Development of U-model enhansed nonlinear systems

摘要: Nonlinear control system design has been widely recognised as a challenging issue where the key objective is to develop general model prototype with conciseness, flexibility and manipulability, so that designed can best match required performance or specifications. As generic systematic approach, U-model concept appeared in Prof. Quanmin Zhu’s Doctoral thesis, approach was firstly published journal paper titled ‘U-model based pole placement for nonlinear plants’ 2002. The polynomial precisely describes wide range of smooth models, defined controller output u(t-1) time-varying models converted from original model. Within this equivalent expression, first study plants simple mapping exercise ordinary linear difference equations polynomials terms plant input u(t-1). The framework realised concise applicable by using such approaches. Since publication, methodology progressed evolved over course decade. By technique, researchers have proposed many different algorithms systems including; adaptive control, internal sliding mode predictive neural network control. However, limited research concerned analysis robust stability systems. This project proposes suitable method analyse developed against uncertainty. parameter variation bounded, thus margin closed loop be determined LMI (Linear Matrix Inequality) procedure. U-block an assignor system. With bridge it connects state space Therefore, approaches are able enhanced within structure. With development, stage provides flexible solutions complex problems, methodologies directly applied plant-based design. next milestone work expands technique into establish new framework, U-state model, providing simplification approaches. The described equations, which linear/nonlinear after conversion. Then, basic idea corresponding feedback on principle. employed realisation under structure. desired vectors xd(t), (such placement) designer specifications LQR). Then substitute (regarded time variable xd(t) = x(t) ). obtained one roots root-solving iterative algorithm. A quad-rotor rotorcraft dynamic inverted pendulum introduced verify MIMO/SIMO used determine equation, then root solver. Numerical examples case studies demonstrate effectiveness methods.