Journal papers by Gawthrop in 1999

A new class of nonlinear PID controllers are derived for nonlinear systems using a nonlinear generalised predictive control (NGPC) approach. First, the disturbance decoupling ability of the NGPC is discussed. For a nonlinear system where the disturbance cannot be decoupled, a nonlinear observer is designed to estimate the offset. By selecting the nonlinear gain function in the observer, it is shown that the closed-loop system under optimal generalised predictive control with the nonlinear observer is asymptotically stable. It is pointed out that this composite controller is equivalent to a nonlinear controller with integral action. As a special case, for a nonlinear system with a low relative degree, the proposed nonlinear controller reduces to a nonlinear PI or PID predictive controller, which consists of a nonlinear PI or PID controller and a prediction controller. The design method is illustrated by an example nonlinear mechanical system

Pseudo and true Bond Graphs have been seen as competing approaches to modelling thermodynamic systems. This paper provides a simple mechanism for mixing the two approaches to obtain the best features of each. In so doing, an alternative and more accessible approach to thermodynamic modelling than that provided by classical texts is given.

Analysis and simulation of non-linear inverse systems are sometimes necessary in the design of control systems particularly when trying to determine an input control required to achieve some predefined output specifications. But unlike physical systems which are proper, the inverse systems are very often improper leading to numerical problems in simulation as their models sometimes have a high index when written in the form of differential-algebraic equations (DAE). This paper provides an alternative approach whereby performance specifications and the physical system are combined within a single bond graph leading to a greatly simplified simulation problem.

A conceptual, and practical difficulty with the continuous-time generalised predictive controller is solved by replacing the continuously moving horizon by an intermittently moving horizon. This allows slow optimisation to occur concurrently with a fast control action. Some nonlinear simulations illustrate the potential of this approach.

An `incremental polynomial model-controller network' (IPMCN) is introduced. Smooth control switching is obtained from the use of odd polynomial controllers. The decomposition of the operating space, together with the construction of the network, is achieved on-line while controlling the system. The performance and robustness of this scheme are illustrated through various simulations.