Algebraic robust control of a closed circuit heating-cooling system with a heat exchanger and internal loop delays

This study demonstrates the use of a simple algebraic controller design for a cooling-heating plant with a through-flow air-water heat exchanger that evinces long internal delays with respect to the robustness to plant model uncertainties and variable ambient temperature conditions during the season. The advantage of the proposed design method consists in that the delays are not approximated but fully considered. Moreover, the reduction of sensitivity to model parameters’ variations yields the better applicability regardless modeling errors or environmental fluctuations. The infinite-dimensional mathematical model of the plant has been obtained by using anisochronic modeling principles. The key tool for the design is the ring special of quasipolynomial meromorphic functions (RQM). The Two-Feedback-Controllers (TFC) rather than the simple negative control feedback loop is utilized, which enables to solve the reference tracking and disturbance rejection independently and more efficiently. The eventual controller is then tuned such that robust stability and robust performance requirements are fulfilled. The tuning procedure is supported by a performance optimization idea. Since the originally obtained controller is of the infinite-dimensional nature, a possible way how to substitute it by a simplified finite-dimensional one is proposed for engineering practice. The functionality of both the controllers is compared and verified by simulations as well as by real measurements which prove a very good performance. © 2016 Elsevier LtdEuropean Regional Development Fund under the project CEBIA-Tech Instrumentation [CZ.1.05/2.1.00/19.0376

Design of Robust PID Controllers with Constrained Control Signal Activity

This thesis presents a new method for design of PI and PID controllers with the level of control signal activity taken into consideration. The main reason why the D-part is often disabled in industrial control loops is because it leads to control signal sensitivity of measurement noise. A frequently varying control signal with too high amplitude will very likely lead to actuator wear and tear. For this reason it is extremely important for any PID design method to take this into account. The proposed controllers are derived using a newly developed design software that solves an IAE minimization problem with respect to H∞ robustness constraints on the sensitivity- and complementary sensitivity function. The software is shown to be fast, easy to use and robust in giving well-performing controllers. By extracting measurement noise from the process value of a real plant, one can estimate its effect on the control signal variance. The time constant of the low-pass filter, through which measurements are fed, is varied to design controllers with constrained control signal activity. By comparing control signal variance and IAE, the user is also able to weigh actuator wear to estimated performance. The proposed PID design method has shown to give very promising results both on simulated examples and real plants such as a recirculation flow process. Optimal Youla parametrized controllers are used both as a quality check of the designed PI and PID controllers and as a tool for determining when these are valid choices compared to more advanced controllers

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

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

Nowadays, liquid rocket engines use closed-loop control at most near steady operating conditions. The control of the transient phases is traditionally performed in open-loop due to highly nonlinear system dynamics. This situation is unsatisfactory, in particular for reusable engines. The open-loop control system cannot provide optimal engine performance due to external disturbances or the degeneration of engine components over time. In this paper, we study a deep reinforcement learning approach for optimal control of a generic gas-generator engine's continuous start-up phase. It is shown that the learned policy can reach different steady-state operating points and convincingly adapt to changing system parameters. A quantitative comparison with carefully tuned open-loop sequences and PID controllers is included. The deep reinforcement learning controller achieves the highest performance and requires only minimal computational effort to calculate the control action, which is a big advantage over approaches that require online optimization, such as model predictive control. control

Smith Predictor with Inverted Decoupling for Square Multivariable Time Delay Systems

Versión del autorThis paper presents a new methodology to design multivariable Smith predictor for n×n processes with multiple time delays based on the centralized inverted decoupling structure. The controller elements are calculated in order to achieve good reference tracking and decoupling response. Independently of the system size, very simple general expressions for the controller elements are obtained. The realizability conditions are provided and the particular case of processes with all of its elements as first order plus time delay systems is discussed in more detail. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response and to obtain a stable output prediction in unstable plants. The effectiveness of the method is illustrated through different simulation examples in comparison with other works

Handling packet dropouts and random delays for unstable delayed processes in NCS by optimal tuning of PIλDμ controllers with evolutionary algorithms

