: - This paper addresses an inverse controller design for excitation system with changing parameters and nonsmooth nonlinearities in the actuator. The existence of such nonlinearities and uncertainty imposes a great challenge for the controller development. To address such a challenge, support vector machines (SVM) will be adopted to model the process and the controller is constructed using SVM. The SVM, used to approximate nonlinearities in the plant as well as the actuator, are adjusted by an adaptive law via back propagation (BP) algorithms. To guarantee convergence and for faster learning, adaptive learning rates and convergence theorems are developed. Simulations show that the proposed inverse controller has better performance in system damping and transient improvement. Key-Words: - nonlnear control, inverse system, support vector machines, adaptive control, model identification, actuator uncertainty