Adaptive control of non-linear continuous-time systems using neural networks—general relative degree and MIMO cases

摘要: Multilayer neural networks are used in a non-linear adaptive control problem. The plant is an unknown feedback linearizable continuous-time system with relative degree 1. single-input:/single-output studied first and then the methodology extended to square multi-input/multi-output systems. objective for track reference trajectory, law defined terms of outputs networks. parameters updated on-line according augmented tracking error network derivatives. A local convergence theorem given on error. This algorithm applied two-input/two-output relative-degree-two system.