Robust Control Toolbox

Robust Control Toolbox™ provides functions, algorithms, and blocks for analyzing and tuning control systems for performance and robustness. You can create uncertain models by combining nominal dynamics with uncertain elements, such as uncertain parameters or unmodeled dynamics. You can analyze the impact of plant model uncertainty on control system performance and identify worst-case combinations of uncertain elements. H-infinity and mu-synthesis techniques let you design controllers that maximize robust stability and performance. The toolbox automatically tunes both SISO and MIMO controllers. These can include decentralized, fixed-structure controllers with multiple tunable blocks spanning multiple feedback loops. The toolbox lets you tune one controller against a set of plant models. You can also tune gain-scheduled controllers. You can specify multiple tuning objectives, such as reference tracking, disturbance rejection, stability margins, and closed-loop pole locations.

References in zbMATH (referenced in 53 articles )

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  1. Ravanbod, Laleh; Noll, Dominikus; Apkarian, Pierre: Branch and bound algorithm with applications to robust stability (2017)
  2. Apkarian, Pierre; Noll, Dominikus; Ravanbod, Laleh: Nonsmooth bundle trust-region algorithm with applications to robust stability (2016)
  3. Veenman, Joost; Scherer, Carsten W.; Köroğlu, Hakan: Robust stability and performance analysis based on integral quadratic constraints (2016)
  4. Wang, Shu; Pfifer, Harald; Seiler, Peter: Robust synthesis for linear parameter varying systems using integral quadratic constraints (2016)
  5. Xue, Dingyü; Chen, YangQuan: Scientific computing with MATLAB (2016)
  6. Chestnov, V.N.: $H_\infty$-approach to controller synthesis under parametric uncertainty and polyharmonic external disturbances (2015)
  7. Pfifer, Harald; Seiler, Peter: Robustness analysis of linear parameter varying systems using integral quadratic constraints (2015)
  8. Xue, Dingyü; Chen, YangQuan: Modeling, analysis and design of control systems in MATLAB and Simulink (2015)
  9. Chestnov, V.N.: Synthesis of discrete $H_\infty$-controllers with given stability margin radius and settling time (2014)
  10. Mathiyalagan, K.; Sakthivel, R.; Anthoni, S.Marshal: Robust exponential stability and $H_\infty$ control for switched neutral-type neural networks (2014)
  11. Palacios-Quiñonero, F.; Rubió-Massegú, J.; Rossell, J.M.; Karimi, H.R.: Feasibility issues in static output-feedback controller design with application to structural vibration control (2014)
  12. Pérez López, César: Matlab control systems engineering (2014) ioport
  13. Petersen, Ian R.; Tempo, Roberto: Robust control of uncertain systems: classical results and recent developments (2014)
  14. Taylor, J.D.; Messner, William: Controller design for nonlinear systems using the contoured robust controller bode plot (2014)
  15. Rubió-Massegú, Josep; Palacios-Quiñonero, Francisco; Rossell, Josep M.; Karimi, Hamid Reza: Static output-feedback control for vehicle suspensions: a single-step linear matrix inequality approach (2013) ioport
  16. Sariyildiz, Emre; Ohnishi, Kouhei: Analysis the robustness of control systems based on disturbance observer (2013)
  17. Scherer, Carsten W.: Structured $H_\infty$-optimal control for nested interconnections: a state-space solution (2013)
  18. Chen, Bor-Sen; Lin, Ying-Po: On the information transmission ability of nonlinear stochastic dynamic networks (2012)
  19. Hayden, Richard A.; Stefanek, Anton; Bradley, Jeremy T.: Fluid computation of passage-time distributions in large Markov models (2012)
  20. She, Jinhua; Zhou, Lan; Wu, Min; Zhang, Jie; He, Yong: Design of a modified repetitive-control system based on a continuous-discrete 2D model (2012)

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