All publications by Gawthrop in 2008

A piezoelectric tube is shown to have linear, but non-minimum phase dynamics. The main impediment to the actuation of this piezoelectric tube is the presence of a low-frequency resonant mode which causes mechanical vibrations. A physical-model-based control method is extended to non-minimum phase systems in general and successfully applied to damp the resonant mode; leading to a vibration-free actuation of the piezoelectric tube.

Fitts' law is a well established empirical formula, known for encapsulating the “speed-accuracy trade-off”. For discrete, manual movements from a starting location to a target, Fitts' law relates movement duration to the distance moved and target size. The widespread empirical success of the formula is suggestive of underlying principles of human movement control. There have been previous attempts to relate Fitts' law to engineering-type control hypotheses and it has been shown that the law is exactly consistent with the closed-loop step-response of a time-delayed, first-order system. Assuming only the operation of closed-loop feedback, either continuous or intermittent, this paper asks whether such feedback should be predictive or not predictive to be consistent with Fitts law. Since Fitts' law is equivalent to a time delay separated from a first-order system, known control theory implies that the controller must be predictive. A predictive controller moves the time-delay outside the feedback loop such that the closed- loop response can be separated into a time delay and rational function whereas a non- predictive controller retains a state delay within feedback loop which is not consistent with Fitts' law. Using sufficient parameters, a high-order non-predictive controller could approximately reproduce Fitts' law. However, such high-order, “non-parametric” controllers are essentially empirical in nature, without physical meaning, and therefore are conceptually inferior to the predictive controller. It is a new insight that using closed-loop feedback, prediction is required to physically explain Fitts' law. The implication is that prediction is an inherent part of the “speed-accuracy trade-off”.

Causality, in the bond graph sense, is shown to provide a conceptual framework for the design of real-time dynamic substructure testing experiments. In particular, known stability problems with split-inertia substructured systems are reinterpreted as causality issues within the new conceptual framework. As an example, causality analysis is used to provide a practical solution to a split-inertia substructuring problem and the solution is experimentally verified.

There are a number of competing scientific hypotheses about the structure and parameters of the human control system concerned with balance. System identification techniques have potential to distinguish between such competing hypotheses. As a step towards this goal, the data from an initial series of experiments involving balancing an inverted pendulum by a human via a joystick was analysed using a recently-developed two-stage continuous-time identification method.

This paper proposes a continuous-time model predictive control design for disturbance rejection and set-point following of periodic signals. By assuming input disturbance in the form of sinusoid, the periodic frequency is embedded into the design model. Hence, from internal model principle, the steady-state error of the model predictive control system is ensured to be zero for both disturbance rejection and set-point following. Furthermore, with the design framework of model predictive control, hard constraints on the derivative and amplitude of the control signals are imposed as part of the performance specification. Simulation studies have been used to show the efficacy of the design with or without hard constraints.