Event‐triggered adaptive backstepping tracking control for a class of nonlinear fractional order systems

This article presents a PI-type iterative learning control (ILC) law with initial state learning for a class of 𝛼 (0 < 𝛼 ≤ 1) fractional order two-dimensional (2D) linear systems. First, by using backward difference method, the finite difference approximation of the fractional order derivative is obtained, which leads to globally 2 − 𝛼 order accuracy. Then, a PI-ILC law is constructed at the nodes and the convergence analysis of the iterative scheme is proved. A linear matrix inequality-based sufficient condition is derived to guarantee that the tracking error is asymptotically convergent. The obtained convergence condition is fractional order dependent. Most of the classical ILC conditions for fractional order one-dimensional linear systems fall into the special cases of this article. Finally, the simulation results show the effectiveness of the proposed control method.

“…For the finite difference scheme (11), borrowed from that in References 20-22, the following PI-type ILC law is constructed at the each nodes…”

Section: Convergence Analysis Of the Discrete Scheme With Pi-ilc Lawmentioning

confidence: 99%

Section: Convergence Analysis Of the Discrete Scheme With Pi-ilc Lawmentioning

confidence: 99%

Section: Convergence Analysis Of the Discrete Scheme With Pi-ilc Lawmentioning

confidence: 99%

Section: Convergence Analysis Of the Discrete Scheme With Pi-ilc Lawmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Event‐triggered switching‐dependent adaptive integral sliding mode control for switched systems

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This article focuses on the event-triggered optimized output feedback control problem for nonlinear strict-feedback systems. First, a fuzzy state observer is designed to estimate the unmeasurable states. Then, the fuzzy-based reinforcement learning is performed under critic-actor architecture to realize the optimized control. In addition, a novel event-triggered mechanism is developed for the system states to greatly economize communication resources. By means of the Lyapunov stability theory, it can be proved that all signals of the closed-loop system are bounded, and the Zeno behavior can be successfully avoided. Lastly, an inverted pendulum example is provided to confirm the effectiveness of the derived algorithm.