Relay Feedback and Multivariable Control

This doctoral thesis treats three issues in control engineering related to relay feedback and multivariable control systems. Linear systems with relay feedback is the first topic. Such systems are shown to exhibit several interesting behaviors. It is proved that there exist multiple fast relay switches if and only if the sign of the first non-vanishing Markov parameter of the linear system is positive. It is also shown that these fast switches can appear as part of a stable limit cycle. A linear system with pole excess one or two is demonstrated to be particularly interesting. Stability conditions for these cases are derived. It is also discussed how fast relay switches can be approximated by sliding modes. Performance limitations in linear multivariable control systems is the second topic. It is proved that if the top left submatrices of a stable transfer matrix have no right half-plane zeros and a certain high-frequency condition holds, then there exists a diagonal stabilizing feedback that makes a weighted sensitivity function arbitrarily small. Implications on control structure design and sequential loop-closure are given. A novel multivariable laboratory process is also presented. Its linearized dynamics have a transmission zero that can be located anywhere on the real axis by simply adjusting two valves. This process is well suited to illustrate many issues in multivariable control, for example, control design limitations due to right half-plane zeros. The third topic is a combination of relay feedback and multivariable control. Tuning of individual loops in an existing multivariable control system is discussed. It is shown that a specific relay feedback experiment can be used to obtain process information suitable for performance improvement in a loop, without any prior knowledge of the system dynamics. The influence of the loop retuning on the overall closed-loop performance is derived and interpreted in several ways

Design, construction and commissioning of the Thermal Screen Control System for the CMS Tracker detector at CERN

The CERN (European Organization for Nuclear Research) laboratory is currently building the Large Hadron Collider (LHC). Four international collaborations have designed (and are now constructing) detectors able to exploit the physics potential of this collider. Among them is the Compact Muon Solenoid (CMS), a general purpose detector optimized for the search of Higgs boson and for physics beyond the Standard Model of fundamental interactions between elementary particles. This thesis presents, in particular, the design, construction, commissioning and test of the control system for a screen that provides a thermal separation between the Tracker and ECAL (Electromagnetic CALorimeter) detector of CMS (Compact Muon Solenoid experiment). Chapter 1 introduces the new challenges posed by these installations and deals, more in detail, with the Tracker detector of CMS. The size of current experiments for high energy physics is comparable to that of a small industrial plant: therefore, the techniques used for controls and regulations, although highly customized, must adopt Commercial Off The Shelf (COTS) hardare and software. The âﾜslow controlâ systems for the experiments at CERN make extensive use of PLCs (Programmable Logic Controllers) and SCADA (Supervisory Control and Data Acquisition) to provide safety levels (namely interlocks), regulations, remote control of high and low voltages distributions, as well as archiving and trending facilities. The system described in this thesis must follow the same philosophy and, at the same time, comply with international engineering standards. While the interlocks applications belong straightforwardly to the category of DES (Discrete Event System), and are therefore treated with a Finite State Machine approach, other controls are more strictly related to the regulation problem. Chapter 2 will focus on various aspects of modern process control and on the tools used to design the control system for the thermal screen: the principles upon which the controller is designed and tuned, and the model validated, including the Multiple Input-Multiple Output (MIMO) problematics are explained. The thermal screen itself, the constraints and the basis of its functioning are described in Chapter 3, where the thermodynamical design is discussed as well. For the LHC experiments, the aim of a control system is also to provide a well defined SIL (Safety Interlock Level) to keep the system in a safe condition; yet, in this case, it is necessary to regulate the temperature of the system within certain values and respect the constraints arising from the specific needs of the above mentioned subsystems. The most natural choice for a PLC-based controller is a PID (Proportional Integral Derivative) controller. This kind of controller is widely used in many industrial process, from batch production in the pharmaceutics or automotive field to chemical plants, distillation columns and, in general, wherever a reliable and robust control is needed. In order to design and tune PID controllers, many techniques are in use; the approach followed in this thesis is that of black-box modeling: the system is modeled in the time domain, a transfer function is inferred and a controller is designed. Then, a system identification procedure allows for a more thorough study and validation of the model, and for the controller tuning. Project of the thermal screen control including system modeling, controller design and MIMO implementation issues are entirely covered in Chapter 4. A systems engineering methodology has been followed all along to adequately manage and document every phase of the project, complying with time and budget constraints. A risk analysis has been performed, using Layer of Protection Analysis (LOPA) and Hazard and Operability Studies (HAZOP), to understand the level of protection assured by the thermal screen and its control components. Tests planned and then performed to validate the model and for quality assurance purposes are described in Chapter 5. A climatic chamber has been designed and built at CERN, where the real operating conditions of the thermal screen are simulated. Detailed test procedures have been defined, following IEEE standards, in order to completely check every single thermal screen panel. This installation allows for a comparison of different controller tuning approaches, including IAE minimization, Skogestad tuning rules, Internal Model Control (IMC), and a technique based upon the MatLab Optimization toolbox. This installation is also used for system identification purposes and for the acceptance tests of every thermal screen panel (allowing for both electrical and hydraulic checks). Also, tests have been performed on the West Hall CERN experimental area , where a full control system has been set up, for interlock high- and low- voltage lines. The interlock system operating procedures and behaviour have been validated during real operating conditions of the detector esposed to a particle beam. The satisfactory results of tests take the project to full completion, allowing the plan to reach the âﾜexitâ stage, when the thermal screen is ready to be installed in the Tracker and ready to be operational

