Full-order Luenberger Observer Research Articles

Intelligent Adaptation Mechanism of Full-Order Luenberger Observer based on Fuzzy Logic Applied to Direct Control by Flux Orientation without Speed Sensor for Doubly Fed Induction Motor

The present work focused on the control by flow orientation without mechanical sensors on the doubly fed induction motor by the use of artificial intelligence techniques. Our main contribution lies in the development of control methodologies to improve control by flux orientation, for this, we acted on the type and control of inverters by the use of multilevel inverters and then on the observation technique of rotor speed based on the high gain Luenberger observer and improvements to the speed adaptation mechanism using fuzzy logic. Simulation tests of the proposed improvement approach were carried out at the end of this work to verify the behavior of this system in the face of different types of training.

Robust consensus of uncertain multi agent systems with one‐sided Lipschitz nonlinearity

AbstractThis article develops protocols for the consensus of an uncertain nonlinear multi‐agent system that satisfies the one‐sided Lipschitz and quadratic‐inner bounded conditions. Fully distributed consensus protocols with observer‐based and observer‐less schemes are investigated. For the observer‐based system, a full order Luenberger observer is designed. To overcome the difficulties of designing the controller and observer‐based controller gains, sufficient conditions are provided with a complete linear matrix inequality characterization. Finally, two simulation examples are provided to illustrate the effectiveness of the proposed approach.

Design of Robust Adaptive Observer against Measurement Noise for Sensorless Vector Control of Induction Motor Drives

Position control in electrical drives is a challenging problem which is complicated by sensor noise and unknown disturbances. This paper proposes a new cascade sensorless speed control technique for induction motor drives suitable for electric vehicle applications using the full-order adaptive Luenberger observer that is insensitive to measurement noise and parametric variation. The adaptive speed law is obtained by the Lyapunov method using the estimated currents and fluxes. This technique ensures the stability of the induction motor considered as nonlinear dynamic system. Since the Luenberger observer works on deterministic environment, and it is most effective when sensor noise is limited, the present study aims to design a robust observer insensitive to measurement noise and parametric variation integrated in a cascade structure. The observer allows the filtering of the measured currents. To highlight the advantages of the new scheme, a comparative study and spectrum analysis will be presented. The proposed structure is verified using MATLAB/Simulink.

A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

Induction motors are more attractive to car manufacturers because they are more robust and more cost effective to maintain in comparison with other types of electric machines. The evolution of their control makes them more efficient and less expensive. However, a new control technique known as sensorless control is being used to simplify the implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensors with an observer. The estimation of these elements is based on the measurement of currents and voltages. The main purpose of the present study is to design a novel robust structure of the sensorless vector control for an urban electric vehicle. The proposed structure aims to improve the accuracy of dynamics at low speeds, eliminate sensitivity to the machine's parameters, and maintain the stability of the system even if the variation reaches high values. The speed estimation is ensured by an enhanced PI adaptation mechanism based on the full order Luenberger observer. The proof of this stability is based on the Lyapunov theorem. Moreover, a GA-based adaptive control is used for self-tuning of the stator resistance. By combining these techniques, we can enhance the efficiency and stability of the whole system.

An SOS Observer-Based Sensorless Control for PMLSM Drive System

Sum-of-squares (SOS) approach is an effective technique for analysis and design of nonlinear systems. Due to the advantage, this study presents an SOS observer-based control approach for sensorless position servo of permanent magnet linear synchronous motor. To apply the SOS approach, a nonlinear polynomial model is firstly established to describe motor dynamics. Based on this model, a full-order Luenberger observer is developed to estimate the system state. The observer gain that ensures the convergence of state estimation is deduced via the stability analysis and solved by using the third-party toolbox SOSTOOLS. Compared with earlier studies, the advantage of the proposed observer is that the exact motor dynamics is used. Therefore, no further hypothesis or adaptive mechanism on the mover speed is required, which is usually utilized to solve the problem of speed variation with the state observation. According to the principle of backstepping control, the controller is systematically designed to guarantee the asymptotic stability of the closed-loop system. Since both the mechanical and electrical dynamics have been considered, the control signal is directly presented as a voltage. This is different from the conventional current control strategy, which applies the proportional–integral controller to produce a voltage command. The experiment results are provided to validate the proposed control scheme. Moreover, a recent work that is based on the sensorless linear quadratic regulator optimal control is adopted as a comparison study.

