Abstract: An adaptive observer and nonlinear feedback control strategy with constraints on control action are developed by using supervisor learning rule of adaptive neuron and the theory of functional -link networks. The convergence of adaptive observer and the stability of control system are proven. They are applied to the control of an exothermic stirred -tank reactor. It is shown that an adaptive observer for concentration can be constructed for a reaction system when only temperature measurements are on line available. An adaptive observer is used to identify the pre- exponential Arrhenius constant and to provide on- line estimation of the unmeasured reactant concentration for a nonlinear state - feedback controller. Simulations show that the combined observer/controller provides satisfactory closed - loop behavior, fast responses and strong robustness. Estimated and actual concentration are in good agreement. Nonlinear feedback controller can provide effective feedback control over a wide range of operating conditions.

摘要： 提出了一种基于神经网络的自适应观测和非线性控制策略,证明了自适应观测器的收敛件和非线性控制系统的稳定性,将其用于连续搅拌釜式放热反应器的浓度控制。根据可在线测量的反应温度,在线估计不可在线测量的反应物浓度和辨识Arrhenius指前因子,并利用重构的状态信息设计出带约束的非线性控制策略。仿真结果表明,观测器/控制器的组合提供了满意的闭环特性,证实了本文方法的有效性。