Intermittent predictive control of man and machine

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For fifty years, the servo mechanism, a simple, reactive, continuous feedback system, has been used as a model of human neural control systems. The PID servo is the most well known example which uses positional and velocity feedback to stabilise the variable of importance. It has always been known that the nervous system is more sophisticated than this. We are all aware that we anticipate: sometimes the error in our expectations catches us out, such as when we use too much force to lift a suitcase that is lighter than we expected. There has been increasing acceptance that the nervous system predicts our world and predicts how neural signals will be converted into bodily movement. As a model of motor control, the servo paradigm has been increasingly replaced by the optimal control or continuous predictive control paradigm which is founded on the engineering control methodology of internal models, prediction and optimisation. While it is more sophisticated and richer in its expression, the continuous predictive control paradigm is still inconsistent with several aspects of biological behaviour. Biological control is inherently variable. For humans, the temporal response to stimuli is inconsistent, the reformulating of immediate goals is highly flexible, and the bandwidth, i.e. frequency limit, of meaningful control is rather low. These neural features are not natural outcomes of the continuous control paradigm derived from engineering insight, which has been designed precisely to negate these limitations of human control and produce control which is temporally consistent, with high bandwidth, highly specified function and hence minimal goal flexibility. This proposal's power derives from a new type of engineering control methodology known as Intermittent predictive control . Intermittent predictive control provides a spectrum of possibilities between the two extremes of continuous-time and discrete-time control: the control signal consists of a sequence of (continuous-time) parameterised trajectories whose parameters are adjusted intermittently. It is different from discrete-time control in that the control is not constant between samples; it is different from continuous-time control in that the trajectories are reset intermittently. As a class of control theory, intermittent predictive control is more general than continuous control and provides a new paradigm incorporating continuous predictive and optimal control with intermittent, open loop (ballistic) control. This new intermittent predictive control paradigm has important technological applications. Consequently there is a need to develop the concept, theory and system identification of these controllers. This new paradigm is also intuitively similar to human physiological control systems in that low bandwidth, flexible, variable control is a natural product of the mechanism. We intend to discover whether human postural mechanisms are best explained by a continuous PID type of controller or an intermittent control process. The powerful corrective responses that occur when posture is perturbed can be explained on the basis of high bandwidth continuous feedback. However, we question whether such mechanisms dominate in the exquisitely fine control of unperturbed, skilled and learned postural activities such as standing. If the intermittent predictive control paradigm is applicable, then natural postural balance is correctly reinterpreted as centrally modulated, voluntary control like any other form of movement. Clarification of this issue will have important implications for diverse healthcare topics including the rehabilitation of spinally injured patients who are no longer able to stand and the diagnosis of risk factors in elderly patients with a history of falling.We aim to incorporate our biological insights into the design of engineering controllers that mimic the real-time flexibility of the human nervous system.