This paper investigates the multi-player non-zero-sum game problem for unknown linear continuous-time systems with unmeasurable states.By only accessing the data information of input and output,a data-driven learning ...This paper investigates the multi-player non-zero-sum game problem for unknown linear continuous-time systems with unmeasurable states.By only accessing the data information of input and output,a data-driven learning control approach is proposed to estimate N-tuple dynamic output feedback control policies which can form Nash equilibrium solution to the multi-player non-zero-sum game problem.In particular,the explicit form of dynamic output feedback Nash strategy is constructed by embedding the internal dynamics and solving coupled algebraic Riccati equations.The coupled policy-iteration based iterative learning equations are established to estimate the N-tuple feedback control gains without prior knowledge of system matrices.Finally,an example is used to illustrate the effectiveness of the proposed approach.展开更多
基金supported by National Key R&D Program of China under Grant No.2021ZD0112600the National Natural Science Foundation of China under Grant No.62373058+3 种基金the Beijing Natural Science Foundation under Grant No.L233003National Science Fund for Distinguished Young Scholars of China under Grant No.62025301the Postdoctoral Fellowship Program of CPSF under Grant No.GZC20233407the Basic Science Center Programs of NSFC under Grant No.62088101。
文摘This paper investigates the multi-player non-zero-sum game problem for unknown linear continuous-time systems with unmeasurable states.By only accessing the data information of input and output,a data-driven learning control approach is proposed to estimate N-tuple dynamic output feedback control policies which can form Nash equilibrium solution to the multi-player non-zero-sum game problem.In particular,the explicit form of dynamic output feedback Nash strategy is constructed by embedding the internal dynamics and solving coupled algebraic Riccati equations.The coupled policy-iteration based iterative learning equations are established to estimate the N-tuple feedback control gains without prior knowledge of system matrices.Finally,an example is used to illustrate the effectiveness of the proposed approach.
