In this work we present a nonlinear adaptive suboptimal control strategy for uncertain nonlinear systems. Stochastic parametric uncertainty is dealt with by employing spectral decomposition of the random variables by means of the generalized polynomial chaos expansion. The projection of uncertainty onto the orthogonal polynomial basis, prescribed by the Wiener-Askey scheme, provides a deterministic model from which the control laws are designed. We apply the nonlinear feedback control law to an automatic pilot system for recovering an aircraft with uncertain aerodynamic data from stall while providing acceptable dynamic response. The control law is obtained by approximating the Hamilton-Jacobi-Bellman equation by a pertubational procedure and asymptotic weak stability in probability of the controlled nonlinear system is verified in a deterministic way.
Polynomial Chaos-based Input Shaper Design under Time-Varying Uncertainty
Goethe-Universität Frankfurt am Main（法兰克福歌德大学）；Louisiana State University（路易斯安那州立大学）；University at Buffalo（布法罗纽约州立大学）；NASA Langley Research Center（美国国家航空航天局兰利研究中心）
Adaptive type-2 fuzzy second order sliding mode control for nonlinear uncertain chaotic system
QUERE Laboratory, Engineering Faculty, University of Setif 1（塞提夫第一大学工程学院QUERE实验室）；CReSTIC of Reims Champagne-Ardenne University,IUT de Troyes（兰斯香槟-阿登大学CReSTIC中心特鲁瓦高等师范学院）
Consistency regularization-based Deep Polynomial Chaos Neural Network Method for Reliability Analysis
College of Aerospace Science and Engineering, National University of Defense Technology（国防科技大学空天科学学院）；Defense Innovation Institute, Chinese Academy of Military Science（中国人民解放军军事科学院国防科技创新研究院）
