nonlinear adaptive resilient observer is designed, and its stability conditions based on the Lyapunov technique are derived. The gain for this observer is derived systematically using the linear matrix inequality approach. A numerical example and a physical setup are provided to show the effectiveness of the proposed method.

Fault diagnosis for singular stochastic systems

This paper studies the fault diagnosis of singular stochastic systems. The probability distribution of output is measured by probability density functions (PDFs), which are modeled by a square root B-spline expansion. An adaptive nonlinear observer is proposed to estimate the size of the fault occurring in systems. Furthermore, the linear matrix inequality (LMI) approach is applied to establish sufficient conditions for the existence of the observer. Finally, the simulation results are given to indicate the method for diagnosing the fault.

Adaptive Observer for DC Voltages in a cascaded H-bridge multilevel converter

AbstractUsing an instantaneous model of a cascaded H-bridge multilevel converter a nonlinear adaptive observer is proposed. The model of the system is arranged as a set of subsystems, in order to take advantage of the converter structure, for designing the observer. This observer scheme can be used to replace the voltage sensors needed to control and monitoring the system capacitor voltages even in the presence of system parameter uncertainties. Simulation results are used to validate the performance of the proposed observer when the multilevel converter is used as an electrical network compensator.

Adaptive observer-based switched control for electropneumatic clutch actuator with position sensor

AbstractIn this paper we extend previous control design applied to an electropneumatic clutch actuator. A dual-mode switched nonlinear controller design and an adaptive nonlinear observer design are combined to achieve position control of the clutch actuator with only position measurements available. The observer provides estimates of position, velocity, chamber pressures, friction state and parameters, and clutch load characteristic parameters. The paper focus on design for implementation in a heavy duty truck system, and focus on performance evalution using simulations. Performance is tested with a simulation model which is validated against experimental results from a heavy duty test truck, showing no significant loss of performance due to lack of a pressure sensor.

Adaptive Observer for Three Phase Source Voltage Under Unbalanced Conditions

In this paper the problem of estimating amplitude, phase and frequency of the main component of three-phase line voltage under unbalanced conditions is considered. Unbalancing is a common condition and generates a so-called negative sequence in the line voltage, which may affect relevantly estimation of main components dynamics. Different adaptive schemes are proposed and analyzed. First of all, a straightforward solution derived by LTI observer with frequency adaptation is analyzed and its high sensitivity to negative sequence component is underlined. Hence, an adaptive nonlinear observer is proposed, exploiting the properties of a synchronous reference frame to represent the line voltage. Its larger robustness to negative sequence and voltage harmonics is verified by analysis and simulations. Finally, the latter solution is enhanced by adding the negative sequence model to the basic observer structure. This allows for perfect compensation if the unbalancing effects. Adaptation law for this solution is fairly different form the previous one and a completely different stability analysis is required. Simulation results are also provided to demonstrate the effectiveness of the proposed scheme even under large unbalancing.

Design of a smart MEMS accelerometer using nonlinear control principles

This paper presents a novel smart MEMS accelerometer which employs a hybrid control algorithm and an estimator. This scheme is realized by adding a sliding-mode controller to a conventional PID closed loop system to achieve higher stability and higher dynamic range and to prevent pull-in phenomena by preventing finger displacement from passing a maximum preset value as well as adding an adaptive nonlinear observer to a conventional PID closed loop system. This estimator is used for online estimation of the parameter variations for MEMS accelerometers and gives the capability of self testing to the system. The analysis of convergence and resolution show that while the proposed control scheme satisfies these criteria it also keeps resolution performance better than what is normally obtained in conventional PID controllers. The performance of the proposed hybrid controller investigated here is validated by computer simulation.

Nonlinear adaptive observer-based sliding mode control for LAMOST mount driving

Heavy disturbances caused mainly by wind and friction in the mount drive system greatly impair the pointing accuracy of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). To overcome this negative effect, a third order Higher Order Sliding Mode (HOSM) controller is proposed. The key part of this approach is to design an appropriate observer which obtains the acceleration state. A nonlinear adaptive observer is proposed in which a novel polynomial model is applied to estimate the internal disturbances of the mount drive system. Theoretical analysis demonstrates the stability of the proposed observer. Simulation results show that this nonlinear adaptive observer can obtain a high precision acceleration signal which completes the HOSM controller. Furthermore, the HOSM approach can easily satisfy the position tracking requirements of the LAMOST mount drive system.

A generalised time-varying output feedback controller for non-linear systems

This paper presents a solution for the design of a time-varying and parametric output feedback controller for known general non-linear dynamic systems subjected to linear output structure. The controller consists of two parts: an adaptive observer and a time-varying controller. Under a certain assumption on the non-linear dynamics of the system, a stable and non-linear adaptive observer can be firstly built. This observer can then be logically combined with any pre-specified smooth non-linear controller that uses the estimated state feedback with a tuning parameter. A combined parameter dependent Lyapunov function is constructed and used to formulate an effective tuning rule for the time-varying parameters involved in both the observer and the controller. With this selection of the tuning rule, it has been shown that the closed loop system is stable and the output can be controlled to converge to zero. An example is included to illustrate the use of the proposed methods and encouraging results have been obtained.

Sliding‐mode control for speed sensorless induction machine drive using an adaptive nonlinear rotor flux observer

PurposeTo propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer scheme in this paper provides the simultaneous estimation of the rotor speed, rotor resistance and stator resistance.Design/methodology/approachThe IM rotor speed and rotor flux controllers are designed based on combination of input‐output feedback linearizing, linear optimal feedback control and sliding‐mode (SM) control methods. In addition a novel adaptive rotor flux observer is designed based on Lyapunov theory. The proposed control method is tested by simulation and experimental results.FindingsThe composite rotor speed and rotor flux observer in combination with adaptive rotor flux scheme guarantees a perfect speed, torque and flux tracking control for the IM sensorless drive.Research limitations/implicationsThe proposed control method has a drawback in the IM low speed operating region. Additional research may be able to solve this problem as well as should analyze the sensitivity of the IM drive system performance with respect to variation of the system controller and adaptive flux observer gains. In addition, this research should also analyze the influence of sampling rate, truncation errors, measurement noise, simplifying model assumption and magnetic saturation.Practical implicationsThe proposed control method can be used for adaptive and robust control of the IM drive where an optimal efficiency is desired subject to the variable load torque demand.Originality/valueBased on Lyapunov theory, a novel adaptive rotor flux observer is introduced in which the rotor speed, rotor resistance and stator resistance are treated as the unknown constant parameters.