Delayed feedback control requires an internal forward model

Biological motor control provides highly effective solutions to difficult control problems in spite of the complexity of the plant and the significant delays in sensory feedback. Such delays are expected to lead to non trivial stability issues and lack of robustness of control solutions. However, such difficulties are not observed in biological systems under normal operating conditions. Based on early suggestions in the control literature, a possible solution to this conundrum has been the suggestion that the motor system contains within itself a forward model of the plant (e.g., the arm), which allows the system to ‘simulate’ and predict the effect of applying a control signal. In this work, we formally define the notion of a forward model for deterministic control problems, and provide simple conditions that imply its existence for tasks involving delayed feedback control. As opposed to previous work which dealt mostly with linear plants and quadratic cost functions, our results apply to rather generic control systems, showing that any controller (biological or otherwise) which solves a set of tasks, must contain within itself a forward plant model. We suggest that our results provide strong theoretical support for the necessity of forward models in many delayed control problems, implying that they are not only useful, but rather, mandatory, under general conditions.

[1]  David L. Kleinman,et al.  Optimal control of linear systems with time-delay and observation noise , 1969 .

[2]  D. Bushaw,et al.  Functional analysis and time optimal control , 1972 .

[3]  Mitsuo Kawato,et al.  Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.

[4]  Eduardo D. Sontag,et al.  Adaptation and regulation with signal detection implies internal model , 2003, Syst. Control. Lett..

[5]  Amir Karniel,et al.  Three creatures named 'forward model' , 2002, Neural Networks.

[6]  Eitan Altman,et al.  Closed-loop control with delayed information , 1992, SIGMETRICS '92/PERFORMANCE '92.

[7]  Emanuel Todorov,et al.  Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System , 2005, Neural Computation.

[8]  W. Wonham,et al.  The internal model principle for linear multivariable regulators , 1975 .

[9]  S. Scott Optimal feedback control and the neural basis of volitional motor control , 2004, Nature Reviews Neuroscience.

[10]  D. Wolpert,et al.  Is the cerebellum a smith predictor? , 1993, Journal of motor behavior.

[11]  Yaakov Bar-Shalom Update with out-of-sequence measurements in tracking: exact solution , 2002 .

[12]  Dimitri P. Bertsekas,et al.  Convex Analysis and Optimization , 2003 .

[13]  Reza Shadmehr,et al.  Motor Adaptation as a Process of Reoptimization , 2008, The Journal of Neuroscience.

[14]  A. Fuller Optimal nonlinear control of systems with pure delay , 1968 .

[15]  Zoubin Ghahramani,et al.  Perspectives and problems in motor learning , 2001, Trends in Cognitive Sciences.

[16]  Stelios C.A. Thomopoulos Decentralized Filtering and Control in the Presence of Delays: Discrete-Time and Continuous-Time Case , 1994, Inf. Sci..

[17]  P. R. Davidson,et al.  Widespread access to predictive models in the motor system: a short review , 2005, Journal of neural engineering.

[18]  Rieko Osu,et al.  CNS Learns Stable, Accurate, and Efficient Movements Using a Simple Algorithm , 2008, The Journal of Neuroscience.

[19]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[20]  Mark L Latash,et al.  Motor synergies and the equilibrium-point hypothesis. , 2010, Motor control.

[21]  J. Krakauer,et al.  A computational neuroanatomy for motor control , 2008, Experimental Brain Research.

[22]  Pablo A. Iglesias,et al.  An approximate internal model principle: Applications to nonlinear models of biological systems , 2008 .

[23]  Maarten F Bobbert,et al.  Is equilibrium point control feasible for fast goal-directed single-joint movements? , 2006, Journal of neurophysiology.

[24]  Oliver Mason,et al.  The rôle of control and system theory in systems biology , 2008, Annu. Rev. Control..

[25]  Masami Ito,et al.  A process-model control for linear systems with delay , 1981 .

[26]  Leonid Mirkin,et al.  Every stabilizing dead-time controller has an observer-predictor-based structure , 2003, Autom..

[27]  Silviu-Iulian Niculescu,et al.  Survey on Recent Results in the Stability and Control of Time-Delay Systems* , 2003 .