A method for building the rule-base of a fuzzy controller, using the iterative learning and adaptive neural fuzzy training is tested in practical conditions. This method aims to engage intelligent features to controller design procedure, by implying concepts and techniques from artificial intelligence as learning or adapting. An iterative self-learning algorithm is used to gather useful and tru...

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controlle...

A new type of adaptive neural network fuzzy controller based on the stability for the double inverted pendulum control problem is introduced. The method uses a fusion function to reduce the dimension of the system, reducing the number of input variables to solve the fuzzy rule explosion problem. In order to optimize and amend the front-part and later-part parameter of TakagiSugeno fuzzy model, ...

Choosing the adaptation gains for a model reference adaptive controller is a complex matter. Low values of the adaptation gains may result in very slow adaptation, while high adaptation gains may lead to instability in the adaptation process. Good values of them depend on many factors in this type of non-linear system; the input amplitude and frequency, the process performance specification and...

-Arterial pressure control is an important task, mostly in postsurgical patients. This work proposes an adaptive system to patient’s arterial blood pressure control using sodium nitroprusside. The proposed system uses Proportional-Integral (PI), Fuzzy-PI, rule-based and predictive controllers. To introduce an adaptive characteristic to PI controller, it was used an intelligent fuzzy supervisor ...

This study develops a fuzzy sliding mode controller (FSMC) based on a variable boundary layer. A fuzzy inference mechanism is used to on-line tune the thickness of the boundary layers of the controller. Minimum rule base has been used for the fuzzy inference system which results in low calculation effort. The aim of this paper is to design a controller which will eliminate the chattering of FSM...

A discrete pole-placement-based and multiestimation-based adaptive control scheme involving a relative adaptation dead zone is presented for a plant with known poles and unknown zeros. The basic usefulness of the proposed multiestimation scheme is related to the use of a set of models of reduced order associated with the multiestimation scheme instead of a high-order one. Depending on the frequ...

This paper proposes a switching adaptive control for trajectory tracking of unmanned aircraft systems. The switching adaptive control method is designed to overcome the wind disturbance and achieve a proper tracking performance for control systems. In the suggested system, the wind disturbance is regarded as a finite set of uncertainties; a controller is designed for each uncertainty, and a per...

In this paper, the design and implementation of adaptive speed controller for a sensorless synchronous reluctance motor (SynRM) drive system is proposed. A combination of well-known adaptive input-output feedback linearization (AIOFL) and adaptive backstepping (ABS) techniques are used for speed tracking control of SynRM. The AIOFL controller is capable of estimating motor two-axis inductances ...

A robust adaptive sampled-data feedback stabilization scheme is presented for a class of systems with nonlinear additive perturbations. The proposed controller generates a control input by using high-gain static or dynamic feedback from nonuniform sampled values of the output. A simple adaptation rule adjusts the gain and the sampling period of the controller.