This paper addresses the integrated fault estimation and robust control problem for unknown linear discrete-time systems. The considered problem is formulated as a multivariable multiobjective optimisation one. A data-based coordinated design strategy that co-designs an output feedback H ∞ / H ∞ controller and a residual generator is proposed to optimise both H ∞ fault estimation and robust control performances. Based on the input and output data, the design parameters of the controller and the residual generator are determined by using Q-learning technique and introducing a new matrix block identification Q-learning method, respectively. Compared with the existing single-variable multiobjective optimisation methods, the proposed strategy can achieve better fault estimation performance, remove the restriction condition of using input and output data, and extend the traditional Q-learning technique to the case of designing a residual generator with a low-rank condition. Finally, simulation results illustrate the effectiveness of the proposed method.
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