A new adaptive multiple-controller is proposed incorporating a neural network based Generalized Learning Model (GLM). The GLM assumes that the unknown complex plant is represented by an equivalent stochastic model consisting of a linear time-varying sub-model plus a Radial Basis Function (RBF) neural-network based learning sub-model . The proposed non-linear multiple-controller methodology prov...

Taking an intelligent trimming device hydraulic manipulator as the research object, aiming at uncertainty, nonlinearity and complexity of its system, a trajectory tracking control scheme is studied in this paper. In light virtual work principle, coupling dynamic model system established. order to improve anti-interference adaptive abilities compound strategy combining neuro-fuzzy inference (ANF...

In this paper, an online adaptation scheme for tuning of PID parameters is presented. This scheme is based upon our previous works on using a data-driven method to obtain a sufficient condition for robust stability and integrating robustness into the Unfalsified Control framework. Here, a modified bumpless transfer approach to facilitate the adaptation of the PID controller parameters is presen...

Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATL...

The paper is dedicated to experimenting a simple LMI procedure to design simple adaptive control laws for ’almost stable’ systems. The procedure initially conceived for regulation problems around zero equilibrium point is extended to PID like tracking control problem. LMI results gives conditions to guarantee robustness of the simple adaptive control law with respect to parametric uncertainties...

today, dc motors is still being used globally due to their easy speed controllability. in this article, an adaptive neuro-fuzzy inference system (anfis) controller is designed for dc motors. the main purpose of performing such task is to reduce the dc motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

Recent progress in the theory of neural networks played a major role in the development of new tools and techniques for modelling, identification and control of complex nonlinear dynamic systems. Intelligent control, with a special focus on neuro-control has been used successfully to solve difficult real control problems which are nonlinear, noisy and relatively complex. This is due to the fact...

Proportional-integral-derivative (PID) controllers are extensively used in engineering practices for their simple structures, robustness to model errors, and easy operations. At present, there is a great variety of PID controllers. Companies have developed intelligent regulators with functions automatically tuning parameters. For present controllers, strategies such as intelligence, self-adapta...

The design and use of PID controllers is a part of what has been denominated Classical Control, which as the name implies, has been studied for many years (DiStefano et al. 1996), however it continues to be a source for research (Alvarez et al. 2008), (Ang et al. 2008), (Su et al. 2010). The structure of the controller contains a differential term to aid in the reduction of system friction and ...

This study proposes an adaptive control method of a weigh feeder. A weigh feeder dispenses material into a process at a precise rate, and it has been employed in industries, e.g., process control, cement manufacturing plants, food industry equipment, and so on. To introduce advanced control into industries, self-tuning controllers are designed for controlling a weigh feeder. Three difference co...