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Abstract:

In all levels of society, a lot of effort is put in the optimal use of resources as e.g.energy, labor and time. Resource optimization is also important in the control ofmechatronic systems. For these applications, typically either the required time orthe energy consumption to perform an action is minimized. This thesis developscontrollers which aim to minimize the time required to perform a point-to-pointmotion, i.e. the settling time of the system. These controllers are developedwithin the model predictive control framework (mpc). In this framework, thesystem input is determined by solving on-line, during every sampling period, anoptimization problem. This on-line optimization allows to take systems constraintslike actuator saturation, directly into account. The time-optimal controllers havebeen developed for mechatronic systems with sampling periods in the order ofmilliseconds. Hence, the fast solution of these problems is an important designparameter. The main contributions of this research are as follows. First, theminimization of settling time has been formulated as an optimization problemwithin the mpc framework. Then, the structure of these optimization problems hasbeen analyzed and exploited such that these problems can now be formulated withenough variables to be applicable for relevant mechatronic applications while stillbeing solvable within a few milliseconds. All developed time-optimal controllershave been validated experimentally on representative mechatronic systems as linearmotors and an overhead crane. This experimental validation shows that with thedeveloped controllers sampling periods of a few milliseconds are attainable and thatthe settling time can be reduced considerably in comparison with linear controllersand traditional mpc controllers.Within this global framework of minimizing settling time, three controllers havebeen designed. First, a time-optimal feedforward controller has been developed.This controllers generates a reference trajectory which minimizes the settling timefor point-to-point motions. This feedforward controller has been developed as amore performant alternative to linear prefilters. Then, a time-optimal feedbackcontroller has been developed. The introduction of feedback allows to rejectdisturbances and to remove steady state errors. Last, a control scheme whichcombines the time-optimal controllers with linear feedback controllers, has beenproposed. This scheme allows to fulfill the benchmark requirements of an industriallinear motor, i.e. not only a small settling time but also an absolute settlingaccuracy in the submicrometer range.