Pages that link to "Item:Q2628483"

The following pages link to Unified frameworks for sampled-data extremum seeking control: global optimisation and multi-unit systems (Q2628483):

Displaying 24 items.

• A robust extremum seeking scheme for dynamic systems with uncertainties and disturbances (Q254575) (← links)
• Iterative learning control based on extremum seeking (Q254596) (← links)
• Extremum seeking control of a nonholonomic system with sensor constraints (Q290833) (← links)
• A non-gradient approach to global extremum seeking: an adaptation of the Shubert algorithm (Q357565) (← links)
• Multi-agent source seeking via discrete-time extremum seeking control (Q466471) (← links)
• Extremum seeking of dynamical systems via gradient descent and stochastic approximation methods (Q889000) (← links)
• On the accuracy of gradient estimation in extremum-seeking control using small perturbations (Q1626850) (← links)
• Deterministic and stochastic Newton-based extremum seeking for higher derivatives of unknown maps with delays (Q1648013) (← links)
• Robust sampled-data PI controller design for networked control systems (Q1660967) (← links)
• Extremum seeking for dynamic maps using Lie brackets and singular perturbations (Q1679081) (← links)
• A dynamical interval Newton method (Q2034215) (← links)
• Extremum seeking via a time-delay approach to averaging (Q2059356) (← links)
• Robustness to delay mismatch in extremum seeking (Q2068559) (← links)
• A hybrid dynamical systems perspective on reinforcement learning for cyber-physical systems: vistas, open problems, and challenges (Q2094057) (← links)
• Sampled-data extremum-seeking framework for constrained optimization of nonlinear dynamical systems (Q2151945) (← links)
• An extremum seeking-based approach for Nash equilibrium seeking in \(N\)-cluster noncooperative games (Q2174006) (← links)
• Extremum seeking boundary control for PDE-PDE cascades (Q2242931) (← links)
• Multidimensional global extremum seeking via the DIRECT optimisation algorithm (Q2356647) (← links)
• Multi‐parametric extremum seeking‐based iterative feedback gains tuning for nonlinear control (Q5298550) (← links)
• Numerical optimization‐based extremum seeking control of a class of constrained nonlinear systems via finite‐time state transition (Q6082765) (← links)
• 100 years of extremum seeking: a survey (Q6119740) (← links)
• Newton-based extremum seeking of higher-derivative maps with time-varying delays (Q6494280) (← links)
• Data-enabled extremum seeking: a cooperative concurrent learning-based approach (Q6494284) (← links)
• Model-guided extremum seeking-case studies (Q6495671) (← links)