A Supervisor for Control of Mode-switch Process

Many processes operate only around a limited number of operation points. In order to have adequate control around each operation point, and adaptive controller could be used. When the operation point changes often, a large number of parameters would have to be adapted over and over again. This makes application of conventional adaptive control unattractive, which is more suited for processes with slowly changing parameters. Furthermore, continuous adaptation is not always needed or desired. An extension of adaptive control is presented, in which for each operation point the process behaviour can be stored in a memory, retrieved from it and evaluated. These functions are co-ordinated by a ¿supervisor¿. This concept is referred to as a supervisor for control of mode-switch processes. It leads to an adaptive control structure which quickly adjusts the controller parameters based on retrieval of old information, without the need to fully relearn each time. This approach has been tested on experimental set-ups of a flexible beam and of a flexible two-link robot arm, but it is directly applicable to other processes, for instance, in the (petro) chemical industry

Dual self-tuning parameter-robust minimax output regulation of a first-order process with ellipsoidal uncertainty

The parameters of a first-order process with known disturbance bounds are known to lie in an ellipsoidal region. At each sample, a static output feedback is designed which minimizes the maximum absolute output over the disturbance and parameter ranges. Then from the resulting measurements, the ellipsoid is updated according to a specific criterion. This criterion should be chosen for adequate performance of the resulting selftuning regulator. It is shown that a dual criterion minimizing a weighted sum of ellipsoidal volume and control performance outperforms these separate criteria

Supervisory Control of Mode-switch Processes; Application to a flexible beam

Many processes operate only around a limited number of operation points. In order to have adequate control around each operation point, an adaptive controller could be used. Then, if the operation point changes often, a large number of parameters would have to be adapted over and over again. This prohibits application of conventional adaptive control, which is more suited for processes with slowly changing parameters. Furthermore, continuous adaptation is not always needed or desired. An extension of adaptive control is presented, in which for each operation point the process behaviour can be stored in a memory, retrieved from it and evaluated. These functions are coordinated by a “supervisor”. This concept is referred to as supervisory control. It leads to an adaptive control structure which, after a learning phase, quickly adjusts the controller parameters based on retrieval of old information, without the need to fully releam each time. This approach has been tested on an experimental set-up of a flexible beam, but it is directly applicable to processes in e.g. the (petro)chemical industry as well