Abstract:
Biological systems are highly nonlinear, have at least one pair of muscles actuating every degree of freedom at any joint, and possess neural transmission delays in their...Show MoreMetadata
Abstract:
Biological systems are highly nonlinear, have at least one pair of muscles actuating every degree of freedom at any joint, and possess neural transmission delays in their feedforward (efferent) and feedback (afferent) paths. This nonlinear time delay system, involved in movement and continuous interaction with the environment, is precise, stable, and very adaptive. The problem of trajectory tracking control of a three-link sagittal model of the shank, thigh and trunk is considered in this study. The controller is synthesized using the Q-parameterization method of controller design, for the class of stable nonlinear systems. The "free design" parameter is chosen to achieve certain performance and robustness objectives, the standard approach in H/sup /spl infin// control design. Performance of the system to a class of reference inputs and robustness issues pertaining to neglected nonlinearities, unmodeled dynamics and uncertainties in time delays, are addressed in the problem. Simulations are conducted to test the performance and feasibility of the controller for the task of squatting.
Published in: Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
Date of Conference: 10-15 May 1999
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7803-5180-0
Print ISSN: 1050-4729
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1.
V. Anantharam and C. A. Desoer, "On the Stabilisation of Nonlinear System", IEEE Trans. on Automat. Contr, vol. 29, no. 6, pp. 569-572, 1984.
2.
A. Bahill and J. McDonald, "Model Emulates Human Smooth Pursuit System producing Zero Latency Tracking", Biological Cybernetics, vol. 48, pp. 213-222, 1983.
3.
A. G. Barto, J. T. Buckingham and J. C. Houk, "A Predictive Model of Cerebellar Movement Control" in Advances in Neural Information Proteasing Systems, Cambridge:The MIT Press, vol. 8, pp. 136-144, 1996.
4.
J.B. Beers, Neural Control Mechanisms in Coactivated Muscle Pairs, 1991.
5.
R. E. Bellman and K. L. Cooke, Differential-Difference Equation, New York:Academic Press, 1963.
6.
A. Cammuri and V. Sangulneti, "Network Models In Motor Control and Music" in Self-organization Computation Maps and Motor Control, Amsterdam:North-Holland, Elsevier, pp. 311-355, 1997.
7.
A. Z. Ceranowiez, B. F. Wyman and H. Hemami, "Control of Constrained Systems of Controllability Index Two", IEEE Trans. on Automat. Contr., vol. AC-25, no. 6, pp. 1102-1111, Dec 1990.
8.
I. Choi, Controi of a Three Link Robot with transmission Delays, 1996.
9.
B. Dariush, Stability Control and Energetic Studies of a Three Link Neuromuscular Model for Point-to-point Movements, 1993.
10.
J. C. Doyle, K. Glover, P. P. Khargonekar and B. A. Francis, " State-space Solutions to Standard H 2 and H ∞ control problems ", IEEE Trans. Automat. Contr., vol. AC-34, no. 8, pp. 831-847, 1989.
11.
C. Foias, H. Özbay and A. Tannenbaum, Robust Control of Infinite Dimensional Systems: Frequency Domain Methods, London:Springer Verlag, vol. 209, 1996.
12.
H. Hemami, "Execution of Voluntary Bipedal Movement with a Simple Afferent Processor" in Adaptability of Human Gait: Implications for the Control of Locomotion, The Netherlands:Elsevier Science Publishers, B.V., 1991.
13.
H. Hemami and J. A. Dinneen, "A Marionette-based Control Strategy for Stable Movement", IEEE Trans. on Systems Man and Cybernetics, vol. 23, no. 2, pp. 502-511, Mar/Apr 1993.
14.
[14] H.Hemami and H.Özbay, "Modeling and Control of Biological Systems with Multiple Afferent and Efferent Transmission Delays," Submitted for Publication, 1997.
15.
J. C. Houk, "Cooperative Control of Limb Movements by the Motor Cortex Brainstem and Cerebellum" in Models of Brain Function, Cambridge:Cambridge Press, pp. 309-326, 1989.
16.
K. Iqbal, 5tu4iiity and Control in a Planar Neuro-Musculo-Skeletal Model with Latencies, 1992.
17.
F. A. M. Ivaldi, E. Bizzi and V. Sanguineti, "Learning Newtonian Mechanics" in Self-organization Computation Maps and Motor Control, Amsterdam:North-Holland, Elsevier, pp. 191-237, 1997.
18.
[18] A. Kataria, H.Özbay, H.Hemami, "H∞ Controller Design for Musculoskeletal Robotic Systems with Multiple Afferent and Efferent Path Delays, to be submitted for Publication, 1999.
19.
W. M. Lu, "A State-Space Approach to Parameterization of Stabilising Controllers for Nonlinear Systems", IEEE Trans. on Automatic Control, vol. 40, no. 9, pp. 1579-1588, 1995.
20.
D. W. R. C. Miall, D. J. Weir and J. Stein, "Is the cerebellum a Smith Predictor?", J. of Motor Behavior, vol. 25, no. 3, pp. 203-216, 1993.
21.
R. Miall, D. Wolpert and W. Ferrell, "The Cerebellum as a Predictive Model of the Motor System: A Smith Predictor hypothesis" in Neural Control of Movement, Plenum Press, pp. 215-223, 1995.
22.
A. Pellionisz and R. Llinas, "Brain Modeling by tensor Network Theory and Computer Simulation The Cerebellum:Distributed Processor for Predictive Coordination", Neuroscience, vol. 4, pp. 323-348, 1979.
23.
O. J. M. Smith, Feedback Control Systems, New York:McGraw-Hill, 1958.
24.
G. Stepan, "Retarded Dynamical Systems: Stability and Characteristic Functions" in Longman Scientific Technical, New York:Wiley, 1989.
25.
G. Weiss and R. F. Curtain, "Dynamic Stabilisation of regular Linear Systems", IEEE Trans. on Automat. Contr., vol. 42, no. 1, pp. 4-21, Jan 1997.
26.
K. Zhou, J. C. Doyle and K. Glover, Robust and Optimal Control, New York:Prentice Hall, 1996.