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The issues of stochastically varying network delays and packet dropouts in Networked Control System (NCS) applications have been simultaneously addressed by time domain optimal tuning of fractional order (FO) PID controllers. Different variants of evolutionary algorithms are used for the tuning process and their performances are compared. Also the effectiveness of the fractional order PI(λ)D(μ) controllers over their integer order counterparts is looked into. Two standard test bench plants with time delay and unstable poles which are encountered in process control applications are tuned with the proposed method to establish the validity of the tuning methodology. The proposed tuning methodology is independent of the specific choice of plant and is also applicable for less complicated systems. Thus it is useful in a wide variety of scenarios. The paper also shows the superiority of FOPID controllers over their conventional PID counterparts for NCS applications.This work has been supported by the Board of Research in Nuclear Sciences (BRNS) of the Department of Atomic Energy (DAE), India, sanction no. 2009/36/62-BRNS, dated November 2009

Further experimental results on modelling and algebraic control of a delayed looped heating-cooling process under uncertainties

The aim of this research is to revise and substantially extend experimental modelling and control of a looped heating-cooling laboratory process with long input-output and internal delays under uncertainties. This research follows and extends the authors' recent results. As several significant improvements regarding robust modelling and control have been reached, the obtained results are provided with a link and comparison to the previous findings. First, an infinite-dimensional model based on mathematical-physical heat and mass transfer principles is developed. All important heat-fluid transport and control-signal delays are considered when assembling the model structure and relations of quantities. Model parameter values optimization based on the measurement data follows. When determining static model parameter values, all variations in steady-state measured data are taken into account simultaneously, which enhances previously obtained models. Values of dynamic model parameters and delays are further obtained by least mean square optimization. This innovative model is compared to two recently developed process models and to the best-fit model that ignores the measured variations. Controller structures are designed using algebraic tools for all four models. The designed controllers are robust in the sense of robust stability and performance. Both concepts are rigorously assessed, and the obtained conditions serve for controller parameter tuning. Two different control systems are assumed: the standard closed-loop feedback loop and the two-feedback-controllers control system. Numerous experimental measurements for nominal conditions and selected perturbations are performed. Obtained results are further analyzed via several criteria on manipulated input and controlled temperature. The designed controllers are compared to the Smith predictor structure that is wellestablished for time-delay systems control. An essential drawback of the predictor regarding disturbance rejection is highlighted.College of Polytechnics Jihlava; National Foreign Expert Project, (G2022178023L); Tomas Bata University in Zlin, TBU; Grantová Agentura České Republiky, GA ČR, (GAČR 21–45465L)Czech Science Foundation [GAC?R 21-45465L]; National Foreign Expert Project [G2022178023L

Advanced tools for interactive design of simple controllers

Cílem této práce je návrh nástrojů pro identifikaci modelu reálného procesu, návrh robustního regulátoru pro procesy s neurčitostí, optimalizaci chování zpětnovazební smyčky v časové oblasti. V první části práce je vysvětlena část teorie řízení, která byla použita pro autorovo řešení. Autorův přístup je zaměřen na metodu ladění regulátorů pomocí robustních regionů stability pro PI regulátory, procesy s neurčitostí, množinový model a integrální kritéria optimality v časové oblasti. V druhé části práce je analyzovaný současný stav nástrojů pro návrh regulátorů a identifikaci procesů. Ve třetí části je popsána implementace identifikačního modulu, návrh robustního regulátoru pro procesy s neurčitostí a nástroj pro optimalizaci chování zpětnovazebné smyčky v časové oblasti pomocí integrálních kritérií. Je zde také představena metoda gradientní optimalizace. V závěrečné části této práce je ověřena funkčnost vyvinutých nástrojů na reálném systému.ObhájenoThe aim of this thesis is to develop tools for process model identification, robust controller design for processes with uncertainty, and closed-loop performance optimization in the time domain. In the first part, the control theory used in the author's approach is explained. The approach is focused on the controller tuning method using the robust stability regions for PI controllers, processes with uncertainty, the Model set approach, and the time domain integral criteria of optimality. In the second part, the state-of-the-art of the current controller design and process identification tools is analyzed. In the third part, the implementation of the identification module, robust controller design for processes with uncertainty, and a tool for closed-loop optimization in the time domain using the integral criteria is described. The gradient optimization method is shown here. In the final part, the functionality of the developed tools is validated on a real system