this paper presents a stable new algorithm for force/position control in robot manipulators. in this algorithm, position vectors are measured by sensors and then used in the control law. since using force sensor has some issues such as high costs and technical problems, an approach is presented to overcome these issues. in this respect, force sensor is replaced by an adaptive fuzzy estimator to...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

Two phenomena can produce chattering: switching of input control signal and the large amplitude of this switching (switching gain). To remove the switching of input control signal, dynamic sliding mode control (DSMC) is used. In DSMC switching is removed due to the integrator which is placed before the plant. However, in DSMC the augmented system (system plus the integrator) is one dimension bi...

In this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.Based on the backstepping technique, the adaptive fuzzy controller is constructed. The main contributions of the paper...

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 novel technique is investigated for pid controller adaptation in order to control thetemperature of a liquid-phase reactor tank by using a heat exchanger system. as for nonlinearity,time delay problems and model uncertainties introduced by the heat exchanger, an interval type-2fuzzy system (it2fs) is implemented to enhance and improve the total control performance.moreover, the fuzzy inferenc...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

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...