A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Combination of bioelectrochemical systems and electrochemical capacitors: Principles, analysis and opportunities

© 2019 The Authors Bioelectrochemical systems combine electrodes and reactions driven by microorganisms for many different applications. The conversion of organic material in wastewater into electricity occurs in microbial fuel cells (MFCs). The power densities produced by MFCs are still too low for application. One way of increasing their performance is to combine them with electrochemical capacitors, widely used for charge storage purposes. Capacitive MFCs, i.e. the combination of capacitors and MFCs, allow for energy harvesting and storage and have shown to result in improved power densities, which facilitates the up scaling and application of the technology. This manuscript summarizes the state-of-the-art of combining capacitors with MFCs, starting with the theory and working principle of electrochemical capacitors. We address how different electrochemical measurements can be used to determine (bio)electrochemical capacitance and show how the measurement data can be interpreted. In addition, we present examples of the combination of electrochemical capacitors, both internal and external, that have been used to enhance MFC performance. Finally, we discuss the most promising applications and the main existing challenges for capacitive MFCs

Linear and nonlinear arx model for intelligent pneumatic actuator systems

System modeling in describing the dynamic behavior of the system is very important and can be considered as a challenging problem in control systems engineering. This article presents the linear and nonlinear approaches using AutoRegressive with Exogenous Input (ARX) model structure for the modeling of position control of an Intelligent Pneumatic Actuator (IPA) system. The input and output data of the system were obtained from real-time experiment conducted while the linear and nonlinear mathematical models of the system were obtained using system identification (SI) technique. Best fit and Akaike’s criteria were used to validate the models. The results based on simulation reveals that nonlinear ARX (NARX) had the best performance for the modeling of position control of IPA system. The results show that nonlinear modeling is an effective way of analyzing and describing the dynamic behavior and characteristics of IPA system. This approach is also expected to be able to be applied to other systems. A future study exploring the execution of other model structures in demonstrating the position control of IPA system would be exceptionally intriguing

Performance Analysis of Batch Reactor Temperature Control Systems

The aim of this project was to investigate the performance of a number of key control strategies in the temperature control of batch reactors. A bench scale model was built and a batch production system was then implemented on this model. As there was no a priori knowledge of the system a number of common system identification methods were investigated. The system was controlled using a Mitsubishi FX(2)N Programmable Logic Controller which was interfaced with a PC running ICONICS, a Supervisory Control And Data Acquisition software package. The system identification methods produced two different models for the system and these models were examined against the actual system using Matlab/SIMULINK, a software package used for technical computing. Then a number of tuning rules were investigated and implemented on both models with the results compared and contrasted. The standard Industry criteria were used to compare the performance of the servo response for each controller. The PI controller using Zeigler-Nichols tuning rules was set as the bench mark. The Cascaded control strategy offered no increase in performance in the servo response in either the actual process or the SIMULINK models. However the regulatory response of the Cascaded strategy would offer an improvement on the performance of the PI controller. The performance of the Smith Predictor was limited due to the minimal time delay relative to the time constant. The Integrating method proved to offer an improvement on the two point method in terms of system performance and in the time required to identify the initial controller. Also the Smith Predictor offered a slight improvement in both the laboratory model and in the Matlab/SIMULINK simulations

Energy efficiency improvement through MPC-based peripherals management for an industrial process test-bench

High energy costs evince the growing need for energy efficiency in industrial companies. This paper presents a solution at the industrial machine level to obtain efficient energy consumption. Therefore, a controller inspired by the well-known model predictive control (MPC) strategy was developed for the management of peripheral devices. The validation of the control requires a test-bench to emulate the energy consumption of a manufacturing machine. The test-bench has four devices, two used to emulate the periodic and fixed energy consumption of the manufacturing process and two as peripherals, subject to rules associated with the process. Consequently, a subspace identification (SI) was employed to identify energy models to simulate the behavior of the device. As a final step, a performance comparison between a rule-based control (RBC) and the proposed predictive-like controller revealed the remarkable energy savings. The MPC results show an energy saving of around 3% with respect to RBC as well as an instant maximum energy consumption reduction of 8%, approximately.Peer ReviewedPostprint (published version

State space model building and validation by comparison with non-linear models and performing SSA

The level of penetration of renewables and power electronics in the grid is increasing, and in the future, it may even be possible to have a 100 % converter-based transmission system[1]. In such a future, methods for analyzing the stability of the grid with high penetration of power electronics and renewable energy sources are essential. However, due to the increased penetration of power electronics in power systems and the instability of renewable energy sources, the stability analysis of power systems can be very complex. In this paper, GFOL(Grid following system) and GFOR(Grid forming system) are modeled and verified using the state-space equation, and then the stability of the system is analyzed based on the data from the matrix of the state-space equation. This thesis first describes the working principles, advantages and disadvantages, key components, and key technologies of GFOL(Grid following system) and GFOR(Grid forming system). The system components are described and modeled. Control schemes are described, the basic necessary control modules are detailed and simulation results are provided to illustrate the control methods described. This thesis then investigates the application of state-space modeling to the modeling of circuits and control elements. The linearisation of non-linear equations is introduced and the state-space equation of state models for GFOL and GFOR are constructed and validated using small signal disturbance analysis. Finally, the stability of the GFOR and GFOL systems was assessed and analyzed through indicators such as eigenvalues and participation coefficients. This paper provides a simple and reliable example for analyzing the stability of modern power systems by modeling, verifying, and analysing the state-space equations of power system