Adaptive nonlinear control with constrained parallel parameter estimates

The state feedback regulation of nonlinear systems of order 'n' in parametric strict-feedback form is considered. A simple, easy to tune, adaptive control with projected parameter estimates is proposed. The uncertain parameter vector is estimated by parallel vector estimates whose differences are constrained to tend asymptotically to zero. When the uncertain parameter vector is identifiable, the closed loop system is globally asymptotically and locally exponentially stable. Three comparative examples illustrate the advantages of the proposed simple adaptive control over the tuning functions or extended matching approaches.