Decentralized tracking control for linear uncertain interconnected systems with time delays

In this paper, an improved decentralized control method is proposed to design a bank-to-turn (BTT) missile autopilot. Compared to the general diagonal blocked Lyapunov function method, the improved decentralized control method by considering the coupling terms as the structured uncertainty can provide a simpler design, tolerate more types of uncertainties and yield a better dynamic performance. Moreover, this method can be extended to multimodel systems expediently. Due to the structural constraints, the decentralized controller may not realize the tracking control target under some conditions, and this paper also provides such a condition. The decentralized controller design is formulated in terms of linear matrix inequality (LMI) optimization, and the simulation results demonstrate the effectiveness of the proposed method.

Section: The Decentralized Control For Lti Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An improved decentralized control method for Bank‐to‐Turn missile autopilot design

Qin

Duan

2011

“…The reason for recent awareness of nonlinear models is that they describe most physical systems and increase the accuracy and performance of system behavior. During recent decades, various types of adaptive controllers have been developed and applied, more particularly for smaller systems [35][36][37][38][39] and large-scale linear systems [2,5,[32][33][34], based on different approaches, such as, minimum variance [37,39], generalized minimum variance [2,38], decentralization [12], and so on.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control Scheme for Large‐Scale Interconnected Systems Described by Hammerstein Models

Elloumi

Kamoun

2017

This paper proposes an adaptive algorithm for the online control of discrete‐time large‐scale nonlinear systems, which reduces the noise effects acting on the system output (regulation problem) and allows the system output to keep track of a time‐varying trajectory (tracking problem). We consider a large‐scale nonlinear system that can be decomposed into single‐input single‐output (SISO) interconnected nonlinear subsystems with known structure variables (orders, delays) and unknown time‐varying parameters. Each interconnected subsystem is described by block‐oriented models, specifically a discrete‐time Hammerstein model. Parameter adaptation is performed using a recursive parametric estimation algorithm based on the adjustable model method and the least squares techniques. Simulation results of an interconnected petroleum process are provided to demonstrate the effectiveness of the developed control scheme.

“…A considerable amount of research effort has been devoted to the analysis and design of robust or H ∞ controllers for neutral delay systems 4–31. In general, the existing H ∞ control methods proposed for neutral delay systems can be featured as delay‐independent 4, 5, 8 or delay‐dependent 5–7, 9–11, 13, 15–17, 24–26, 30–32.…”

Section: Introductionmentioning

confidence: 99%

An improved delay‐dependent bounded real lemma (BRL) and H_∞ controller synthesis for linear neutral systems

Parlakci

2010

In this paper, a novel delay-dependent bounded real criterion and an improved sufficient condition are derived for the design of an H ∞ statefeedback controller for linear neutral time-delay systems. On the basis of an augmented Lyapunov-Krasovskii functional, a new bounded real lemma is introduced in terms of a convex linear matrix inequality (LMI) condition that can be solved using interior point algorithms. The bounded real lemma is extended to obtain a sufficient condition for the existence of a delay-dependent H ∞ memoryless state-feedback controller. Neither any model transformation nor bounding of any of the cross terms are utilized while deriving the bounded real lemma. Moreover, the use of any free slack matrix variable approach is avoided to a certain extent in order not to increase the complexity of the synthesis problem. A cone complementary nonlinear minimization algorithm is employed to achieve a feasible solution set for the synthesis conditions. Finally, seven numerical examples are given to illustrate the effectiveness of the proposed method.