Reduced-order Luenberger Observer Research Articles

Load Torque Observer for BLDC Motors Based on a HOSM Differentiator

An observer is proposed for a trapezoidal brushless DC motor composed of a cascade connection of a reduced-order Luenberger observer and a high-order sliding mode (HOSM) differentiator. This configuration can estimate the angular velocity and reconstruct the load torque, key elements for the control of this type of motor, under the mild assumption that the variable load torque and its k-th time derivatives are bounded. The proposed observer was tested on an experimental test bench based on Texas Instruments (TI) High Voltage Digital Motor Control (HVMTR Kit) using a Delfino F28379D micro controller. The results show that the velocity and load torque can be properly estimated, despite the presence of noise in the current measurements.

Full prediction cascade control of permanent magnet toroidal motor with time-varying parameters

This paper presents the modeling and predictive control of permanent magnet toroidal motor (PMTM). Based on the spatial structure characteristics and working principle of toroidal motor, the time-varying inductance parameters are derived. The nonlinear mathematical model of toroidal motor is established in rotating coordinate system. The output fluctuation of the toroidal motor is analyzed. To improve the output performance of toroidal motor, the full predictive cascade speed and current control (F-MPC) strategy for toroidal motor is proposed. For F-MPC of toroidal motor, the finite control set model predictive current control (FCS-MPCC) strategy with delay compensation is adopted in current inner loop, and the deadbeat model predictive speed control (DB-MPSC) strategy is adopted in speed outer loop. Meanwhile, to achieve DB-MPSC, the reduced-order Luenberger observer is designed to obtain load torque in real time. F-MPC is the combination of current-speed prediction and Luenberger observer; it can overcome the limitation of excessive parameter adjustment of traditional cascade PI (Proportional Integral) controller. The simulation results show that compared with FOC (Field Oriented Control) and FCS-MPCC, F-MPC can improve the dynamic response and anti-interference performance of toroidal motor, and it can also reduce the fluctuation of output speed and torque significantly.

Linear Robust Discharge Control for Flywheel Energy Storage System With RLC Filter

High speed becomes an important development direction of flywheel energy storage system (FESS) for higher energy storage density. However, the high speed leads to a wide-range and rapid speed variation (tens of thousands of revolutions in seconds) and a limited frequency modulation index, both of which aggravate the current harmonics and deteriorate the robustness of the discharge control, and even lead to instability. To address this issue, this article proposes a robust and practical discharge control strategy for high-speed FESS with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RLC</i> filter, which realizes speed adaptation and harmonic suppression. In this scheme, the linear extended state observer and two-degree-of-freedom internal model control (TDOF-IMC) are applied to FESS in the framework of linear active disturbance rejection control (LADRC). Besides, considering that high-speed FESS usually require sensorless control due to magnetic bearings, a reduced-order Luenberger observer for the investigated FESS is proposed. The salient feature of this strategy is to introduce the TDOF-IMC containing FESS dynamic information into LADRC, so that the discharge control is both practical and robust. Experiments and simulations verify the effectiveness of the control strategy.

Research on Grey Predictive Control of PMSM Based on Reduced-order Luenberger Observer

Research on Grey Predictive Control of PMSM Based on Reduced-order Luenberger Observer

A controller comprising tail wing control of a hybrid autonomous underwater vehicle for use as an underwater glider

A controller for an underwater glider is presented. Considered underwater glider is a torpedo-shaped autonomous underwater vehicle installing adjustable buoyancy bag and movable battery in it. The controller is composed of an LQR controller to maintain zigzag vertical movement for gliding and two PD controllers to control elevator/rudder angles. The LQR controller controls the pumping speed into the buoyancy bag and the moving speed to locate the battery. One of the PD controller controls the elevator angle to assist the LQR controller, and the other controls the rudder angle to adjust the direction of the underwater glider. A reduced order Luenberger observer is adopted to estimates the center of gravity of the glider and the buoyancy mass that are essential but cannot be measured. Mathematical simulation using Matlab proved the validity of the proposed controller to obtain better performance than conventional LQR only controller under the influence of sea current.

Online Identification Methods of Load Rotary Inertia and Torque in Radar Servo System

In radar servo system, the load is usually subject to movement and gust, which may cause instability of the system. In this paper, the online identification methods of load rotary inertia and torque in radar servo system are proposed, respectively. The radar servo system is based on synchronous motor. The load rotary inertia of the system is identified online by a disturbance observer. Moreover, a reduced order Luenberger observer is designed to observe the variation of the load torque and velocity online. The simulation models are established to verify the proposed disturbance observer for the load rotary inertia and the reduced order Luenberger observer for the load torque and velocity.

