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MPC and genetic algorithm for flying pendulum control
US & West ·
An approach combining model predictive control (MPC) and an online genetic algorithm is proposed to estimate the unknown pendulum length in a flying inverted pendulum control problem. Experiments on a real setup confirmed the accuracy and robustness of the method under various initial conditions and disturbances.
Why it matters
Demonstrates real-time adaptation of MPC to uncertain parameters, which is important for robust control in complex dynamic systems.
arXiv:2610.18400v1 Announce Type: new Abstract: Data trading markets that span industries and regions are expanding, but the implicit trust that supports data use within an organization does not carry over to cross-domain exchange.
Digital twins (DTs) can generate dense synthetic fingerprints for localization via ray tracing, yet the sim-to-real domain gap limits their direct use, particularly in cell-free millimeter-wave (mmWave) deployments where distributed geometries and blockage-induced sparsity widen the mismatch.
arXiv:2610.17274v1 Announce Type: new Abstract: Model reduction can substantially reduce the computational burden of model predictive control (MPC) for high-dimensional systems, but a reduced dimension chosen for performance may be insufficient for safety-critical operation.
