Disturbance Observer-Based Predictive Functional Critical Control of a Table Drive System
This paper addresses a control system design for a table drive system based on the disturbance observer (DOB)-based predictive functional critical control (PFCC). To empower the previously developed DOB-based PFC to handle constraints on controlled outputs, we propose to take a critical control approach. To this end, we derive the transfer function representation of the PFC controller and yield a detailed design procedure. The effectiveness of the proposed method is confirmed through an experimental evaluation.
Improving Tracking Performance of Predictive Functional Control Using Disturbance Observer and Its Application to Table Drive Systems
A practical approach for improving tracking performance of the predictive functional control (PFC) is proposed. The disturbance observer is utilized to nominalize the actual plant and to reduce the predicted output error in the PFC algorithm by canceling not only constant but also high-order disturbances. The proposed control scheme is experimentally validated on a single axis table drive system and is compared with the standard PFC and the industrial cascade control. The experimental results prove the effectiveness of the proposed disturbance observer-based PFC scheme.
Proportional-integral-plus (PIP) control of the ALSTOM gasifier problem
Abstract Although it is able to exploit the full power of optimal state variable feedback within a non-minimum state-space (NMSS) setting, the proportional-integral-plus (PIP) controller is simple to implement and provides a logical extension of conventional proportional-integral and proportional-integral-derivative (PI/PID) controllers, with additional dynamic feedback and input compensators introduced automatically by the NMSS formulation of the problem when the process is of greater than first order or has appreciable pure time delays. The present paper applies the PIP methodology to the ALSTOM benchmark challenge, which takes the form of a highly coupled multi-variable linear model, representing the gasifier system of an integrated gasification combined cycle (IGCC) power plant. In particular, a straightforwardly tuned discrete-time PIP control system based on a reduced-order backward-shift model of the gasifier is found to yield good control of the benchmark, meeting most of the specified performance requirements at three different operating points.