Design and Implementation of Robust Hybrid Control of Vision Based Underactuated Mechanical Nonminimum Phase Systems

This paper presents a vision based Cart-Inverted Pendulum (CIP) system under a hybrid feedback configuration: the continuous cart’s position measured by encoder and the delayed & sampled inverted pendulum’s upper coordinates, obtained from a visual sensor. The challenge here is to stabilize the CIP from a big inclined initial angle by using a low cost CCD camera. Under this scheme, we propose a hybrid control which consists in a Jumpingup (Bang-Bang) control and a two causal stabilization loops control: the first one (inner loop) realizes a linearization and the stabilization control of the pendulum based on an innovative Piecewise Continuous Reduced Order Luenberger Observer coupled with a linearization module, the second one (the outer loop) realizes a Lyapunov based control for the unstable internal system with lower dynamics than that of the pendulum. This hybrid control method is capable of balancing the CIP system within small cart’s displacement. Performances issues of the proposed method are illustrated by the experimental figures and videos.

Commande d'un pendule inversé 3D par asservissement visuel

This paper presents a stabilization control system of a 3D inverted pendulum. The challenge is to realize a control via remote sensing based on a low cost CCD camera. The proposed method transforms the 3D problem into a 2D one by choosing a new balacing plane for the pendulum at each camera's sampling instant. For a given plane, two feedback loops are considered. The first one, which is an observation loop, processes the delayed and sampled angle information delivered by the artificial vision system so as to set up a linear and stable model of the pendulum (without any approximations) and to reconstitue its continuous state by means of a specific observer called Plecewise Continuous reduced-order Luenberger Observer (PCO). The second loop, which is a stabilitation loop , makes use of a Lyapunov function based control in order to stabilise the cart-pendulum system. Simulations and experimental results illustrate the method's performance.

Two-level methods for incipient fault diagnosis in nonlinear chemical processes

Various two-level methods are formulated by using different forms of extended Kalman filter, recursive least squares and a reduced-order Luenberger observer for fault detection and diagnosis in nonlinear, time-varying and stochastic chemical processes. These methods are specified for state estimation in the first level and fault diagnosis via parameter identification in the second level. The performances of the proposed methods are evaluated by applying them to a nonlinear CSTR with a heat exchanger and a nonlinear batch beer fermentation with closed-loop control. Dynamic simulation results demonstrate that these two-level methods can be applied for process fault detection and diagnosis to transient time domain systems with closed-loop control in addition to the steady-state systems of normal operation. Among these methods, the two-level extended Kalman filter has exhibited better performance. Therefore, the method of the two-level extended Kalman filter is recommended for incipient fault diagnosis.

On observing the states of uncertain dynamical systems

For the implementation of a stable asymptotic reduced-order Luenberger observer, which is not sensitive to unknown disturbances entering the system, it is shown that specific columns of the measurement matrixC must be different from zero.

Decentralized Load-Frequency Control of Interconnected Energy Systems

The paper deals with the design of an optimal decentralized load-frequency controller for interconnected energy systems. It is assumed that the entire system state vector is not measurable and a decentralized observer based on a reduced order Luenberger observer is synthesized to estimate the unmeasurable states. For the system augmented by the observer, a decentralized output feedback control is applied using an algorithm for parameter optimization with constrained controller structure. The results obtained from a digital simulation of a two-area electric energy system are presented and briefly discussed.

On designing reduced-order observers for linear time-invariant systems subject to unknown inputs

Abstract Using the simplest matrix generalized inverse, the {l}-inverse, a procedure is developed for the construction of a reduced-order Luenberger observer for a linear time-invariant system subjected to immeasurable input disturbances. Illustrative examples are included.

Observers for linear systems with unknown inputs

This paper presents a constructive solution to the problem of designing a reduced-order Luenberger observer for linear systems subject to arbitrary unknown inputs.

Sensitivity and error analysis algorithms for combined estimation and control systems

Sew algorithms for sensitivity and error analysis of combined estimation and control systems are presented. The control structure is constrained a priori to be a fixed configuration type in which the closed-loop control is generated by the summation of a gain matrix multiplying the measured states and another gain matrix multiplying an estimate of the unmeasured states. The estimator is constrained a priori to be a reduced-order Luenberger observer. An augmented state vector is formed consisting of the original system states plus the estimation errors for each of the states not measured. This vector is used in deriving a mean square closed-loop system propagation matrix equation which is a function of the feedback gains, observer dynamics, system modelling errors, and a priori state statistics. The standard quadratic form performance index is reformulated using trace notation in terms of the closed-loop mean square matrix. The performance index is then reduced to a simple expression by forcing a matrix Ri...