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.

scholarly journals H∞Gain-Scheduled Control for LPV Stochastic Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Guan-Wei Chen
Keyword(s):  
Stochastic Systems ◽  
Weighting Function ◽  
Design Method ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Mean Square ◽  
Gain Scheduled Controller ◽  
The Stability ◽  
Uncertain Stochastic System ◽  
Gain Scheduled

A robust control problem for discrete-time uncertain stochastic systems is discussed via gain-scheduled control scheme subject toH∞attenuation performance. Applying Linear Parameter Varying (LPV) modeling approach and stochastic difference equation, the uncertain stochastic systems can be described by combining time-varying weighting function and linear systems with multiplicative noise terms. Due to the consideration of stochastic behavior, the stability in the sense of mean square is applied for the system. Furthermore, two kinds of Lyapunov functions are employed to derive their corresponding sufficient conditions to solve the stabilization problems of this paper. In order to use convex optimization algorithm, the derived conditions are converted into Linear Matrix Inequality (LMI) form. Via solving those conditions, the gain-scheduled controller can be established such that the robust asymptotical stability andH∞performance of the disturbed uncertain stochastic system can be achieved in the sense of mean square. Finally, two numerical examples are applied to demonstrate the effectiveness and applicability of the proposed design method.

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.

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.

Delay-Dependent Robust Control for Discrete-Time Uncertain Stochastic Systems With Time-Varying Delays

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Guan-Wei Chen
Keyword(s):  
Robust Control ◽  
Discrete Time ◽  
Stochastic Systems ◽  
Design Method ◽  
Sufficient Conditions ◽  
Jensen Inequality ◽  
Linear Matrix ◽  
Time Varying ◽  
Gain Scheduled Controller ◽  
Delay Dependent

This paper investigates a delay-dependent robust control problem of discrete-time uncertain stochastic systems with delays. The uncertainty considered in this paper is time-varying but norm-bounded, and the delays are considered as interval time-varying case for both state and input. According to the considerations of uncertainty, stochastic behavior, and time delays, the problem considered in this paper is more general than the existing works for uncertain stochastic systems. Via the proposed Lyapunov–Krasovskii function, some sufficient conditions are derived into the extended linear matrix inequality form. Moreover, Jensen inequality and free matrix equation are employed to reduce conservatism of those conditions. Through using the proposed design method, a gain-scheduled controller is designed to guarantee asymptotical stability of uncertain stochastic systems in the sense of mean square. Finally, two numerical examples are provided to demonstrate applicability and effectiveness of the proposed design method.

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.

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.

A fault-detection, filter-design method for linear parameter-varying systems

2007 ◽  
Vol 221 (6) ◽  
pp. 865-874 ◽  
Author(s):  
A Casavola ◽  
D Famularo ◽  
G Franzè ◽  
M Sorbara
Keyword(s):  
Fault Detection ◽  
Filter Design ◽  
Design Method ◽  
Linear Matrix ◽  
False Alarms ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Luenberger Observer ◽  
Parameter Varying ◽  
Filter Design Method

In this paper a fault-detection (FD), filter-design method has been proposed for linear parameter-varying (LPV) systems. The FD filter is an optimal H∞ Luenberger observer synthesized by minimizing frequency conditions that ensure guaranteed levels of disturbance rejection and fault detection. Via the bounded real lemma (BRL) and the separation principle the design method is formulated as a convex linear matrix inequality (LMI) optimization problem. The resulting residual generator is parameter-dependent and uses the plant parameter assumed measurable online. Finally, an FD threshold logic is proposed in order to reduce the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example.

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