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Online learning algorithm for zero-sum games with integral reinforcement learning

Vamvoudakis K. G., Vrabie D., Lewis F. L.

Journal of Artificial Intelligence and Soft Computing Research

2011

Vol. 1, No. 4

315--332

In this paper we introduce an online algorithm that uses integral reinforcement knowledge for learning the continuous-time zero sum game solution for nonlinear systems with infinite horizon costs and partial knowledge of the system dynamics. This algorithm is a data based approach to the solution of the Hamilton-Jacobi-Isaacs equation and it does not require explicit knowledge on the system’s drift dynamics. A novel adaptive control algorithm is given that is based on policy iteration and implemented using an actor/ disturbance/critic structure having three adaptive approximator structures. All three approximation networks are adapted simultaneously. A persistence of excitation condition is required to guarantee convergence of the critic to the actual optimal value function. Novel adaptive control tuning algorithms are given for critic, disturbance and actor networks. The convergence to the Nash solution of the game is proven, and stability of the system is also guaranteed. Simulation examples support the theoretical result.

Use of neural networks for dynamic modelling and predictive control of power plant systems

Lazar C., Carari S., Vrabie D., Ivana D.

Systems Science

2005

Vol. 31, no 1

37-44

Boiler drum is a critical power plant component having nonlinearities and a non-minimum phase response but, despite this fact, control structures with PID controllers are usually used in industrial applications. In the last decades, important efforts have been made to improve the closed loop performance of the drum level controller by using on-line self-tuning approaches. In this paper, such a method of on-line adaptation is presented based on a neuro-predictive technique of the authors of [4], [5]. In order to implement the neuro-predictive procedure a neural model was developed for drum level process. By means of simulation, a comparison between the obtained drum level controller's operation and that of a classic controller of the type PI under similar conditions is carried out.