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

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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

A classification of techniques for the compensation of time delayed processes. Part 2: Structurally optimised controllers

Following on from Part 1, Part 2 of the paper considers the use of structurally optimised controllers to compensate time delayed processes

DC motorun otomatik ayarlamalı PID ile hız kontrolünün gerçekleştirilmesi

Although advanced controllers are used in control applications, proportional-integral-derivative (PID) controllers are preferred in industry due to their simple structure and ease of application. However, it can difficult to set these controller parameters for the controlled platform. These parameters tuning with trial-error method leads to time and job loss, and the parameters determined in this way cannot provide a sufficiently efficient operating characteristic. In order to overcome this problem related to PID parameter tuning many automatic tuning methods have been developed. In this paper, the automatic tuning method proposed by Aström and Hagglund was applied to a DC motor speed control system. The DC motor speed control system was implemented in an interface designed on Laboratory Virtual Instrument Electronic Workbench (LabVIEW) environment and CompactRIO unit. The PID parameters obtained with trial-error and two types auto-tuning methods were tested in the DC motor control system and achieved results were compered. The results showed that performance of the PID controller tuned with LAbVIEW auto-tuning method is better than others.Kontrol uygulamalarında gelişmiş kontrolörler kullanılsa da PID (Proportional-Integral-Derivative) kontrolörler basit yapısından ve kolay uygulanabildiğinden dolayı endüstride tercih edilmektedir. Ancak kontrol edilecek platforma uygun PID parametrelerinin ayarlanması oldukça güç olabilmektedir. Bu parametrelerin deneme yanılma yöntemiyle ayarlanması zaman ve iş kaybına sebep olmakla birlikte bu yolla tespit edilen parametrelerle ayarlanan kontrolörler yeterince verimli bir çalışma karakteristiği sunmayabilmektedir. PID parametrelerinin ayarıyla ilgili bu sorunların üstesinden gelebilmek için çok sayıda otomatik ayar yöntemi geliştirilmiştir. Bu makalede Åström ve Hägglund tarafından önerilen otomatik ayar yöntemi bir DC motoru hız kontrol sistemine uygulanmıştır. Bu DC motor hız kontrol sistemi LabVIEW (Laboratory Virtual Instrument Electronic Workbench) ortamında geliştirilen ara yüz ve CompactRIO ünitesi üzerinde gerçekleştirilmiştir. Deneme yanılma ve iki farklı otomatik ayarlama yöntemiyle elde edilen PID parametreleri DC motor kontrol sistemi üzerinde denenmiş ve elde edilen sonuçlar karşılaştırılmıştır. Sonuçlar, LabVIEW otomatik ayarlama yöntemiyle elde edilen parametrelerle işletilen PID kontrolörün daha iyi performans gösterdiğini göstermişti

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

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

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