A PD-Type State-Dependent Riccati Equation With Iterative Learning Augmentation for Mechanical Systems
نویسندگان
چکیده
This work proposes a novel proportional-derivative (PD)-type state-dependent Riccati equation (SDRE) approach with iterative learning control (ILC) augmentation. On the one hand, PD-type gains could adopt many useful available criteria and tools of conventional PD controllers. other SDRE adds nonlinear optimality characteristics to controller, i.e., increasing stability margins. These advantages ILC correction part deliver precise law capability error reduction by learning. The provides symmetric-positive-definite distributed suboptimal gain $\mathrm{K}(\mathrm{x})$ for input xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{u}=-\mathrm{R}^{-1}(\mathrm{x})\mathrm{B}^{T}(\mathrm{x})\mathrm{K}(\mathrm{x})\mathrm{x}$ . sub-blocks overall xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{R}^{-1}(\mathrm{x})\mathrm{B}^{T}(\mathrm{x})\mathrm{K}(\mathrm{x})$ , are not necessarily symmetric positive definite. A new design is proposed transform optimal into two like controllers as xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{u}= -\mathrm{K}_{\mathrm{SP}}(\mathrm{x})\mathrm{e}-\mathrm{K}_{\mathrm{SD}}(\mathrm{x})\dot{\mathrm{e}}$ form allows us analytically prove learning-based controller mechanical systems; presents guaranteed uniform boundedness in finite-time between loops. also developed differential (SDDRE) manipulate final time. SDDRE expresses boundary condition, which imposes constraint on time that be used control. So, availability an asset enhancing classical linear this tool. rules benefit from gradient descent method both regulation tracking cases. One guaranteed-stability even first loop manipulator, illustrative example, was simulated problems. Successful experimental validation done show system practice implementation variable-pitch rotor benchmark.
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ژورنال
عنوان ژورنال: IEEE/CAA Journal of Automatica Sinica
سال: 2022
ISSN: ['2329-9274', '2329-9266']
DOI: https://doi.org/10.1109/jas.2022.105533