No abstract

This paper is concerned with the controllability and observability for a class of fractional linear systems with two different orders. The sufficient and necessary conditions for state controllability and state observability of such systems are established. The results obtained extend some existing results of controllability and observability for fractional dynamical systems.

This paper is concerned with the controllability and observability for a class of matrix Riccati type differential systems. The solution of such matrix systems is obtained via using variation of parameters. Meanwhile, the sufficient and necessary conditions for state controllability and state observability of such systems are established.

In this paper, a reinforcement learning (RL) approach is developed to solve the robust control for uncertain continuous-time linear systems. The objective is to find a feedback control law for the uncertain linear system using an online policy iteration algorithm. The robust control problem is solved by constructing an extended algebraic Riccati equation with properly defined weighting matrices for a general uncertain linear system. An online policy iteration algorithm is developed to solve the robust control problem based on RL principles without knowing the nominal system matrix. The convergence of the algorithm to the robust control solution for uncertain linear systems is proved. The simulation examples are given to demonstrate the effectiveness of the proposed algorithm. The results extend the design method of robust control to uncertain linear systems. INDEX TERMS Reinforcement learning, uncertain linear system, robust control, algebraic Riccati equation.