Shane Dominic

A nonhomogeneous super-twisting algorithm for systems of relative degree more than one

Abstract This paper presents a nonhomogeneous continuous super-twisting algorithm for systems of relative degree more than one. The conditions of finite-time convergence to the origin are obtained and the robustness of the designed algorithm is discussed. The paper concludes with numerical simulations illustrating performance of the designed algorithms.

Dynamic Modeling and Simulation of Compressor Trains for an Air Separation Unit

Abstract This paper presents dynamic models of a compressor train for an air separation unit. The model is derived from physical equations. A block library and complete models are implemented in Matlab/Simulink. Model accuracy is validated by comparing simulation results with realistic data gained from an existing industrial plant. The goal of modeling is to obtain a better understanding of the dynamic behavior in different operating modes and to get a base for design of new control strategies, e.g. a supervisory controller for minimizing power consumption of the total compressor train.

An Adaptive, Advanced Control Strategy for KPI-Based Optimization of Industrial Processes

The need to deal with rapid change in an environmentally and economically friendly manner has led to renewed interest in data-driven, online process optimization. Although various methods, such as economic model predictive control (EMPC), are available to achieve this goal, they require that the process model be available and relatively accurate and that there be no process changes. Recently, the focus has shifted to using economic key performance indices (KPIs) to design supervisory controllers to regulate the process. In order to accomplish this, accurate models of the highly nonlinear KPIs are needed. A solution to this problem is to develop a two-step control strategy consisting of a static, offline component and a dynamic, online component. This paper proposes the use of a linear, BILIMOD method combined with a self-partitioning algorithm for the static component and gradient-based optimization method for the dynamic component. In order to deal with process changes, the static model parameters are updated. The proposed new controller strategy is tested on the wastewater treatment process. It is shown that the proposed method can quickly and effectively achieve the desired optimal point with minimal disturbance to the overall process.

Real-Time Optimization of Automatic Control Systems With Application to BLDC Motor Test Rig

Driven by the increasing demands on production quality, system performance, and the reliability and safety issues of process industry, this paper proposes an integrated process monitoring and control design technique for industrial control systems. The proposed approach is an alternative realization of Youla parameterization which allows the performance of the controlled systems to be improved without modifying or replacing the predesigned control systems, while the closed-loop stability is guaranteed. In addition, a residual signal is available for the fault detection and isolation purpose. The effectiveness and performance of the proposed approach are demonstrated on a brushless direct current motor test rig.

PLC-Based Real-Time Realization of Flatness-Based Feedforward Control for Industrial Compression Systems

In this paper, we present a novel programmable logic controller (PLC)-based real-time realization of a flatness-based feedforward control (FFC) scheme. The proposed approach is applied to an industrial fuel-gas compression system which is used to supply fuel gas to the gas turbines in combined cycle power plants. Due to the increasing demand for fast operation point transitions with high performance and accuracy requirements, the currently applied decentralized proportional-integral-derivative controllers appear to be not appropriate any more. Hence, by means of system simulations, a new flatness-based FFC design has been shown to provide improved control performance. In this paper, we bridge the gap between simulation-based control design and practical applicability, in that, we present the real-time realization of the approach on a PLC. Furthermore, the PLC-based controller is tested on a hardware-in-the-loop platform running with a complex compression system model in real time. The results reveal that the flatness-based control design can be implemented on a real compressor system.

A Nonhomogeneous Super-Twisting Algorithm

This chapter presents a nonhomogeneous continuous super-twisting algorithm for systems of dimension more than one. The conditions of finite-time convergence to the origin are obtained and the robustness of the designed algorithm is discussed. The chapter concludes with numerical simulations illustrating performance of the designed algorithms.

A nonhomogeneous finite-time convergent super-twisting algorithm

This paper presents a nonhomogeneous continuous super-twisting algorithm for systems of relative degree more than one. The conditions of finite-time convergence to the origin are obtained and the robustness of the designed algorithm is discussed. The paper concludes with numerical simulations illustrating performance of the designed algorithms.