Full-order observer-based output regulation for linear heterogeneous multi-agent systems under switching topology

This study addressed the output regulation issue of linear heterogeneous multi-agent systems under switching topology. All agents excluding the external system are divided into two groups with measurable agents or unmeasurable agents. The agents’ states in the first group can be available for measurement while the agents’ states in the second group are unmeasurable. For the second group, a full-order Luenberger observer is devised to recover these agents’ states. Moreover, there are some agents that can not receive the information from the exosystem directly, thus, a dynamic compensator is constructed for these agents. Based on the proposed observer and compensator, a hybrid feedback control strategy is put forward to settle the output regulation issue. Furthermore, the information interaction among agents is expressed by the switching topology, and the topology is assumed to be jointly connected. Finally, two numerical examples are given to illustrate the feasibility of the theoretical results. The results show that whether the states are measurable or not, the proposed control strategy can address the output regulation issue of linear heterogeneous MASs under switching topology. Moreover, the comparative experiment indicates that our method obtains superior performance in terms of convergence speed, and is more efficient in dealing with practical problems.

A Nonlinear Observer for Rotor Flux Estimation of Induction Motor Considering the Estimated Magnetization Characteristic

This paper proposes a nonlinear observer for induction machine drives based on space-vector dynamic model of induction machine, expressed in state form, which presents the peculiarity of taking into consideration the magnetic saturation of the iron core. This observer is particularly suitable in order to obtain high accuracy in rotor flux estimation, in both amplitude and phase position, during working conditions characterized by varying flux, among which the most important are those during electrical losses minimization. A Lyapunov-based convergence analysis is proposed in order to suitably compute the numerical observer gain guaranteeing the convergence of the estimation error. The proposed nonlinear observer has been tested by means of simulations and experiments carried out on a suitably developed test setup. Its behavior has been compared with that obtained with a standard full-order Luenberger observer that assumes the linearity of the magnetization characteristic. The paper shows the capability of the proposed nonlinear observer to correctly estimate amplitude and phase of the rotor flux under flux varying conditions. Moreover, the proposed observer exhibits a higher accuracy than that obtained with the standard observer, which does not consider the estimated magnetization characteristic.

Adaptive fault tolerant control for reconfigurable systems

Reconfigurable systems are the safe dynamical systems wherein the health of the control input and/or sensor output variables are continuously monitored and then they are reconfigured, if necessary, in an event of an unexpected fault detected online. This idea is applied, in particular, at the reconfigurable system where the number of control variables is more than the state variables considered to define its motion. In this paper, an adaptive pole placing controller is developed for use in such reconfigurable systems. Adaptive pole placing controller, in theory, is adaptive to take a fault size and retain the closed loop poles it assigns at fixed locations in the open left half plane of the complex plane. As a result, when the controller is not adaptive, it means that the pole perturbations could lead to catastrophes. However, to design adaptive pole placing controller for a reconfigurable system, fault size is required. Hence, the primary objective of the paper is to present a simple procedure that determines the fault size for tuning in the adaptive pole placing controller. Both direct and full-order Luenberger observer based state feedback adaptive pole placing controllers are presented. In situations where the adaptive pole placing controller is not possible, the fault size for which the reconfigurable system with a non-adaptive pole placing controller would transit from a stable to unstable system (referred as fault tolerant margin with respect to the non-adaptive pole placing controller) is also presented. Some of these features of this paper are illustrated by using the reconfigurable aircraft model available in the literature.

