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.

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.

scholarly journals Robust Filtering for Discrete-Time Linear Parameter-Varying Descriptor Systems

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1871 ◽  
Author(s):  
Carlos Rodriguez ◽  
Karina A. Barbosa ◽  
Daniel Coutinho
Keyword(s):  
Discrete Time ◽  
Filter Design ◽  
Linear Time ◽  
Estimation Error ◽  
Sufficient Conditions ◽  
Descriptor Systems ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Parameter Varying ◽  
Time Linear

This paper deals with robust state estimation for discrete-time, linear parameter varying (LPV) descriptor systems. It is assumed that all the system state-space matrices are affine functions of the uncertain parameters and both the parameters and their variations are bounded functions of time with known minimum and maximum values. First, necessary and sufficient conditions are proposed for admissibility and bounded realness for discrete linear time-varying (DLTV) descriptor systems. Next, two convex optimisation based methods are proposed for designing admissible stationary linear descriptor filters for LPV descriptor systems which ensure a prescribed upper bound on the ℓ2-induced gain from the noise signal to the estimation error regardless of model uncertainties. The proposed filter design results were based on parameter-dependent generalised Lyapunov functions, and full-order, augmented-order and reduced-order filters were considered. Numerical examples are presented to show the effectiveness of the proposed filtering scheme. In particular, the proposed approach was used to estimate the state variables of a controlled horizontal 2-DOF robotic manipulator based on noisy measurements.

Distributed sliding mode leader-following consensus controller for uncertain time-delay linear parameter-varying multiagent systems

2020 ◽  
pp. 107754632095652
Author(s):  
Mohammad Amin Moradi ◽  
Behrouz Safarinejadian ◽  
Mohammad Hossein Shafiei
Keyword(s):  
Time Delay ◽  
Multiagent Systems ◽  
Sliding Mode ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Leader Following ◽  
Parameter Varying ◽  
Uncertain Time ◽  
Delay Dependent

This study addresses the consensus problem of leader-following multiagent systems, whose dynamics are governed by time-delay linear parameter-varying models with norm-bounded uncertainties. At first, a delay-dependent sufficient condition concerned with the existence of a parameter-varying sliding surface is given in terms of linear matrix inequalities. Then, a robust consensus among the leader and followers is achieved via the distributed linear parameter-varying sliding mode control protocol. Conditions for closed-loop stability are also presented in the form of some theorems. Simulation results demonstrate the effectiveness of the proposed approach.

Control of LPV systems subject to state constraints and input saturation

2018 ◽  
Vol 40 (14) ◽  
pp. 3985-3993 ◽  
Author(s):  
Yanmei Hu ◽  
Guangren Duan ◽  
Feng Tan
Keyword(s):  
Linear Matrix Inequalities ◽  
Input Saturation ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Linear Parameter ◽  
Parameter Uncertainties ◽  
Linear Parameter Varying ◽  
Linear Parameter Varying Systems ◽  
Parameter Varying

This paper deals with the stabilization of state-constrained linear parameter-varying systems subject to parameter uncertainties and input saturation. Based on a class of parameter-dependent Lyapunov functions, and the set invariance, sufficient conditions for the stabilization problem of the linear parameter-varying systems are established in terms of parameterized linear matrix inequalities. Further, these conditions are converted into linear matrix inequalities by using a parameter relaxation technique. Finally, detailed simulation results are presented to illustrate the effectiveness of the proposed methodology.

scholarly journals Finite-time non-fragile controller design for a class of switching linear parameter varying systems based on linear matrix inequalities

2018 ◽  
Vol 233 (1) ◽  
pp. 58-66 ◽  
Author(s):  
Chengcheng Ren ◽  
Longfang Li ◽  
Shuping He
Keyword(s):  
Linear Matrix Inequalities ◽  
Finite Time ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Parameter Varying ◽  
Linear Parameter Varying System

The finite-time non-fragile controller design problem is studied for a class of switching linear parameter varying system in this article. We aim to design a suitable finite-time non-fragile controller such that the closed-loop switching linear parameter varying system is finite-time bounded. Based on the linear matrix inequalities and multiple Lyapunov functions methods, sufficient conditions on the existence of the finite-time non-fragile controller are proposed and proved. Considering the parameters dependence, we change the infinite linear matrix inequalities into finite linear matrix inequalities by using approximate basis functions and gridding techniques. Finally, a simulation example is given to illustrate the effectiveness of the design methods.

Gain-Scheduled H∞ Control for Linear Parameter Varying Stochastic Systems

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Cheng-I Wu
Keyword(s):  
Stochastic Systems ◽  
Controller Design ◽  
Design Method ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Parameter Varying ◽  
Gain Scheduled Controller ◽  
Gain Scheduled

In this paper, a gain-scheduled controller design method is proposed for linear parameter varying (LPV) stochastic systems subject to H∞ performance constraint. Applying the stochastic differential equation, the stochastic behaviors of system are described via multiplicative noise terms. Employing the gain-scheduled design technique, the stabilization problem of LPV stochastic systems is discussed. Besides, the H∞ attenuation performance is employed to constrain the effect of external disturbance. Based on the Lyapunov function and Itô's formula, the sufficient conditions are derived to propose the stability criteria for LPV stochastic systems. The derived sufficient conditions are converted into linear matrix inequality (LMI) problems that can be solved by using convex optimization algorithm. Through solving these conditions, the gain-scheduled controller can be obtained to guarantee asymptotical stability and H∞ performance of LPV stochastic systems. Finally, numerical examples are provided to demonstrate the applications and effectiveness of the proposed controller design method.

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