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

Self-tuning run-time reconfigurable PID controller

Digital PID control algorithm is one of the most commonly used algorithms in the control systems area. This algorithm is very well known, it is simple, easily implementable in the computer control systems and most of all its operation is very predictable. Thus PID control has got well known impact on the control system behavior. However, in its simple form the controller have no reconfiguration support. In a case of the controlled system substantial changes (or the whole control environment, in the wider aspect, for example if the disturbances characteristics would change) it is not possible to make the PID controller robust enough. In this paper a new structure of digital PID controller is proposed, where the policy-based computing is used to equip the controller with the ability to adjust it's behavior according to the environmental changes. Application to the electro-oil evaporator which is a part of distillation installation is used to show the new controller structure in operation

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

An Adaptive PPI Controller

Processes with long dead times are among the most difficult to control. This has urged the development of controllers that cope with this kind of delays. A possible approach is to use a model predictive controller, i.e. a controller with an internal model of the process and its dead time. In ABB’s new control system, Control IT, there exists such a controller, namely the PPI controller. PPI stands for Predictive PI, and as the name indicates it shares some of its features with the common PI controller. The system contains an auto-tuner that is able to detect long dead times and to design a PPI controller. Another feature of Control IT is adaptive control. An adaptive controller has the ability to change its parameters in order to optimize its performance. Today, there is no adaptation mechanism for the PPI controller. This thesis investigates the possibilities of an adaptive version of the PPI controller. A test version has been implemented and simulation results show that there are processes that would benefit from an adaptive PPI. The big flaw is however that adaptation is possible only at set point changes, an event that might not be that common in industry. This implies that industrial studies must be performed before the solution is included in the final product. Other problems that have been encountered are sensitivity to noise and ramped set point changes. It has also been shown that the existing auto-tuner sometimes chooses a PPI design in cases were a PID design would be more useful. The thesis further discusses the subject of switching controller structure while in adaptation mod

Robust controller design: Recent emerging concepts for control of mechatronic systems

The recent industrial revolution puts competitive requirements on most manufacturing and mechatronic processes. Some of these are economic driven, but most of them have an intrinsic projection on the loop performance achieved in most of closed loops across the various process layers. It turns out that successful operation in a globalization context can only be ensured by robust tuning of controller parameter as an effective way to deal with continuously changing end-user specs and raw product properties. Still, ease of communication in non-specialised process engineering vocabulary must be ensured at all times and ease of implementation on already existing platforms is preferred. Specifications as settling time, overshoot and robustness have a direct meaning in terms of process output and remain most popular amongst process engineers. An intuitive tuning procedure for robustness is based on linear system tools such as frequency response and bandlimited specifications thereof. Loop shaping remains a mature and easy to use methodology, although its tools such as Hinf remain in the shadow of classical PID control for industrial applications. Recently, next to these popular loop shaping methods, new tools have emerged, i.e. fractional order controller tuning rules. The key feature of the latter group is an intrinsic robustness to variations in the gain, time delay and time constant values, hence ideally suited for loop shaping purpose. In this paper, both methods are sketched and discussed in terms of their advantages and disadvantages. A real life control application used in mechatronic applications illustrates the proposed claims. The results support the claim that fractional order controllers outperform in terms of versatility the Hinf control, without losing the generality of conclusions. The paper pleads towards the use of the emerging tools as they are now ready for broader use, while providing the reader with a good perspective of their potential

Binary Distillation Column Control Techniques: a Comparative Study

The purpose of this study is to propose the best control strategy for the binary distillation column. Woods & Berry model is used to represent the distillation column process. The control process is simulated on Matlab Simulink. Traditional controller settings including P, PI and PID are put to comparison. PI is found to result in a control superior to P and PID. PI is then tuned using different tuning method including Ziegler Nichols, Cohen Coon, ITAE, IMC and Symmetric Optimum. The study finds that IMC tuning parameters relatively improves the PI controller response and robustness. It is suggested to compare IMC-tuned PI controller with an advance Model Predicative Controller to ultimately conclude a superior control technique for the binary distillation column