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Thus, controller design for redundant robot system is difficult job for controller designer.
Orthogonal eigenstructure control can minimizes the trial and error by the controller designer.
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The multiobjective optimization strategy called physical programming provides controller designers with a flexible tool to express design preferences with a 'physical' meaning.
Hence, it is important to derive a good approximate sampled-data model because the exact sampled-data model for nonlinear systems is often unavailable to the controller designers.
The simplified model is described by physically meaningful state variables, which enables controller designers to effectively consider practical objectives and constraints.
The paper deals with the development of a new robust PID controller design method that guarantees designer-specified maximum overshoot and settling time for non-minimum phase processes with unstable zero.
The chaotic NSGAII algorithm, which is an incorporation of chaotic behaviors into NSGAII, is used as the optimizer to search true Pareto-front of the FOPID controller and designers can implement each of them based on objective functions priority.
This paper presents the design of a robust Pareto-optimal controller with the designer preference articulation for a Permanent Magnet Synchronous Motor (PMSM).
Movement is still achieved by using a traditional controller, although other designers have experimented with creating treadmill-like add-ons for the device.
In this paper an overall MOOD procedure focusing in controller tuning applications using designer's preferences is proposed.
The designer chooses the controller order and may introduce constant time-delays in the controller.
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