Uncertain Models and Robust Control
By A. Weinmann. 2002
297 citations recorded by the source corpus.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/3a78a051b97880ac9823e2e9ac90d85c02cf12b3
How researchers see this paper
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In Control and Systems Engineering
- Nathan Michael
- Vijay R. Kumar
- Shaojie Shen
- Carlos Olalla
- Ramon Leyva
- Han Ho Choi
- Krishna K. Busawon
- Isabelle Queinnec
Citations in the corpus
- Robust LQR Control for PWM Converters: An LMI Approach (2009, methodology): “There exist other gradient-based approaches to obtain robust LQR controllers [19].”
- LMI-Based Sliding Surface Design for Integral Sliding Mode Control of Mismatched Uncertain Systems (2007, methodology): “The assumption of norm boundedness of A(t) and B(t) has been utilized in the literature such as Weinmann [13] or so.”
- Autonomous multi-floor indoor navigation with a computationally constrained MAV (2011, methodology): “Tuning of control gains is accomplished via optimal control methods (LQR) based on a linearized system model [20].”
- Disturbance attenuation using proportional integral observers (2001, background): “Proportional integral observers (PIO) are observers in which an additional term, which is proportional to the integral of the output estimation error, is added in order to achieve some desired robustness performance (see, e.g. Beale and Shafai 1987, Saif 1992, Shafai and Caroll 1985, Weinmann 1991).”
- Variable structure control of dynamical systems with mismatched norm-bounded uncertainties: An LMI approach (2001, methodology): “The assumption of norm boundedness of ¢A…x; t† and ¢B…x; t† has been utilized in many literatures such as Sobel et al. (1989), Weinmann (1991), etc.”
- On the simultaneous state and unknown input estimation of complex systems via a multiple model strategy (2009, unknown): “This observer known for its robustness properties [7, 8] has been successfully employed in order to cope with the state and the UI estimations when the UI is characterised by low frequency signals (constant or slowly varying signals) [9, 10, 11, 12, 13].”