Adaptive fuzzy control of MIMO nonlinear systems
Fuzzy Sets and Systems
A mixed fuzzy controller for MIMO systems
Fuzzy Sets and Systems
Artificial Intelligence: A Guide to Intelligent Systems
Artificial Intelligence: A Guide to Intelligent Systems
Covariance matrix adaptation evolution strategy based design of centralized PID controller
Expert Systems with Applications: An International Journal
Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
A simple and effective immune particle swarm optimization algorithm
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
High dimensional problem based on elite-grouped adaptive particle swarm optimization
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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A nonlinear, multiple input-multiple output controller called the quality controller of neuro-traveling particle swarm optimizer (QC/NTPSO) approach has been proposed in this paper. A reliable controller must stabilize the quality during the manufacturing process and bring the quality characteristics of the manufacturing process close to the target. This controller must also have an adequate feedback system with estimation technology and optimization algorithm. In addition, the artificial intelligence has reasonably been matured and is often used in dealing with construction problems. Therefore, this work constructed a controller with artificial intelligence technology by first using an artificial neural network as the predictor and then using the traveling particle swarm optimizer that is ideal for continuous optimization problems as the algorithm for optimization. The proposed approach has been tested through chemical mechanical polishing (CMP), an important process in semiconductor manufacturing. The result of the test shows that the proposed approach can bring quality characteristics closer to the target than any other approaches.