Abstract

In this paper, we establish an event-triggered intelligent control scheme with a single critic network, to cope with the optimal stabilization problem of nonlinear aeroelastic systems. The main contribution lies in the design of a novel triggering condition with input constraints, avoiding the Lipschitz assumption on the inverse hyperbolic tangent function. Based on an improved weight updating criterion that eliminates the requirement of initial admissible control, the control law is obtained approximately by online training of a single critic network. The Lyapunov stability and the Zeno phenomenon of the closed-loop system are analysed. The feasibility of the established algorithm is verified by applying it to an optimal stabilization task of a nonlinear aeroelastic system. The results reveal that the developed approach can handle input-constrained optimal control problems, with performance comparable to the time-based method that updates control inputs at each instant, while reducing the computational and communication's load.

Highlights

  • Aeroelastic systems exhibit a variety of unstable phenomena, such as flutter and limit-cycle oscillations (LCOs), which can significantly degrade the flight performance of an aircraft [1,2,3]

  • Motivated by the demands for tackling these challenges, this paper aims at developing a constrained-input optimal control approach with reduced computational and communication’s cost for nonlinear aeroelastic systems

  • This paper develops a general control method that can be applied directly without making coordinate transformations

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Summary

Introduction

Aeroelastic systems exhibit a variety of unstable phenomena, such as flutter and limit-cycle oscillations (LCOs), which can significantly degrade the flight performance of an aircraft [1,2,3]. Motivated by the demands for tackling these challenges, this paper aims at developing a constrained-input optimal control approach with reduced computational and communication’s cost for nonlinear aeroelastic systems. For CT systems adopting ETC methods, the inter-execution time can be zero, resulting in the accumulation of event times This is the infamous Zeno phenomenon that must be avoided in the controller design. The initial admissible control is a requirement for both time-based and event-triggered ADP methods, which weakens their application, especially for closed-loop online learning control. The remainder of this paper is organized as follows: Section 2 states the constrained-input optimal control problem for a CT nonlinear aeroelastic system under the event-triggered framework. The symbol ∇(·) ∂(·)/∂ x stands for the gradient operator

Aeroelastic wing section model
Optimal control design with input constraints
Event-triggered scheme design
Intelligent critic control implementation
Improved neural control implementation
Closed-loop stability analysis
Analysis of Zeno phenomenon in the closed-loop system
Simulation study
Findings
Conclusion
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