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Unknown time-varying input delay compensation for uncertain nonlinear systems

Başlık çevirisi mevcut değil.

  1. Tez No: 403303
  2. Yazar: SERHAT OBUZ
  3. Danışmanlar: Dr. WARREN E. DIXON
  4. Tez Türü: Doktora
  5. Konular: Makine Mühendisliği, Mechanical Engineering
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2016
  8. Dil: İngilizce
  9. Üniversite: University of Florida
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 107

Özet

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Özet (Çeviri)

Time delay commonly exists in engineering applications such as master-slave robots, haptic systems, networked systems, chemical systems, and biological systems. The system dynamics, communication over a network, and sensing with associated sensor processing (e.g., image-based feedback) can induce time delays that can result in decreased performance and loss of stability. Time delays in physical systems are often time-varying. For example, the input delay in neuromuscular electrical stimulation (NMES ) applications often changes with muscle fatigue, communication delays in wireless networks change based on the operating environment and distance between the communicating agents, etc. NMES is a technique that activates muscle artificially by using electrical impulses to induce a contraction. NMES is a prescribed treatment for various neuromuscular disorders (e.g., providing restored motor function in spinal cord injured individuals, relearning skills after a stroke, and increasing muscle mass). However, feedback control of NMES is difficult since muscles exhibit a delayed response to electrical stimulation. Furthermore, the exact value of the input delay is time-varying. Specifically, muscle groups rapidly fatigue in response to artificial muscle stimulation compared to volitional contractions. Muscle fatigue, in turn, can cause the delay to increase during NMES. Therefore, input delay presents a significant challenge to designing controllers that yield controlled limb movement, especially since the delay is unmeasurable during limb movement. Motivated by such practical engineering challenges, this dissertation focuses on designing controllers to compensate for time delay disturbances for uncertain nonlinear systems. Chapter 1 motivates current challenges in the field of input delayed systems. It also provides an overview of pioneering and state of the art control strategies for systems with input delays and discusses the contributions of this dissertation. Chapter 2 details the development of a novel tracking controller for a class of uncertain nonlinear systems subject to unknown time-varying input delay and additive disturbances that provide uniformly ultimate boundedness of the tracking error signals. The techniques used in Chapter 2 are extended in Chapter 3 to investigate compensating for the effects of input delay without delay rate constraints for uncertain Euler-Lagrange systems with unknown time-varying input delay. The techniques in Chapters 2 and 3, compensate for the effects of unknown time-varying input delay by using a constant estimate of the input delay. These techniques are extended in Chapter 4 by using an adaptive based control strategy to estimate an uncertain state-dependent input delay and compensate the effects of input delay despite an uncertain nonlinear system with an unknown time-varying additive disturbances. In Chapter 5, a position tracking control problem is considered for an uncertain time-varying delayed muscle response by using the technique used in Chapter 3 and adding an integral feedback of the error signal to increase tracking performance and robustness of the controller with respect to uncertainties in lower limb dynamics and time-varying input delay. A robust controller is designed in Chapter 6 to ensure reaction torque tracking in isometric NMES for the uncertain, nonlinear dynamics of the lower limb with additive disturbances without knowledge of time-varying input delay. Chapter 7 discusses the main contributions of each chapter, limitations and implementation challenges, and possible future research directions.

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