Model predictive current control of surface‐mounted permanent magnet synchronous motor with low torque and current ripple

Electromagnetic torque and stator flux of a permanent magnet synchronous motor (PMSM) can be controlled indirectly with model predictive current control (MPCC). In MPCC, a predefined cost function is minimised by selecting and applying appropriate voltage vectors to stator terminals. Since MPCC employs machine model to predict stator currents, it requires accurate knowledge of its parameters. Furthermore, MPCC results in high torque and current ripples at normal sampling rates. In this study, torque and current ripples of a surface-mounted PMSM are effectively reduced by incorporating the concept of duty cycle and applying two voltage vectors, instead of one voltage vector as in conventional MPCC, during a control period. A fuzzy logic modulator is designed and utilised to determine the duty cycles of voltage vectors. Furthermore, sensitivity of the proposed control strategy against parameter variations is alleviated by employing a full-order Luenberger observer. Various case studies are carried out on a hardware-in-the-loop setup and performance of the proposed method is compared with conventional and a recently introduced duty cycle-based predictive control. The obtained results verify the superiority of the proposed MPCC and its effectiveness in reducing the PMSM torque and current ripples with accurate and erroneous knowledge of motor parameters.

Multiple-AVF Cross-Feedback-Network-Based Position Error Harmonic Fluctuation Elimination for Sensorless IPMSM Drives

To diminish the position estimation error with harmonic fluctuations for position sensorless interior permanent-magnet synchronous motor (IPMSM) drives, a multiple adaptive vector filter (AVF) cross-feedback network (CFN) is proposed for a model-based position observer. A full-order Luenberger observer is utilized to obtain back electromotive force (EMF) information. The harmonic fluctuations in the position estimation error caused by inverter nonlinearities and flux spatial harmonics are analyzed. Accordingly, a newly proposed multiple-AVF CFN with an easy-to-implement structure is adopted to detect and compensate the back-EMF harmonic distortions and, hence, to eliminate the position error harmonic fluctuations. Consequently, the position estimation accuracy can be enhanced, which improves the position sensorless control performance. The proposed scheme was verified on a 2.2-kW sensorless IPMSM drive. Experimental results confirm the effectiveness of the method in eliminating the harmonic fluctuations in the position estimation error.

Full-order Luenberger observer based on fuzzy-logic control for sensorless field-oriented control of a single-sided linear induction motor

This paper investigates sensorless indirect field oriented control (IFOC) of SLIM with full-order Luenberger observer. The dynamic equations of SLIM are first elaborated to draw full-order Luenberger observer with some simplifying assumption. The observer gain matrix is derived from conventional procedure so that observer poles are proportional to SLIM poles to ensure the stability of system for wide range of linear speed. The operation of observer is significantly impressed by adaptive scheme. A fuzzy logic control (FLC) is proposed as adaptive scheme to estimate linear speed using speed tuning signal. The parameters of FLC are tuned using an off-line method through chaotic optimization algorithm (COA). The performance of the proposed observer is verified by both numerical simulation and real-time hardware-in-the-loop (HIL) implementation. Moreover, a detailed comparative study among proposed and other speed observers is obtained under different operation conditions.

Closed-Loop MRAS Speed Observer for Linear Induction Motor Drives

This paper presents a closed-loop model reference adaptive system (CL-MRAS) speed observer developed for linear induction motor (LIM) drives. Starting from the structure of the CL-MRAS speed observer developed in the literature for rotating induction motors, a corresponding speed observer for LIMs has been developed here. It is based on the LIM dynamic model taking into consideration its dynamic end effects. In particular, the following aspects are original: 1) It employs the voltage and current models of the LIM considering its dynamic end effects, 2) it proposes a net thrust model including the braking force caused by the dynamic end effects; 3) it models the friction load of the LIM drive experimentally obtained with off-line tests. The proposed sensorless technique has been tested on a purposely developed experimental set-up. Results show that the CL-MRAS observer permits the drive to operate down to the speed of 0.01 m/s, i.e., about 0.15% of the rated speed, which is about 20 times lower than the minimum working speed achieved with other observers implemented on the same LIM drive, such as the total least squares (TLS) MRAS observer, the TLS EXIN full-order Luenberger observer, the extended Kalman filter, and, finally, the TLS EXIN Kalman filter.

