Exact Output Regulation for Nonlinear Systems Described by Takagi–Sugeno Fuzzy Models

Meda-Campaña, J. A.; Gomez-Mancilla, J. C.; Castillo–Toledo, B.

doi:10.1109/tfuzz.2011.2172689

Cited by 43 publications

(32 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1: Nonlinear models are unnecessarily rewritten as TS ones through the sector nonlinearity approach [5], but their convex structure is never used to obtain LMIs; therefore, there is nothing properly fuzzy in this work and, up to eqs. (38)-(39) in [1], its results are equivalent to the already existent sufficient and necessary conditions in [2]. In other words, the EOFRP in [1] is the same as the SFORP in [2].…”

Section: Introductionmentioning

confidence: 68%

“…(38)-(39) in [1], its results are equivalent to the already existent sufficient and necessary conditions in [2]. In other words, the EOFRP in [1] is the same as the SFORP in [2].…”

Section: Introductionmentioning

confidence: 74%

“…on Fuzzy Systems [1]. An scheme for exact output fuzzy regulation problem (EOFRP) of Takagi-Sugeno (TS) systems is thereby proposed by considering the fuzzy model as a special class of linear time-varying (LTV) system; this assumption allows the implementation of a regulation scheme mimicking the sufficient and necessary conditions in [2] with certain nonlinear mappings being algebraically or dynamically derived.…”

Section: Introductionmentioning

confidence: 99%

“…The work considered in this note [1] presents two problems (treated in detail in Secs. II and III, respectively):…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comments on “Exact Output Regulation for Nonlinear Systems Described by Takagi–Sugeno Fuzzy Models”

Robles

Bernal

2015

IEEE Trans. Fuzzy Syst.

View full text Add to dashboard Cite

This note considers the work entitled "Exact Output Regulation for Nonlinear Systems Described by Takagi-Sugeno Fuzzy Models" published in IEEE Trans. on Fuzzy Systems [1], where the authors try to provide a fuzzy approach to the well known problem of exact output regulation [2] via a dynamic implementation of the nonlinear mapping between the state space and the steady-state zero error manifold. Two problems invalidate this methodology: 1) The results do not depend on the fuzzy structure as claimed by the authors; 2) The results have been obtained without properly taking into account the time-derivative of the aforementioned nonlinear mapping. Example B in [1] is revised and corrected to illustrate these issues.

show abstract

Section: Introductionmentioning

confidence: 68%

“…(38)-(39) in [1], its results are equivalent to the already existent sufficient and necessary conditions in [2]. In other words, the EOFRP in [1] is the same as the SFORP in [2].…”

Section: Introductionmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

“…The work considered in this note [1] presents two problems (treated in detail in Secs. II and III, respectively):…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comments on “Exact Output Regulation for Nonlinear Systems Described by Takagi–Sugeno Fuzzy Models”

Robles

Bernal

2015

IEEE Trans. Fuzzy Syst.

View full text Add to dashboard Cite

show abstract

“…fuzzy model-based (FMB) control techniques (see, for instance, Dong et al 2009Dong et al , 2010Ding 2011;Esfahani and Sichani 2011;Campana et al 2012). Basically, this type of models allows the representation of nonlinear systems in terms of local linear models that are smoothly connected by means of nonlinear fuzzy membership functions (MFs) so that it is possible to apply, for instance, well-established Lyapunov and LMI-based tools for parameter varying control systems (Tanaka and Wang 2001;Mozelli and Palhares 2011).…”

mentioning

confidence: 99%

A T–S Fuzzy Approach to the Local Stabilization of Nonlinear Discrete-Time Systems Subject to Energy-Bounded Disturbances

Klug

Castelan

Coutinho

2015

J Control Autom Electr Syst

View full text Add to dashboard Cite

This paper addresses the local stabilization problem of nonlinear discrete-time systems subject to energybounded disturbances by means of T-S fuzzy models. A fuzzy state feedback controller is designed such that the input-to-state stability in the 2 sense of the original nonlinear system is guaranteed in a bounded region of the state space. Such a region is related to the exactness of the T-S model and describes the domain around the origin where the convexity property remains valid. In addition, an estimate of the closed-loop reachable set is provided for a given class of 2 disturbances. Three (convex) optimization problems are proposed to either minimize the estimate of the reachable set, improve the disturbance tolerance or minimize the 2 -gain from the disturbance input to the regulated output. Numerical examples are considered to illustrate the approach demonstrating the effectiveness of the proposed technique for the control synthesis of nonlinear discrete-time systems.

show abstract

Robust Double‐integral T‐S Fuzzy Output Regulation for Nonlinear Systems

Lian

Liu

Chiu

2017

Asian Journal of Control

View full text Add to dashboard Cite

This paper proposes a robust double‐integral T‐S fuzzy output regulator design for affine nonlinear systems in the presence of parametric uncertainty and external disturbance. First, we adopt double integrators (an error integrator and an input integrator) to obtain an augmented T‐S fuzzy model representation which has a common input matrix of fuzzy rules. This property yields less stability conditions. Next, by introducing a set of virtual desired variables (VDVs), a double‐integral VDV‐based fuzzy regulator is proposed to cope with unknown bias and to achieve asymptotical output regulation. Afterward, the controller is simplified to avoid VDV calculation and enhance robustness to uncertainty and external disturbance. In contrast to traditional regulation design, the double‐integral non‐VDV fuzzy regulator design reduces the number of fuzzy controller rules and stability LMIs. Moreover, the error coordinate transformation is removed and the uncertainty is allowed in this paper. Finally, a DC/DC buck converter system is taken as the example to demonstrate the expected performance.

show abstract

Exact Output Regulation for Nonlinear Systems Described by Takagi–Sugeno Fuzzy Models

Cited by 43 publications

References 38 publications

Comments on “Exact Output Regulation for Nonlinear Systems Described by Takagi–Sugeno Fuzzy Models”

Comments on “Exact Output Regulation for Nonlinear Systems Described by Takagi–Sugeno Fuzzy Models”

A T–S Fuzzy Approach to the Local Stabilization of Nonlinear Discrete-Time Systems Subject to Energy-Bounded Disturbances

Robust Double‐integral T‐S Fuzzy Output Regulation for Nonlinear Systems

Contact Info

Product

Resources

About