状態推定性能を最適化したオブザーバベースScaled H_∞制御

—飛行制御におけるオブザーバのバーチャルセンサとしての利用可能性—

抄録

This paper addresses observer-based scaled H_∞ control design with state estimation performance optimized. The simultaneous design of observer and state-feedback gains in H_∞ control framework is, in general, formulated in terms of Bilinear Matrix Inequality (BMI), which is not tractable compared to Linear Matrix Inequality (LMI). Similarly, the simultaneous design of H_∞ controllers and scaling matrices for multiple uncertainty blocks is also formulated in terms of BMI. On these issues, under some particular plant structures, we have proposed a tractable design method of the simultaneous design of observer and state-feedback gains as well as scaling matrices with some conservatism admitted due to the structural constraints for the matrices introduced in the so-called “dilation” procedure; however, observer performance was not optimized, and thus there is no guarantee on it. On this issue, this paper proposes two-step design, viz., control performance is firstly optimized using the existing method, and then observer performance is optimized under a slightly relaxed control performance imposed as a constraint. This approach expects the controllers' states faithfully work as the estimated plants' states while control performance is almost kept as optimized. This property is illustrated in this paper by the lateral-directional flight controller for a research airplane MuPAL-α validated through hardware-in-the-loop simulation tests.