Continuous Stirred Tank Reactor (CSTR) plays an important role in the process industries. It helps for maintaining the temperature of the liquid in the reactors. This paper deals with the comparison of adaptive control and conventional PID control in CSTR process. In the adaptive control, Model Reference Adaptive Control (MRAC) and Self-Tuning Regulator (STR) methods are used. The Recursive Lea...

In this paper a new technique is proposed to design an online control algorithm using the Radial Basis Functions Neural Network (RBFNN). The controller is an RBFNN based direct self-tuning regulator (STR) that overcomes several shortcomings of the inverse control design using the neural networks. The control algorithm performs equally good to both minimum phase and non-minimum phase plants. The...

In the last decade, policy gradient methods have significantly grown in popularity in the reinforcement–learning field. In particular, they have been largely employed in motor control and robotic applications, thanks to their ability to cope with continuous state and action domains and partial observable problems. Policy gradient researches have been mainly focused on the identification of effe...

Database tuning is a common problem, but it requires much knowledge about the characteristics of the database system and the expected workload. Dynamically changing workload complicates the search for the perfect settings. In this contribution we present several approaches that autonomously examine the operations and adjust different parameters. Even though different tools for this task are ava...

We argue about the importance of embedding the successful mechanism of Inflation in the context of a fundamental theory. We review some of the attempts in this direction made in the framework of String Theory. In particular we report on recent developments in Brane Inflation with emphasis on the fine tuning issue.

The robust self-tuning regulator of a class of linear systems, which can be described by the input-output Auto-Regressive Moving Average with exogenous (ARMAX) mathematical model with unknown and time-varying parameters, at bounded external disturbances is developed. A scheme of polynomial approximation has been applied to approximate the unknown and time-varying parameters of systems. The modi...