A robust fuzzy control is developed for robot manipulators to guarantee both global stability and Performance. Robot dynamics under consideration may include large nonlinear uncertainties, such as nonlinear load variations and unmodelled dynamics. Fuzzy sets are chosen based on performance requirements and stability regions of the control system. For each fuzzy set, a sub-control is designed, based on nonlinear robust control design using Lyapunov's direct method; this is blended with others into a final fuzzy control. The resulting control provides not only robust and global stability, but also more accurate control performance than fuzzy controls obtained from constant sub-controls. The proposed design is applied to a robot trajectory control problem and compared with a standard nonlinear robust controller. The simulation results show that the proposed control is effective and yields superior tracking performance.
A new collaborative design scheme of a super-high-speed permanent-magnet synchronous motor (PMSM) and its digital controller is presented, which provides a low-cost but highly efficient motor system with guaranteed stability and performance. Since the systematic design of the PMSM can ensure its stability over the full operating speed range, a simple and reliable open-loop controller can be designed for the super-high-speed motor. With stability assurance, an optimal digital control is also designed in order to enhance the efficiency and performance of the PMSM. The unique feature in the proposed optimal V/f control is its design consideration to the stator resistor, which is generally neglected in most V/f controls but cannot be neglected in the super-high-speed motor owing to the extra small-size requirement. The simulation and stability analysis for various design options are provided. Finally, simulation and experimental results validate the design technique and its effectiveness.
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