This work describes a CACSD tool for automatic design of robust controllers for hydraulic turbines. The tool calcul the optimal controller using the MATLAB hinfopt function and it serves as a practical and effective solution for the laborious task of designing a different controller for each type of turbine and generator, and different parameters and conditions Results of the simulation of a ge...

We present a new optimal control approach to robust control of robot manipulators in the framework of Lin et al [7]. Because of the unknown load placed on a manipulator and the other uncertainties in the manipulator dynamics, it is important to design a robust control law that will guarantee the performance of the manipulator under these uncertainties. To solve this robust control problem, we f...

A version of nonlinear generalization of the C1-control problem, which deals with the attenuation of persistent bounded disturbances in &-sense, is investigated in this paper. The methods used in this paper are motivated by [23]. The main idea in the C1-performance analysis and synthesis is to construct a certain invariant subset of the state-space such that achieving disturbance rejection is e...

Two new Bayesian approaches to Robust Parameter Design (RPD) are presented that recompute the optimal control factor settings based on on-line measurements of the noise factors. A dual response model approach to RPD is taken. The first method uses the posterior predictive density of the responses to determine the optimal control factor settings. A second method uses in addition the predictive d...

We consider a linear programming problem in which the constraint matrix is uncertain. Each element of the constraint matrix is modeled as a random variable whose range is asymmetrically bounded around its mean. We construct a formulation that yields a solution with a better objective value, compared to the classical robust optimization approach, while taking the risk that the solution may becom...

Over the last few years, much research has been dedicated to the creation of decisions support systems for space system engineers or even for completely automated design methods capturing the reasoning of system experts. However, the problem of taking into account the uncertainties of variables and models defining an optimal and robust spacecraft design have not been tackled effectively yet. Th...

Abstract: This paper presents a novel robust voltage-based control approach for tracking control of electrical manipulators by reducing the effects of uncertainties. The proposed control law is simple, fast response and robust with acceptable tracking error and without chattering problem. This approach is superior to torque-based control approaches due to considering the role of actuators. The ...

Adaptive robust control (ARC) of MIMO nonlinear systems transformable to two semi-strict feedback forms are considered. The forms can have both parametric uncertainties and uncertain nonlinearities such as external disturbances. In addition, the forms allow coupling and appearance of parametric uncertainties in the input matrix of each layer. Furthermore, the usual assumption on the linear para...

One of the most important challenges facing an electric grid is to incorporate renewables and distributed energy resources (DERs) to the grid. Because of the associated uncertainties in power generations and peak power demands, opportunities for improving the functioning and reliability of the grid lie in the design of an efficient, yet pragmatic distributed control framework with guaranteed ro...

The aim of the paper is to present an approach to optimal control of biotechnological processes, described by fuzzy sets which is based on genetic algorithms (GA). It allows more adequate, flexible and intelligent (human oriented) description of bioprocess dynamic and inclusion of this information in an effective and robust optimization procedure. Related algorithms and software are designed an...