This paper presents an adaptive interval type-2 fuzzy sliding mode controller for a class of unknown nonlinear discrete-time systems with training data corrupted by noise or rule uncertainties involving external disturbances. Adaptive interval type-2 fuzzy control scheme and sliding mode control (SMC) approach are incorporated to implement the main objective of controlling the plant to track a ...

Autonomous robots operating in unstructured environments clearly require some capacity for adaptive behaviour. This paper presents a method for achieving an adaptive response based on a multi-layer control architecture. The primary level of control is composed of the Behaviour Synthesis Architecture [1] which is continuously modified by a secondary layer, composed of a Fuzzy Logic controller. T...

In this paper a predictive controller for real-time target tracking in mobile robotics is proposed based on adaptive/evolving Takagi-Sugeno fuzzy systems, eTS. The predictive controller consists of two modules; i) a conventional fuzzy controller for robot motion control, and ii) a modelling tool for estimation of the target movements. The prediction of target movements enables the controller to...

accurate and correct performance of controller in cruise control systems is important. hence, in such systems, controller should optimize itself against noise and probable changes in system dynamic. as a matter of fact, in this article three approaches have been conducted to-ward this purpose: mit, direct estimation and indirect estimation. these approaches are used as controllers to track refe...

In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based control is proposed for the tracking of a Micro-Electro Mechanical Systems (MEMS) gyroscope sensor. The ANFIS is used to train parameters of the controller for tracking a desired trajectory. Numerical simulations for a MEMS gyroscope are looked into to check the effectiveness of the ANFIS control scheme. It proves that the sy...

In this paper, an adaptive fuzzy tracking control approach is proposed for a class of single-inputsingle-output (SISO) nonlinear systems in which the unknown continuous functions may be nonlinearlyparameterized. During the controller design procedure, the fuzzy logic systems (FLS) in Mamdani type are applied to approximate the unknown continuous functions, and then, based on the minimal learnin...