This article presents the design of super twisting sliding mode control (STSMC) based on radial basis function neural network (RBFNN) for path tracking two link robot manipulator. The proposed controller is utilized to guarantee and achieve that surface can be in equilibrium point within a short time avoid problem chattering at output. Lyapunov theory used presenting new convergence proof. Also...

This article proposes an adaptive dynamic reference (ADR) control for power converters in a microgrid. Conventionally, two separate controllers are required to the input current and dc bus voltage. The proposed ADR eliminates need additional controller by utilizing simple discrete-time model generate appropriate voltage regulation. technique is easy design guarantees convergence of its nominal ...

A reinforcement learning-based adaptive optimal fuzzy controller is proposed for maximum power point tracking (MPPT) control of a variable-speed permanent magnet synchronous generator-based wind energy generation system. The algorithm consists critic, an controller, and estimator. critic built based on neuro-fuzzy inference system (ANFIS) network instead the neural as normal to reduce computati...

Adaptive control of robot manipulators has been an active research topic in the last 15 years. The main motivation of this has been the interest in adding a reliable degree of robustness to the closed–loop system, specially in manufacturing system, where the manipulator frequently achieves pick and place tasks of materials and parts, whereby adaptation of the payload changes helps to guarantee ...

This study offers a unique contribution to the literature by investigating the convergence of province-level carbon dioxide emission intensity among a panel of 30 provinces in China over the period 1990-2010. We use a novel, spatial dynamic panel data model to test the hypotheses of absolute beta convergence and conditional beta convergence. Our results suggest: (1) CO2 emission intensities are...

We consider output feedback adaptive stabilization for second-order systems in the presence of bounded exogenous disturbances. This case is of particular interest as it has been shown that, in the presence of exogenous disturbances, direct adaptive control schemes for minimum phase plants with relative degree 1 exhibit parameter divergence eventually leading to instability. We present controlle...

The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, th...

In this work, a Neuro-Sliding mode controller (NSMC) for piezo-positioning mechanism (PEA) was designed. This controller takes into account parameter uncertainties and unknown external disturbances. The LuGre model is used to establish the mathematical model of the system including the mechanical motion dynamics, the hysteresis friction, the load disturbance and parameter uncertainties. Using t...

The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, th...