System Identification I

The notion of fuzziness as defined in this paper relates to situations in which the source of imprecision is not a random variable or a stochastic process, but rather a class or classes which do not possess sharply defined boundaries, e.g., the “class of bald men,” or the “class of numbers which are much greater than 10,” or the “class of adaptive systems,” etc. A basic concept which makes it possible to treat fuzziness in a quantitative manner is that of a fuzzy set, that is, a class in which there may be grades of membership intermediate between full membership and non-membership. Thus, a fuzzy set is characterized by a membership function which assigns to each object its grade of membership (a number lying between 0 and 1) in the fuzzy set. After a review of some of the relevant properties of fuzzy sets, the notions of a fuzzy system and a fuzzy class of systems are introduced and briefly analyzed. The paper closes with a section dealing with optimization under fuzzy constraints in which an approach to...

Fuzzy sets and systems

Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems

The standard extended state observer based control (ESOBC) method is only applicable for a class of single-input-single-output essential-integral-chain systems with matched uncertainties. It is noticed that systems with nonintegral-chain form and mismatched uncertainties are more general and widely exist in practical engineering systems, where the standard ESOBC method is no longer available. To this end, it is imperative to explore new ESOBC approach for these systems to extend its applicability. By appropriately choosing a disturbance compensation gain, a generalized ESOBC (GESOBC) method is proposed for nonintegral-chain systems subject to mismatched uncertainties without any coordinate transformations. The proposed method is able to extend to multi-input-multi-output systems with almost no modification. Both numerical and application design examples demonstrate the feasibility and efficacy of the proposed method.

/pdf/generalized-extended-state-observer-based-control-for-hzsdfbl5ol.pdf

Generalized Extended State Observer Based Control for Systems With Mismatched Uncertainties

Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will concern you to try reading modelling and control of robot manipulators as one of the reading material to finish quickly.

Modelling and Control of Robot Manipulators

A robust vector control intended for a doubly fed induction motor (DFIM) mode is considered. The state-all-flux induction machine model with a flux orientation constraint is replaced by a simpler control model. The double-flux orientation leads to orthogonality between the stator and rotor fluxes, resulting in a linear and decoupled machine control and an optimal developed torque. The inner flux controllers are designed using the Lyapunov linearisation approach. This flux control is exponentially stabilised independently of the speed. Associated with sliding-mode control, this solution shows good robustness with respect to parameter variations, measurement errors and noisse. Finally, a speed controller is designed using two methods: the first with a PI controller and the second with the Lyapunov method associated with a backstepping procedure, especially employed for the unknown load torques. This second solution shows good robustness with respect to inertia variation and guarantees torque and speed tracking. The global asymptotic stability of the overall system is proven theoretically. The simulation and experimental results largely confirm the effectiveness of the proposed DFIM system control.

Robust backstepping vector control for the doubly fed induction motor

—In this paper; we are interested in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation and new control scheme. We present after the development and the synthesis of a stabilizing control laws design based on sliding mode in order to perform best tracking results. It ensures locally asymptotic stability and desired tracking trajectories. Nonlinear observer is then synthesized in order to estimate the unmeasured states and the effects of the external disturbances such as wind and noise. Finally simulation results are also provided in order to illustrate the performances of the proposed controllers.

Nonlinear Observer Design and Sliding Mode Control of Four Rotors Helicopter

The work proposed in this paper aim to design a robust second order sliding mode controller for the attitude stabilization of a four rotor helicopter (commonly known as quadrotor) to overcome to the chattering phenomena in classical (first) sliding mode control, while preserving the invariance property of sliding mode. The both controllers have been designed to stabilize the roll, pitch and yaw angles of the system. The theoretical results have been validated in simulation and in real time and a good performance results are obtained in second order sliding mode controller comparing with the classical sliding mode controller in stabilization, tracking and external disturbances rejection.

Mohamed Tadjine

Papers

Robust backstepping vector control for the doubly fed induction motor

Nonlinear Observer Design and Sliding Mode Control of Four Rotors Helicopter

Classical and second order sliding mode control solution to an attitude stabilization of a four rotors helicopter: From theory to experiment

Augmented reality for photovoltaic pumping systems maintenance tasks

Trajectory tracking with obstacle avoidance of redundant manipulator based on fuzzy inference systems