A neuro-adaptive approach for autonomous flight controller design for aerial robots is proposed. Three intelligent modules are implemented to control respectively the altitude, airspeed and roll angle of the airplane, through which the altitude and the latitude-longitude of the unmanned aerial vehicle are controlled. Each intelligent module consists of a conventional feedback controller and a n...

In this paper, an intelligent adaptive control system (IACS) for induction motor (IM) servo drive to achieve high dynamic performance is proposed. The proposed IACS comprises a recurrent functional-linkbased Petri fuzzy-neural-network (RFLPFNN) controller and a robust controller so that the developed adaptive control scheme has more robustness against parameters uncertainties and approximation ...

This paper studies the H∞ tracking control for uncertain nonlinear multivariable systems. We propose a strategy, which combines adaptive wavelet-type Takagi-Sugeno-Kang (TSK) fuzzy brain emotional learning controller (WTFBELC) and robust compensator. As WTFBELC, it is main designed to mimic ideal controller. The proposed WTFBELC obtain much better ability of handling nonlinearities uncertaintie...

Emotional learning is new tool in the field of machine learning that the inspired from limbic system. The various models of emotional learning (BEL) have been successfully utilized in many learning problems. For example, control applications and prediction problems. In this paper a new architecture based on a brain emotional learning model that can be used in classification problem (BELC). This...

In this article, a speed control of DC motor is designed and illustrated using fuzzy logic-based programmable logic controller (PLC). The DC motor is an attractive part of electrical equipment in many industrial applications requiring variable speed and load specifications due to its ease of controllability. The designed system is consisted of three main parts including programmable logic contr...

An intelligent controller is described for an automated vehicle planning its trajectory based on sensor and communication data received. The intelligent controller is designed using a stochastic learning automaton. Using the data received from on-board sensors, two automata (for lateral and longitudinal actions) are capable of learning the best possible actions to avoid collisions. The system h...

In this paper, an almost new control approach called terminal synergetic control which works based on user defined manifold is applied to a nonlinear helicopter model. Stability analysis is convestigated using Lyapunov stability theory. Synergetic controller is applied to this nonlinear fifth-order helicopter model to control height and angle. Simulation results showed that it has faster and sm...

This paper presents a way of improving computerbased with lifelike presence in learning environment. The approach combines Intelligent Tutoring Systems with research on human emotion in Cognitive Sciences, Psychology and Communication. Considering the relations between emotion, cognition and action in contextual learning, we propose an architecture of a multiagent-based instructional system in ...

Evolution and the brain have done a marvelous job solving many tricky problems in action control, including problems of learning, hierarchical control over serial behavior, continuous recalibration, and fluency in the face of slow feedback. Given that evolution tends to be conservative, it should not be surprising that these solutions are exploited to solve other tricky problems, such as the de...