Abstract
The paper presents the design of a new reduced-order multiple observer for the estimation of the state associated with Takagi-Sugeno systems with unknown inputs, this being only the second reduced-order multiple observer ever designed. The design of reduced-order multiple observers which can achieve the finite-time state reconstruction for nonlinear systems described by multiple models is a niche area problem; the author of this paper continuing his work started with the introduction of the reduced-order multiple observer concept. The new multiple observer is a combination of a typical reduced-order observer for linear-time invariant multivariable systems and a full-order multiple observer for Takagi-Sugeno systems. The sufficient stability conditions of the observer are derived via the Lyapunov theory and its robustness is improved by means of a novel and efficient method which cancels the negative effect of the uncertainties appearing in the system. To validate the suggested design algorithm, the steps of the design procedure have been summarized and software implemented for the concrete case of a light aircraft lateral-directional motion.
Highlights
In many real-world applications, there are difficulties in obtaining the measurement of the state variables describing the functioning of a system; sometimes, this is even impossible because of the physical constraints and/or economical restrictions; the usage of observers instead of sensors is a solution largely adopted in order to avoid these problems
The design of reduced-order multiple observers which can achieve the finite-time state reconstruction for nonlinear systems described by multiple models is a niche area problem; the author of this paper continuing his work started with the introduction of the reducedorder multiple observer concept
In [14], the authors focus on the state estimation of a nonlinear system described by a Takagi-Sugeno (T-S) multiple model having unknown inputs and outputs; the proposed approach consists of a mathematical transformation which enables
Summary
In many real-world applications, there are difficulties in obtaining the measurement of the state variables describing the functioning of a system; sometimes, this is even impossible because of the physical constraints and/or economical restrictions; the usage of observers instead of sensors is a solution largely adopted in order to avoid these problems. The estimation of the states and unknown inputs (noises, measurement uncertainties, faults of sensors or actuators, etc.) for a physical system is needed in order to conceive a control strategy able to minimize the negative effects of the disturbances [4, 5]. In [14], the authors focus on the state estimation of a nonlinear system described by a Takagi-Sugeno (T-S) multiple model having unknown inputs and outputs; the proposed approach consists of a mathematical transformation which enables
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