scholarly journals A comparative study of nonlinear circle criterion based observer and H∞ observer for induction motor drive

2019 ◽  
Vol 10 (3) ◽  
pp. 1229
Author(s):  
Farid Berrezzek ◽  
Wafa Bourbia ◽  
Bachir Bensaker
Keyword(s):  
Comparative Study ◽  
Induction Motor ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Optimization Approach ◽  
Lmi Optimization ◽  
Circle Criterion ◽  
True State ◽  
The Stability

<span lang="EN-US">This paper deals with a comparative study of circle criterion based nonlinear observer<em> </em>and <em>H<sub>∞</sub></em> observer for induction motor (IM) drive. The  advantage of the circle criterion approach for nonlinear observer design is that it directly handles the nonlinearities of the system with less restriction  conditions in contrast of the other methods which attempt to eliminate them. However the <em>H<sub>∞</sub></em> observer guaranteed the stability taking into account disturbance and noise attenuation. Linear matrix inequality (LMI) optimization approach is used to compute the gains matrices for the two observers. The simulation results show the superiority of <em>H<sub>∞</sub></em> observer in the sense that it can achieve convergence to the true state, despite the nonlinearity of model and the presence of disturbance.</span>

scholarly journals Backstepping Based Nonlinear Sensorless Control of Induction Motor System

2021 ◽  
Vol 54 (3) ◽  
pp. 495-502
Author(s):  
Farid Berrezzek ◽  
Abdelhak Benheniche
Keyword(s):  
Induction Motor ◽  
Control Strategy ◽  
Sensorless Control ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Asymptotic Convergence ◽  
Matrix Inequalities ◽  
Circle Criterion ◽  
The Stability ◽  
Criterion Approach

This work proposes a sensorless control strategy for the induction motor (IM) using a Backstepping control and a nonlinear observer based on the circle-criterion approach. The Backstepping is a powerful control strategy that deals with nonlinear higher-order systems and includes non-measurable parameters related to the (IM). The nonlinear observer approach is intended to determine these important parameters. The circle-criterion approach is employed to determine the observer gain matrices as a solution of LMI (linear matrix inequalities) that guarantee the stability conditions of the designed observer. The main objective of this method is to solve the problem of the nonlinearities of the system which ensure the global asymptotic convergence of the observed dynamics and to improve the performance of the induction motors. The efficiency and correctness of the proposed scheme are proven by several numerical simulations.

Convex Optimization Approach to Observer-Based Stabilization of Uncertain Linear Systems

2005 ◽  
Vol 128 (4) ◽  
pp. 989-994 ◽  
Author(s):  
Salim Ibrir
Keyword(s):  
Linear Systems ◽  
State Feedback ◽  
Observer Design ◽  
Linear Matrix ◽  
Computational Algorithms ◽  
Optimization Approach ◽  
Matrix Inequality ◽  
Matrix Inequalities ◽  
The Stability ◽  
Uncertain Linear Systems

New sufficient linear matrix inequality conditions guaranteeing the stability of uncertain linear systems by means of dynamic output feedbacks are presented. It is shown that the search of an observer-based controller for this class of systems is fundamentally decomposed into two main problems: robust stability with a memoryless state feedback and observer design with measured uncertainties. Under the fulfilment of the developed linear matrix inequalities conditions, we show that the observer-based problem is solvable without any need for some equality constraints or iterative computational algorithms. Examples showing the potential of the results are presented.

scholarly journals Suboptimal Disturbance Observer Design Using All Stabilizing Q Filter for Precise Tracking Control

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1434 ◽  
Author(s):  
Wonhee Kim ◽  
Sangmin Suh
Keyword(s):  
Design Method ◽  
Industrial Applications ◽  
Point Of View ◽  
Observer Design ◽  
Linear Matrix ◽  
External Disturbances ◽  
Closed Loop Systems ◽  
Control Target ◽  
The Stability ◽  
Unified Index

For several decades, disturbance observers (DOs) have been widely utilized to enhance tracking performance by reducing external disturbances in different industrial applications. However, although a DO is a verified control structure, a conventional DO does not guarantee stability. This paper proposes a stability-guaranteed design method, while maintaining the DO structure. The proposed design method uses a linear matrix inequality (LMI)-based H∞ control because the LMI-based control guarantees the stability of closed loop systems. However, applying the DO design to the LMI framework is not trivial because there are two control targets, whereas the standard LMI stabilizes a single control target. In this study, the problem is first resolved by building a single fictitious model because the two models are serial and can be considered as a single model from the Q-filter point of view. Using the proposed design framework, all-stabilizing Q filters are calculated. In addition, for the stability and robustness of the DO, two metrics are proposed to quantify the stability and robustness and combined into a single unified index to satisfy both metrics. Based on an application example, it is verified that the proposed method is effective, with a performance improvement of 10.8%.

