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Smith predictor

About: Smith predictor is a research topic. Over the lifetime, 1927 publications have been published within this topic receiving 31418 citations.


Papers
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Journal ArticleDOI
David Clarke, C. Mohtadi, P S Tuffs1
TL;DR: The relationship between GPC and LQ designs is investigated to show the computational advantage of the new approach and the robustness of the GPC approach to model over- and under-parameterization and to fast sampling rates is demonstrated by a set of simulations.

1,273 citations

01 Jan 1959

1,204 citations

Journal ArticleDOI
TL;DR: This article suggests that the cerebellum forms two types of internal model, a forward predictive model of the motor apparatus and a time delays in the control loop, which delays a copy of the rapid prediction so that it can be compared in temporal register with actual sensory feedback from the movement.
Abstract: The motor system may use internal predictive models of the motor apparatus to achieve better control than would be possible by negative feedback. Several theories have proposed that the cerebellum may form these predictive representations. In this article, we review these theories and try to unify them by reference to an engineering control model known as a Smith Predictor. We suggest that the cerebellum forms two types of internal model. One model is a forward predictive model of the motor apparatus (e.g., limb and muscle), providing a rapid prediction of the sensory consequences of each movement. The second model is of the time delays in the control loop (due to receptor and effector delays, axonal conductances, and cognitive processing delays). This model delays a copy of the rapid prediction so that it can be compared in temporal register with actual sensory feedback from the movement. The result of this comparison is used both to correct for errors in performance and as a training signal to learn the first model. We discuss evidence that the cerebellum could form both of these models and suggest that the cerebellum may hold at least two separate Smith Predictors. One, in the lateral cerebellum, would predict the movement outcome in visual, egocentric, or peripersonal coordinates. Another, in the intermediate cerebellum, would predict the consequences in motor coordinates. Generalization of the Smith Predictor theory is discussed in light of cerebellar involvement in nonmotor control systems, including autonomic functions and cognition.

1,052 citations

Book
21 Feb 2008
TL;DR: In this paper, the authors present a stable analysis of linear time-delay systems with delay sensitivity and interference, and use a direct eigenvalue optimization approach to stabilize the system.
Abstract: Preface List of symbols List of abbreviations Part I. Stability Analysis of Linear Time-Delay Systems: 1. Spectral properties of linear time-delay systems 2. Pseudospectra and robust stability analysis 3. Computation of stability regions in parameter spaces 4. Stability regions in delay-parameter spaces 5. Delays ratio sensitivity and interference 6. Stability of linear periodic systems with delays Part II. Stabilization and Robust Stabilization: 7. The continuous pole placement method 8. Stabilizability with delayed feedback: a numerical case-study 9. The robust stabilization problem 10. Stabilization using a direct eigenvalue optimization approach Part III. Applications: 11. Output feedback stabilization: the single delay case 12. Output feedback stabilization: the multiple delay case 13. Congestion control algorithms in networks 14. Smith predictor for stable systems: delay sensitivity analysis 15. Controlling unstable systems using finite spectrum assignment 16. Consensus problems in traffic flow applications 17. Stability analysis of delay models in biosciences A. Appendices Bibliography Index.

715 citations

Journal ArticleDOI
TL;DR: This work designs controllers using a backstepping method for parabolic PDEs and shows that the proposed method can be used for boundary control of the a Korteweg-de Vries-like third order PDE.

655 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202323
202242
202166
202064
201974
201872