Neural Sensorless Control of Linear Induction Motors by a Full-Order Luenberger Observer Considering the End Effects

This paper proposes a neural based full-order Luenberger adaptive speed observer for sensorless linear induction motor (LIM) drives, where the linear speed is estimated with the total least squares (TLS) EXIN neuron. A novel state space-vector representation of the LIM has been deduced, taking into consideration its dynamic end effects. The state equations of the LIM have been rearranged into a matrix form to be solved, in terms of the LIM linear speed, by any least squares technique. The TLS EXIN neuron has been used to compute online, in recursive form, the machine linear speed. A new gain matrix choice of the Luenberger observer, specifically taking into consideration the LIM dynamic end effects, has been proposed, overcoming the limits of the gain matrix choice based on the rotating-induction-machine model. The proposed TLS full-order Luenberger adaptive speed observer has been tested experimentally on an experimental rig. Results have been compared with those achievable with the TLS EXIN MRAS, the classic MRAS, and the sliding-mode MRAS observers.

High-performance sensorless nonlinear power control of a flywheel energy storage system

The flywheel energy storage systems (FESS) can be used to store and release energy in high power pulsed systems. Based on the use of a homopolar synchronous machine in a FESS, a high performance model-based power flow control law is developed using the feedback linearization methodology. This law is based on the voltage space vector reference frame machine model. To reduce the magnetic losses, a pulse amplitude modulation driver for the armature is more adequate. The restrictions in amplitude and phase imposed by the driver are also included. A full order Luenberger observer for the torque angle and rotor speed is developed to implement a sensorless control strategy. Simulation results are presented to illustrate the performance.

Delay-Independent Observer-Based Control for a Class of Neutral Systems

In this paper, the observer-based control for a class of neutral systems is considered. The analysis is based on the use of Lyapunov functional stability theory. Delay-independent stabilization criteria are proposed to guarantee stability for the systems via linear control. The linear matrix inequality (lmi) approach is used to design the observer and the feedback control. Our results are a simple generalization of a full-order Luenberger observer. A numerical example is given to illustrate the use of our main results.

Robust Fault Detection and Isolation in a DC Motor: Comparison of Observer-Based Mehtods

Abstract The aim of this paper is to compare two procedures of robust FDI in a DC motor current control loop : a generalized full-order Luenberger observer method and an unknown input observer (UIO) one. Some experimental results are given using a fine model of the process

Nonlinear State Estimation in the Presence of Multiple Steady States

This paper concerns the problem of state estimation in nonlinear deterministic processes. For moderately nonlinear deterministic processes, the inadequacy of full-order Luenberger observer and extended Luenberger observer with constant gain is shown analytically and through numerical simulation of a chemical reactor. The results indicate that the convergence of an extended Luenberger observer with constant gain may be poorer than that of a simple linear Luenberger observer. A nonlinear observer design method with varying gain is applied to a classical exothermic stirred-tank reactor with multiple steady states. Under significant observer-initialization errors and several observer gains, the global asymptotic convergence of the nonlinear observer is demonstrated through numerical simulations. In the presence of the multiple steady states, the nonlinear observer converges to the same steady-state operating point at which the reactor operates, irrespective of the observer initial conditions.

State-space design of multivariable self-tuning regulators

Abstract A state-space design for a multivariable, self-tuning regulator is presented which is based upon eigenvalue assignment. The parameters of a MIMO stochastic process are estimated at each time interval by recursive least squares, and are used to construct an equivalent state-space representation. Eigenvalue assignment of the closed-loop system is accomplished by state feedback, where the state estimate is obtained from the output of a full-order Luenberger observer. The algorithm can be used to regulate non-minimum phase and open-loop unstable systems. Three examples are given.