Stability analysis of a new non-linear pole-zero placement controller incorporating neural networks

The stability analysis and parameter convergence of a newly reported self-tuning pole-zero placement controller algorithm for non-linear dynamic systems are studied. The original controller overcomes the shortcomings of other linear designs and provides an adaptive mechanism, which ensures that both the closed-loop poles and zeros are placed at their prespecified positions. The closed loop system stability and the parameter convergence are derived by assuming that the reference signal is bounded and the process non-linearity is globally bounded.