Study of Sampled Data Control Approach towards Prosthetic Eye Model for Initiating the Non Deterministic Aspect

This paper investigates the problem of passive controller design for a class of nonlinear systems under variable sampling. The Takagi-Sugeno (T-S) fuzzy modeling method is utilized to represent the nonlinear systems. Attention is focused on the design of passive controller for the T-S fuzzy systems via sampled-data control approach. Under the concept of very-strict passivity, a novel time-dependent Lyapunov functional is constructed to develop passive analysis criteria and passive controller synthesis conditions. A new sampled-data controller is designed to guarantee that the resulting closed-loop system is very-strictly passive. These conditions are formulated in the form of linear matrix inequalities (LMIs), which can be solved by convex optimization approach. Finally, an application example is given to demonstrate the feasibility and effectiveness of the proposed results.

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Attitude tracking of mars entry vehicles via fuzzy sampled-data control approach

53rd IEEE Conference on Decision and Control ◽

10.1109/cdc.2014.7040452 ◽

2014 ◽

Cited By ~ 1

Author(s):

Zi-Peng Wang ◽

Huai-Ning Wu ◽

Bo Jiang ◽

Lei Guo

Keyword(s):

Sampled Data ◽

Control Approach ◽

Data Control ◽

Attitude Tracking ◽

Sampled Data Control

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Sampled-data Control of a Class of Nonlinear Flat Systems With Application to Unicycle Trajectory Tracking

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2234491 ◽

2005 ◽

Vol 128 (3) ◽

pp. 722-728 ◽

Cited By ~ 8

Author(s):

N. Léchevin ◽

C. A. Rabbath

Keyword(s):

Trajectory Tracking ◽

Control Method ◽

Digital Design ◽

Control Law ◽

Sampled Data ◽

Control Laws ◽

Control Approach ◽

Flat Systems ◽

Data Control ◽

Sampled Data Control

In this paper we propose a flatness-based nonlinear sampled-data control approach for the trajectory tracking of nonlinear differentially flat systems that can be expressed in cascade form. The nonlinear sampled-data control method relies on the flatness property for the generation of appropriate trajectories, with the design of one-step predictive control laws, and on controller discretization by means of an averaging-like method. In the paper we demonstrate that the causality problem that might arise in the implementation is avoided by using an estimator based on numerical integration techniques of sufficiently high order. Stability-like properties are proved. Numerical simulations show that the proposed sampled-data control law offers the best closed-loop performance when compared with nonlinear direct digital design for the trajectory tracking of a rotorcraft-like UAV modeled as the unicycle. The synthesis of the nonlinear sampled-data control law takes advantage of the feedback linearizability property of the unicycle model. Furthermore, the proposed nonlinear sampled-data control does not rely on approximated discretization techniques and is computed from exponentially convergent steering trajectories that result from the stabilization of the linearized unicycle model.

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