scholarly journals Robust linear parameter varying induction motor control with polytopic models

2013 ◽  
Vol 10 (2) ◽  
pp. 335-348 ◽  
Author(s):  
Khamari Dalila ◽  
Makouf Abdessalem ◽  
Drid Said ◽  
Larbi Chrifi-Alaoui
Keyword(s):  
Induction Motor ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Flux Observer ◽  
Rotor Resistance ◽  
Rotor Flux ◽  
On Line ◽  
Parameter Varying

This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI) based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV) feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.

scholarly journals Output feedback controller design for polynomial linear parameter varying system via parameter-dependent Lyapunov functions

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769032 ◽  
Author(s):  
Xiaobao Han ◽  
Zhenbao Liu ◽  
Huacong Li ◽  
Xianwei Liu
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Output Feedback Controller ◽  
Parameter Varying ◽  
Parameter Dependent

This article presents a new output feedback controller design method for polynomial linear parameter varying model with bounded parameter variation rate. Based on parameter-dependent Lyapunov function, the polynomial linear parameter varying system controller design is formulated into an optimization problem constrained by parameterized linear matrix inequalities. To solve this problem, first, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameter-dependent Lyapunov function, controller, and object coefficient matrices. Then, the control solving problem was reduced to a normal convex optimization problem with linear matrix inequalities constraint on a newly constructed convex polyhedron. Moreover, a parameter scheduling output feedback controller was achieved on the operating condition, which satisfies robust performance and dynamic performances. Finally, the feasibility and validity of the controller analysis and synthesis method are verified by the numerical simulation.

H∞ Linear parameter varying Induction Motor Flux Observer Synthesis

2021 ◽  
Author(s):  
F. Benmessaoud ◽  
M. Bensmaine ◽  
D. Khamari ◽  
I. Benlaloui ◽  
Boutabba ◽  
...  
Keyword(s):  
Induction Motor ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Flux Observer ◽  
Parameter Varying

State estimation for a class of Linear Parameter-Varying systems with parametric uncertainties

2020 ◽  
Vol 42 (15) ◽  
pp. 3035-3042
Author(s):  
Zhongwei He ◽  
Wei Xie
Keyword(s):  
State Estimation ◽  
Sufficient Conditions ◽  
Estimation Methods ◽  
Linear Matrix ◽  
Parametric Uncertainties ◽  
Observation Error ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Linear Parameter Varying Systems ◽  
Parameter Varying

This paper is concerned with interval state estimation for a class of Linear Parameter-Varying systems with parametric uncertainties. Firstly, sufficient conditions to guarantee both the cooperativity and stability of observation error dynamics are presented in terms of parameterized matrix inequality formulations. Secondly, a novel method for scheduled controller law design is proposed in the framework of interval observer design. Under the assumptions that scheduled parameters have a polytopic structure property, the problems of the existence conditions of observers and scheduled controller design are transformed into finite linear matrix inequalities ones, which can be solved by convex optimization algorithms. The validity of the proposed state estimation methods is illustrated through a simple example.

Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance

2019 ◽  
Vol 42 (6) ◽  
pp. 1083-1096 ◽  
Author(s):  
Mohammad Reza Soltanpour ◽  
Farshad Hasanvand ◽  
Reza Hooshmand
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Input Saturation ◽  
Disturbance Attenuation ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Aerial Vehicle ◽  
Parameter Varying ◽  
Parameter Dependent

In this paper, a gain scheduled [Formula: see text] state-feedback controller has been designed to control the attitude of a linear parameter varying (LPV) model of a quadrotor unmanned aerial vehicle (UAV). The scheduling parameters vector, which consists of some states and the control inputs, must vary in a specified polyhedron so that the affine LPV model would be analyzable; therefore, some pre-assumed constraints on states and input saturation have been taken into account in design process. The stabilization and disturbance attenuation conditions are obtained via elementary manipulations on the notion of [Formula: see text] control design. The resulting parameter dependent linear matrix inequalities are solved through a Robust LMI Parser (Rolmip) – which works jointly with YALMIP (A toolbox for modeling and optimization in MATLAB)– by transforming polynomial parameter dependent matrices into multi-simplex domain, to best deal with nonconvex problems. In the end, simulation results have been presented and compared with existing literature to examine the capability of such method in the presence and absence of wind disturbances.

scholarly journals Sliding Mode Observers Based-Simultaneous Actuator and Sensor Faults Estimation for Linear Parameter Varying Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Ali Ben Brahim ◽  
Slim Dhahri ◽  
Fayçal Ben Hmida ◽  
Anis Sallami
Keyword(s):  
Sliding Mode ◽  
Estimation Error ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Parameter Varying ◽  
System States ◽  
Sliding Mode Observers

This paper proposes a scheme to estimate actuator and sensor faults simultaneously for a class of linear parameter varying system expressed in polytopic structure where its parameters evolve in the hypercube domain. Transformed coordinate system design is adopted to decouple faults in actuators and sensors during the course of the system’s operation coincidentally, and then two polytopic subsystems are constructed. The first subsystem includes the effect of actuator faults but is free from sensor faults and the second one is affected only by sensor faults. The main contribution is to conceive two polytopic sliding mode observers in order to estimate the system states and actuator and sensor faults at the same time. Meanwhile, in linear matrix inequality optimization formalism, sufficient conditions are derived withH∞performances to guarantee the stability of estimation error and to minimize the effect of disturbances. Therefore, all parameters of observers can be designed by solving these conditions. Finally, simulation results are given to illustrate the effectiveness of the proposed simultaneous actuator and sensor faults estimation.

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