Validation of a multivariable relay-based PID autotuner with specified robustness

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The application of a new PID autotuning method for the steam/water loop in large scale ships

In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to improve the control performance of the steam/water loop, the application of a recently developed PID autotuning method is studied. Firstly, a 'forbidden region' on the Nyquist plane can be obtained based on user-defined performance requirements such as robustness or gain margin and phase margin. Secondly, the dynamic of the system can be obtained with a sine test around the operation point. Finally, the PID controller's parameters can be obtained by locating the frequency response of the controlled system at the edge of the 'forbidden region'. To verify the effectiveness of the new PID autotuning method, comparisons are presented with other PID autotuning methods, as well as the model predictive control. The results show the superiority of the new PID autotuning method

Universal direct tuner for loop control in industry

This paper introduces a direct universal (automatic) tuner for basic loop control in industrial applications. The direct feature refers to the fact that a first-hand model, such as a step response first-order plus dead time approximation, is not required. Instead, a point in the frequency domain and the corresponding slope of the loop frequency response is identified by single test suitable for industrial applications. The proposed method has been shown to overcome pitfalls found in other (automatic) tuning methods and has been validated in a wide range of common and exotic processes in simulation and experimental conditions. The method is very robust to noise, an important feature for real life industrial applications. Comparison is performed with other well-known methods, such as approximate M-constrained integral gain optimization (AMIGO) and Skogestad internal model controller (SIMC), which are indirect methods, i.e., they are based on a first-hand approximation of step response data. The results indicate great similarity between the results, whereas the direct method has the advantage of skipping this intermediate step of identification. The control structure is the most commonly used in industry, i.e., proportional-integral-derivative (PID) type. As the derivative action is often not used in industry due to its difficult choice, in the proposed method, we use a direct relation between the integral and derivative gains. This enables the user to have in the tuning structure the advantages of the derivative action, therefore much improving the potential of good performance in real life control applications

Robust fractional order PI control for cardiac output stabilisation

Drug regulatory paradigms are dependent on the hemodynamic system as it serves to distribute and clear the drug in/from the body. While focusing on the objective of the drug paradigm at hand, it is important to maintain stable hemodynamic variables. In this work, a biomedical application requiring robust control properties has been used to illustrate the potential of an autotuning method, referred to as the fractional order robust autotuner. The method is an extension of a previously presented autotuning principle and produces controllers which are robust to system gain variations. The feature of automatic tuning of controller parameters can be of great use for data-driven adaptation during intra-patient variability conditions. Fractional order PI/PD controllers are generalizations of the well-known PI/PD controllers that exhibit an extra parameter usually used to enhance the robustness of the closed loop system. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

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

A survey of recent advances in fractional order control for time delay systems

Several papers reviewing fractional order calculus in control applications have been published recently. These papers focus on general tuning procedures, especially for the fractional order proportional integral derivative controller. However, not all these tuning procedures are applicable to all kinds of processes, such as the delicate time delay systems. This motivates the need for synthesizing fractional order control applications, problems, and advances completely dedicated to time delay processes. The purpose of this paper is to provide a state of the art that can be easily used as a basis to familiarize oneself with fractional order tuning strategies targeted for time delayed processes. Solely, the most recent advances, dating from the last decade, are included in this review

PID controller tuning for a multivariable glass furnace process by genetic algorithm

Standard genetic algorithms (SGAs) are investigated to optimise discrete-time proportional-integral-derivative (PID) controller parameters, by three tuning approaches, for a multivariable glass furnace process with loop interaction. Initially, standard genetic algorithms (SGAs) are used to identify control oriented models of the plant which are subsequently used for controller optimisation. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction. © 2015 Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelber

Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

PID control architectures are widely used in industrial applications. Despite their low number of open parameters, tuning multiple, coupled PID controllers can become tedious in practice. In this paper, we extend PILCO, a model-based policy search framework, to automatically tune multivariate PID controllers purely based on data observed on an otherwise unknown system. The system's state is extended appropriately to frame the PID policy as a static state feedback policy. This renders PID tuning possible as the solution of a finite horizon optimal control problem without further a priori knowledge. The framework is applied to the task of balancing an inverted pendulum on a seven degree-of-freedom robotic arm, thereby demonstrating its capabilities of fast and data-efficient policy learning, even on complex real world problems.Comment: Accepted final version to appear in 2017 IEEE International Conference on Robotics and Automation (ICRA

Practical Evaluation of a Novel Multivariable Relay Autotuner with Short and Efficient Excitation

In this paper we propose an autotuning method that combines a setup for decentralized relay autotuning of two-input two-output systems with an identification method that uses short experiments to estimate up to second-ordertime-delayed systems. A small modification of the experiment gives better low-frequency excitation and improved models. The method is successfully demonstrated in simulations and on a quadruple tank process