Advances in Control of Power Electronic Converters

This book proposes a list of contributions in the field of control of power electronics converters for different topologies: DC-DC, DC-AC and AC-DC. It particularly focuses on the use of different advanced control techniques with the aim of improving the performances, flexibility and efficiency in the context of several operation conditions. Sliding mode control, fuzzy logic based control, dead time compensation and optimal linear control are among the techniques developed in the special issue. Simulation and experimental results are provided by the authors to validate the proposed control strategies

New results in relay feedback analysis and multivariable stability margins

Ph.DDOCTOR OF PHILOSOPH

A LOW-COST APPROACH TO DATA-DRIVEN FUZZY CONTROL OF SERVO SYSTEMS

Servo systems become more and more important in control systems applications in various fields as both separate control systems and actuators. Ensuring very good control system performance using few information on the servo system model (viewed as a controlled process) is a challenging task. Starting with authors’ results on data-driven model-free control, fuzzy control and the indirect model-free tuning of fuzzy controllers, this paper suggests a low-cost approach to the data-driven fuzzy control of servo systems. The data-driven fuzzy control approach consists of six steps: (i) open-loop data-driven system identification to produce the process model from input-output data expressed as the system step response, (ii) Proportional-Integral (PI) controller tuning using the Extended Symmetrical Optimum (ESO) method, (iii) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller in terms of the modal equivalence principle, (iv) closed-loop data-driven system identification, (v) PI controller tuning using the ESO method, (vi) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller. The steps (iv), (v) and (vi) are optional. The approach is applied to the position control of a nonlinear servo system. The experimental results obtained on laboratory equipment validate the approach

Model-based control methods to improve the power qualify of grid-connected single-phase inverters.

Power electronic converters are commonly used for interfacing distributing generation sources (DGs) to the electrical power system networks. This is necessary because these DGs usually have different output characteristics and cannot be connected directly to the local load and/or the grid. The power electronic front-end converter is an inverter whose dc link is fed by an ac/dc converter or by a dc/dc converter, according to the DG source type. The commercial front-end inverters are designed to operate either in grid-connected (GC) mode or in stand-alone (SA) mode. In the SA mode, the inverter is connected to local load, but in the GC mode the inverter must be connected to the utility grid and a local load could be connected to this system as well. Based on this, any designed or proposed controller for such systems should work well in both operation modes. The control objective in SA mode is to improve the quality of the local load voltage, and the control objective in GC mode is to inject clean current to the grid with low total harmonic distortion (THD). Most of the control schemes in the literature have been designed to work in one of these operation modes and ensure low THD either for the local load voltage or for the injected grid current. However, some of the existing control schemes in the literature proposed different control architectures for each operation mode. Moreover, there are a few researches have been reported in the literature based on the cascaded control theory to obtain low THD for both the local load voltage simultaneously with the injected current to the grid in the grid-connected mode. Due to the growing penetration of the DG sources in the residential applications, single-phase grid-connected inverters have gained much attention. For this reason, the single-phase grid-connected inverter systems have been chosen in our study. Since such systems have nonlinearity in its behavior, different nonlinear model-based control schemes have been designed in order to improve the quality of the local load voltage while injecting clean current to the grid for single-phase grid-connected inverter systems by using single structure control scheme. Furthermore, the proposed control schemes ensure the seamless transfer between GC and SA operation modes without adjusting the controller structure and with self-synchronization ability

Systems Structure and Control

The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc

Fractional internal -model - control filter - based controller tuning for series cascade unstable plants

The disturbances and plant uncertainties are common in the process industry. In such conditions, the controller must manage robustness from the predefined plant models and be suitable for industrial applications. This paper uses a fractional-order theory in a controller design for a series cascade unstable plant. The methodology is developed using well-known terms for the industry, namely internal-model-control (IMC) and maximum sensitivity. The primary loop is designed with a fractionalorder filter–PID controller. The inner loop is built with IMC-PI controller with desired robustness value. In-depth comparisons reveal that the proposed scheme performs better regarding plant uncertainties and load disturbances

Improved multi model predictive control for distillation column

Model predictive control (MPC) strategy is known to provide effective control of chemical processes including distillation. As illustration, when the control scheme was applied to three linear distillation columns, i.e., Wood-Berry (2x2), Ogunnaike-Lemaire-Morari-Ray (3x3) and Alatiqi (4x4), the results obtained proved the superiority of linear MPC over the conventional PI controller. This is however, not the case when nonlinear process dynamics are involved, and better controllers are needed. As an attempt to address this issue, a new multi model predictive control (MMPC) framework known as Representative Model Predictive Control (RMPC) is proposed. The control scheme selects the most suitable local linear model to be implemented in control computations. Simulation studies were conducted on a nonlinear distillation column commonly known as Column A using MATLAB® and SIMULINK® software. The controllers were compared in terms of their ability in tracking set points and rejecting disturbances. Using three local models, RMPC was proven to be more efficient in servo control. It was however, not able to cope with disturbance rejection requirement. This limitation was overcome by introducing two controller output configurations: Maximizing MMPC and PI controller output (called hybrid controller, HC), and a MMPC and PI controller output switching (called MMPCPIS). When compared to the PI controller, HC provided better control performances for disturbance changes of 1% and 20% with an average improvement of 12% and 20% of the integral square error (ISE), respectively. It was however, not able to handle large disturbance of + 50% in feed composition. This limitation was overcome by MMPCPIS, which provided improvements by 17% and 20% of the ISE for all of types and magnitudes of disturbance change. The application of MMPCPIS on a single model MPC strategy produced almost similar performance for both types of disturbances, while its application on MMPC yielded better results. Based on the results obtained, it can be concluded that the proposed HC and MMPCPIS deserve further detailed investigations to serve as linear control approaches for solving complex nonlinear control problems commonly found in chemical industr