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Differentially Flat Systems

TLDR
This chapter discusses linear time-Invariant SISO Systems, MIMO Systems, and Flatness and Optimal Trajectories.
Abstract
Illustrating the power, simplicity, and generality of the concept of flatness, this reference explains how to identify, utilize, and apply flatness in system planning and design. The book includes a large assortment of exercises and models that range from elementary to complex classes of systems. Leading students and professionals through a vast array of designs, simulations, and analytical studies on the traditional uses of flatness, Differentially Flat Systems contains an extensive amount of examples that showcase the value of flatness in system design, demonstrate how flatness can be assessed in the context of perturbed systems and apply static and dynamic feedback controller design techniques.

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Journal ArticleDOI

Model-free control

TL;DR: Model-free control and the corresponding ‘intelligent’ PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account.
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Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots

TL;DR: An algorithm is presented for wheeled mobile robot trajectory generation that achieves a high degree of generality and efficiency and is efficient enough to use in real time due to its use of nonlinear programming techniques that involve searching the space of parameterized vehicle controls.
Journal ArticleDOI

Non-linear estimation is easy

TL;DR: Non-linear state estimation and some related topics like parametric estimation, fault diagnosis and perturbation attenuation are tackled here via a new methodology in numerical differentiation within the framework of differential algebra.
Journal ArticleDOI

On the Control of the Permanent Magnet Synchronous Motor: An Active Disturbance Rejection Control Approach

TL;DR: The proposed high-gain GPI observer-based ADR controller is justified in terms of a singular perturbation approach and verified by means of realistic computer simulations, using the MATLAB/SIMULINK-PSIM package.
Journal ArticleDOI

Model-Free Control and Intelligent PID Controllers: Towards a Possible Trivialization of Nonlinear Control ?

TL;DR: A model-free control and a control with a restricted model for finite-dimensional complex systems that may be viewed as a contribution to "intelligent" PID controllers, the tuning of which becomes quite straightforward, even with highly nonlinear and/or time-varying systems.
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