Nonlinear observer based sliding mode control and oxygen fraction estimation for diesel engine

2017 ◽  
Vol 40 (7) ◽  
pp. 2227-2239 ◽  
Author(s):  
Haoping Wang ◽  
Qiankun Qu ◽  
Yang Tian
Keyword(s):  
Diesel Engine ◽  
Sliding Mode Control ◽  
Oxygen Concentration ◽  
Control Method ◽  
Sliding Mode ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Model Based ◽  
Mode Control

In this paper, a nonlinear observer based sliding mode control (NOSMC) approach for air-path and a model-based observer for oxygen concentration in the diesel engine equipped with a variable geometry turbocharger and exhaust gas recirculation is introduced. We propose a less conservative observer design technique for Lipschitz nonlinear systems using Ricatti equations. The observer gains are obtained by solving the linear matrix inequality (LMI). Then a robust nonlinear control method, sliding mode control is applied for the states of intake and exhaust manifold pressure and compressor mass flow rate for the sake of the minimization of emissions. The proposed NOSMC controller is applied on a mean value model of turbocharged diesel engine. Besides this, a model-based observer is developed to estimate the oxygen concentration in the intake and exhaust manifolds owing to its significance in reducing emissions of diesel engines. The validation and efficiency of the proposed method are demonstrated by AMESim and Matlab/Simulink co-simulation results.

scholarly journals Experimental Study of Sensor Fault-Tolerant Control for an Electro-Hydraulic Actuator Based on a Robust Nonlinear Observer

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4337 ◽  
Author(s):  
Tan Van Nguyen ◽  
Cheolkeun Ha
Keyword(s):  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Hydraulic Actuator ◽  
Discrete Time System ◽  
Lmi Optimization ◽  
Fault Compensation ◽  
The Difference

Electro-hydraulic actuators (EHAs) have been widely used in modern industries. However, sensor faults and actuator faults in EHA systems can arise due to aging during operation, making the system unstable and unsafe. To solve these issues, fault-tolerant control (FTC) techniques for EHA systems have been studied intensively. In this paper, an FTC is proposed and developed for the mini motion package (MMP) EHA system. First, a mathematical model of the MMP system is formulated and improved to provide position tracking control using a well-known proportional-integral-derivative (PID) controller. Second, an unknown input observer (UIO) reconstruction is performed to estimate the states, disturbances, and sensor faults so that an asymptotically stable control error can be obtained by a linear matrix inequality (LMI) optimization algorithm through Lyapunov’s stability condition. Third, the FTC designed for the nonlinear discrete-time system is formed from fault compensation based on a residual logic signal to implement the fault compensation process and ensure stability and tracking performance with respect to minimizing impacts of disturbances and sensor faults. Here, residual is defined by the difference between state response and state estimation. Finally, numerical simulations and experiments of the MMP system are presented to illustrate the efficiency of the proposed FTC technique.

Fuzzy Control for Nonlinear Uncertain T-S Fuzzy Systems with Time-Varying Delays

2013 ◽  
Vol 341-342 ◽  
pp. 668-673
Author(s):  
Yi Min Li ◽  
Yuan Yuan Li
Keyword(s):  
Stability Analysis ◽  
Discrete Time ◽  
Fuzzy Model ◽  
Optimization Techniques ◽  
Linear Matrix ◽  
Time Varying ◽  
Parameter Uncertainties ◽  
Lmi Optimization ◽  
System A ◽  
The Stability

This paper studies the stability analysis of discrete time-varying system with parameter uncertainties and disturbances. The system under consideration is subject to time-varying non-bounded parameter uncertainties in both the state and measured output matrices. To facilitate the stability analysis, the T-S fuzzy model is employed to represent the discrete-time nonlinear system. A fuzzy observer is used to guarantee the Lyapunov stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. The control and observer matrices can be obtained by directly solving a set of linear matrix inequality (LMI) via the existing LMI optimization techniques. Finally, an example is provided to demonstrate the effectiveness of the proposed approach.

Dynamic Positioning Observer Design Using Exogenous Kalman Filter

2019 ◽  
Author(s):  
Song An ◽  
Dengshuo Chen ◽  
Yong Bai
Keyword(s):  
Kalman Filter ◽  
Stability Property ◽  
Measurement Data ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Dynamic Positioning ◽  
Model Uncertainties ◽  
Process Noise ◽  
Second Stage ◽  
The Stability

Abstract Observer of a dynamic positioning (DP) system utilizes DP’s measurement data, to predict vessel’s velocities, positions, and unknown environmental forces on the vessel, as well as to handle model uncertainties and errors. Stability and optimality of a DP observer is important for overall DP performance. Nonlinear observer (NLO) designs usually take global asymptotic or exponential stability as the primary goal, and discard the noise. On the other hand, linearized Kalman filter (KF) algorithm, e.g. the extended Kalman filter (EKF), is optimal in minimizing the covariance of observer states by taking both measurement and process noise into account. The applied exogenous Kalman filter (XKF) algorithm in this paper, is a two-stage cascade of NLO and linearized KF, which uses the first-stage NLO estimated states as exogenous inputs for the second-stage linearized KF. XKF approach is proved to have both the stability property inherited from NLO and optimality from linearized KF. Stability and optimality of XKF based observer is studied through DP station-keeping numerical simulations.

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