Abstract
This paper describes emergent neurobiological characteristics of an intelligent multiple-controller that has been developed for controlling the throttle, brake and steering subsystems of a validated vehicle model. Simulation results demonstrate the effectiveness of the proposed approach. Importantly, the controller exhibits discrete behaviours, governed by its two component controllers. These controllers are selected according to task demands by a fuzzy-logic based supervisor. The system therefore displays ‘action selection’ under central switched control, as has been proposed to take place in the vertebrate brain. In addition, the supervisor and modular controllers have analogues with the higher and lower levels of functionality associated with the strata in layered brain architectures. Several further similarities are identified between the biology and the vehicle controller. We conclude that advances in neuroscience and control theory have reached a critical mass which make it timely for a new rapprochement of these disciplines.
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References
Conatser, R., Wagner, J., Ganta, S., Walker, I.: Diagnosis of automotive electronic throttle control systems. Control Engineering Practice 12, 23–30 (2004)
Lee, C.Y.: Adaptive control of a class of nonlinear systems using multiple parameter models. Int. J. Contr. Autom. Sys. 4(4), 428–437 (2006)
Prescott, T.J., Bryson, J.J., Seth, A.K.: Introduction to the theme issue on modelling natural action selection. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 362, 1521–1529 (2007)
Gurney, K.N., Prescott, T.J., Redgrave, P.: A computational model of action selection in the basal ganglia i: A new functional anatomy. Biol. Cybern. 84, 401–410 (2001)
Abdullah, R., Hussain, A., Warwick, K., Zayed, A.: Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic based switching and tuning. Neurocomputing (in press)
Abdullah, R., Hussain, A., Polycarpou, M.: Fuzzy logic based switching and tuning supervisor for a multivariable multiple-controller. In: IEEE International conference on Fuzzy Systems, Imperial College, London, UK, pp. 1644–1649 (2007)
Zayed, A., Hussain, A., Abdullah, R.: A novel multiple-controller incorporating a radial basis function neural network based generalized learning model. Neurocomputing 69(16-18), 1868–1881 (2006)
Naranjo, J., Gonzalez, C., Reviejo, J., Garcia, R., Pedro, T.: Adaptive fuzzy control for inter-vehicle gap keeping. IEEE Trans. Intellig. Transport. Syst. 4(3), 132–142 (2003)
Hespanha, J., Liberzon, D., Morse, A., Anderson, B., Brinsmead, T., Bruyne, D.: Multiple model adaptive control. part 2: Switching. Int. J. Robust Nonlin. Contr. 11, 479–496 (2001)
Kiencke, U., Nielsen, L.: Automotive Control Systems: For Engine, Driveline, and Vehicle. Springer, Berlin (2005)
Redgrave, P., Prescott, T.J., Gurney, K.N.: The basal ganglia: a vertebrate solution to the selection problem? Neuroscience 89, 1009–1023 (1999)
Gurney, K.N., Prescott, T.J., Redgrave, P.: A computational model of action selection in the basal ganglia ii: Analysis and simulation of behaviour. Biol. Cybern. 84, 411–423 (2001)
Humphries, M.D., Stewart, R.D., Gurney, K.N.: A physiologically plausible model of action selection and oscillatory activity in the basal ganglia. J. Neurosci. 26, 31–61 (2006)
Prescott, T.J., Gonzales, F., Gurney, K.N., Humphries, M.D., Redgrave, P.: A robot model of the basal ganglia: behavior and intrinsic processing. Neur. Networks 19, 31–61 (2005)
Prescott, T.J., Redgrave, P., Gurney, K.N.: Layered control architectures in robots and vertebrates. Adapt. Behav. 7, 99–127 (1999)
Brooks, R.A.: New approaches to robotics. Science 253, 1227–1232 (1998)
Carter, C.S., Braver, T.S., Barch, D.M., Botvinick, M.M., Noll, D., Cohen, J.D.: Anterior cingulate cortex, error detection, and the online monitoring of performance. Science 280, 747–749 (1998)
Redgrave, P., Gurney, K.N.: The short-latency dopamine signal: a role in discovering novel actions? Nat. Rev. Neurosci. 7, 967–975 (2006)
Gurney, K.N., Chambers, J., Redgrave, P.: A model of reinforcement learning in basal ganglia for action-outcome association. In: IBAGS IX Meeting, Egmond aan Zee, The Netherlands (2007)
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Hussain, A., Gurney, K., Abdullah, R., Chambers, J. (2008). Emergent Common Functional Principles in Control Theory and the Vertebrate Brain: A Case Study with Autonomous Vehicle Control. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_98
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DOI: https://doi.org/10.1007/978-3-540-87559-8_98
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