To address non-linearity, strong coupling and multi-variables existing in general electric-drive system, a simulating system of intelligent control of electric-drives has been designed, in which PID control, Fuzzy control, and neural control schemes are integrated.
Finally, the proposed metamodeling technique and sampling schemes are integrated and applied to optimize sheet forming design; the corresponding optimized results demonstrate that the proposed hybrid metamodeling technique is able to produce good approximation model of sheet metal forming system.
Finally, those schemes are integrated into AdmireRPS system.
Finally, these schemes are integrated into the practical system, that is, AdmireRPS, an RPS of a heterogeneous wireless network- HWN-) orienetwork- HWN-nference system.
Indeed, it will be important that such pilot schemes are integrated into, rather than compete with, other programmes in sexual health, drug, smoking and alcohol consumption reduction etc.
Finally, the scheme is integrated on a hexapod robot and tested by real experiments.
The neuro-fuzzy computing scheme is integrated with operator's posture analysis and evaluation.
Then, the iterative learning control (ILC) scheme is integrated with the high-gain tracker design for the decentralized models.
The robust FDI scheme is integrated with a robust stability-based controller reconfiguration strategy that preserves closed-loop stability following FDI.
This scheme is integrated into the proposed nonlinear controller in order to achieve the angle tracking on a desired reference function.
