Adaptive Singularity-free Controller by Neural Compensation for pH Process in Alkali-terminal Tank of Polyacrylonitrile

For pH process in alkali-terminal tank of polyacrylonitrile, the procedure is developed for design of adaptive singularity-free controller by neural compensation approach. The NN weights are turned on-line with no prior training needed by Lyapunov approach. One novel feature of the presented scheme is that by modifying a special quasi-weighted Lyapunov function, the possible control singularity issue in the design of NN adaptive controller is dealt with effectively.