joint flexibility is a very important factor to consider in the controller design for robot manipulators if high performance is expected. most of the research works on control of flexible-joint robots in literature have ignored the actuator dynamics to avoid complexity in controller design. the problem of designing nonlinear controller for a class of single-link flexible-joint robot manipulator...

The active power filter has gained much more attention because of its effective performance to mitigate the harmonics. This paper presents shunt active power filter (SAPF) controlled by PI controller to compensate the harmonics. Also, it introduces a new artificial intelligent technique called Bacterial Foraging Optimization to optimize the parameters of the PI-controller through on-line self-a...

The paper deals with a controller design for the nonlinear processes using genetic algorithm and neural model. The aim was to improve the control performance using genetic algorithm for optimal PID controller tuning. The plant model has been identified via an artificial neural network from measured data. The genetic algorithm represents an optimisation procedure, where the cost function to be m...

In this paper an artificial neural network, which realizes a nonlinear adaptive control algorithm, has been applied in a control system of variable speed generating system. The speed is adjusted automatically as a function of load power demand. The controller employs a single layer neural network to estimate the unknown plant nonlinearities online. Optimization of the controller is difficult be...

A Riccati-based tracking controller with collision avoidance capabilities is presented for proximity operations of spacecraft formation flying near elliptic reference orbits. The proposed dynamical model incorporates nonlinear accelerations from an artificial potential field, in order to perform evasive maneuvers during proximity operations. In order to validate the design of the controller, te...

anti-lock braking system (abs) is a nonlinear and time varying system including uncertainty, so it cannot be controlled by classic methods. intelligent methods such as fuzzy controller are used in this area extensively; however traditional fuzzy controller using simple type-1 fuzzy sets may not be robust enough to overcome uncertainties. for this reason an interval type-2 fuzzy controller is de...

in this paper an optimal controller is proposed for a self-balancing electrical vehicle called segway pt. this vehicle has one platform and two wheels on the sides and the rider stands on the platform. a handlebar, as a navigator, is attached to the body of segway, with which the rider controls the vehicle. since segway uses electrical energy produced by batteries, resource consumption manageme...

Because of their parallelism, functional approXimation and learning capabilities, artificial neural networks can be effectively employed to apjmximate nonlinear functions, and to synthesize controllers for nonlinear dynamic systems. The use of dynamic neural networks to model and control dynamic systems is of great importance in the control paradigm. The intent of this paper is to use one such ...

This paper presents an Artificial Neural Network (ANN)-based modeling technique for prediction of outlet temperature, pressure and mass flow rate of gas turbine combustor. Results obtained by present modeling were compared with those obtained by experiment. The results showed the effectiveness and capability of the proposed modeling technique with reasonable accuracies of about 95 percent. This...