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Observer-based adaptive control using multiple-models switching and tuning

机译:使用多模型切换和调整的基于观察者的自适应控制

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Despite the remarkable theoretical accomplishments and successful applications of adaptive control, this field is not mature enough to solve challenging problems where strict performance and robustness guarantees are required. The needs of an approach that explicitly accounts for robust performance and stability specifications is a critical to the design of practical adaptive control systems. Towards this goal, this study extends the robust adaptive controller using multiple models, switching and tuning to multiple input multiple output and non-linear systems. The use of 'extended superstability', instead of superstability, allows us to establish overall performance guarantees and reduce the conservativeness of the resulting closed-loop system. The authors show that under the proposed framework, the output and states remain bounded for bounded disturbances, as a direct consequence of the passivation properties of superstability. The effectiveness of the proposed algorithm is demonstrated in numerical simulations of a non-linear continuous stirred tank reactor.
机译:尽管自适应控制取得了卓越的理论成就和成功的应用,但该领域还不够成熟,无法解决需要严格的性能和鲁棒性保证的挑战性问题。明确考虑鲁棒性能和稳定性指标的方法的需求对于实际的自适应控制系统的设计至关重要。为了实现这一目标,本研究使用多种模型扩展了鲁棒的自适应控制器,将其切换和调整为多输入多输出和非线性系统。使用“扩展的超稳定性”而不是“超稳定性”,使我们能够建立总体性能保证并减少最终闭环系统的保守性。作者表明,在所提出的框架下,输出和状态对于有限的扰动仍然是有界的,这是超稳定性的钝化特性的直接结果。非线性连续搅拌釜反应器的数值模拟证明了该算法的有效性。

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