The Experts below are selected from a list of 28551 Experts worldwide ranked by ideXlab platform
Thomas F Edgar - One of the best experts on this subject based on the ideXlab platform.
-
simple proportional integral Controller Tuning rules for foptd and hoptd models based on matching two asymptotes
Industrial & Engineering Chemistry Research, 2018Co-Authors: Jietae Lee, Yongjeh Lee, Dae Ryook Yang, Thomas F EdgarAbstract:Many methods are available to tune proportional integral (PI) Controllers for first order plus time delay (FOPTD) models of overdamped processes. The two asymptotes for small and large ratios of time delays over time constants are easily calculated. These two asymptotes can be used to evaluate and provide guidelines for the performance and application ranges of PI Controller Tuning rules. By matching these two asymptotes, a simple analytic Tuning rule is suggested. For some overdamped processes whose transfer functions have large zero terms, half-order plus time delay (HOPTD) models are found to yield better results than the FOPTD models. Applying the technique of matching two asymptotes, a simple analytic PI Controller Tuning rule has also been proposed for the HOPTD models. To apply these Tuning rules to high order processes with known transfer functions, model reduction methods to obtain the FOPTD and HOPTD models are investigated. Simulation results for empirical and full models of processes show the ...
-
simple analytic proportional integral derivative pid Controller Tuning rules for unstable processes
Industrial & Engineering Chemistry Research, 2014Co-Authors: Wonhui Cho, Jietae Lee, Thomas F EdgarAbstract:Very simple proportional-integral-derivative (PID) Controller Tuning rules for a wide range of stable processes are available. However, for unstable processes, the design trend is for Controllers to be more complex for better performances. Here, the design concept of “simplicity” is extended to unstable processes. Simple desired closed-loop transfer functions for the direct synthesis method and simple approximations of the process time delay are utilized for unstable processes. Very simple Tuning rules for PID Controllers and set-point filters are obtained, yielding similar or even improved performances over previous more complicated PID Controller Tuning methods.
-
simple analytic pid Controller Tuning rules revisited
Industrial & Engineering Chemistry Research, 2014Co-Authors: Jietae Lee, Wonhui Cho, Thomas F EdgarAbstract:The SIMC method by Skogestad (J. Process Control 2003, 13, 291–309) to tune the PID Controller is revisited, and a new method (K-SIMC) is proposed. The proposed K-SIMC method includes modifications of model reduction techniques and suggestions of new Tuning rules and set point filters. Effects of such modifications are illustrated through simulations for a wide variety of process models. The proposed modifications permit the SIMC method to be applied with more confidence.
-
multiloop pi Controller Tuning for interacting multivariable processes
Computers & Chemical Engineering, 1998Co-Authors: Thomas F EdgarAbstract:Abstract A trial-and-error method that is a variation of Ziegler–Nichols Tuning has been employed in the past for field Tuning of PID Controllers. This method is now extended for Tuning of multiloop PI Controllers. The Nyquist array method is refined to determine ultimate gains for multiloop Tuning. The proposed method is simple to use and simulation results show that it avoids sluggish responses and unbalanced responses between loops that occur with other Tuning methods such as BLT and sequential autoTuning.
Sunwon Park - One of the best experts on this subject based on the ideXlab platform.
-
pid Controller Tuning for integrating and unstable processes with time delay
Chemical Engineering Science, 2000Co-Authors: Yongho Lee, Jeong Seok Lee, Sunwon ParkAbstract:A new method for PID Controller Tuning based on process models for integrating and unstable processes with time delay is proposed in this paper. The proposed method is an extension of the PID Controller Tuning method by Lee, Lee, Park and Brosilow (1998) to general unstable and integrating processes with time delay. The proposed method is simpler to use because the proposed method is an explicit Tuning method compared with other frequency response methods. Closed-loop responses tuned by the proposed method are compared with those of existing methods. The results show that the proposed Tuning method gives better closed loop performance than the existing methods.
-
pid Controller Tuning to obtain desired closed loop responses for cascade control systems
IFAC Proceedings Volumes, 1998Co-Authors: Sunwon ParkAbstract:Abstract A new method for PID Controller Tuning based on process models for cascaded control systems is proposed in this paper. The method consists of first finding the ideal Controller that gives the desired closed loop response and then finding the PID approximation of the ideal Controller by Maclaurin series. This method can be applied to anv open loop stable processes. Furthermore, it enables us to tune the PID Controllers both for the inner-loop and the outer-loop simultaneously while existing Tuning methods tune the inner loop first and the outer loop next. Closed-loop responses or cascade control loops tuned by the proposed method are compared with those of existing methods such as the frequency response method and the ITAE method. The results show that the proposed Tuning method is superior to the existing methods.
-
pid Controller Tuning for desired closed loop responses for si so systems
Aiche Journal, 1998Co-Authors: Yongho Lee, Sunwon Park, Moonyong Lee, Coleman BrosilowAbstract:Proportional integral, and derivative (PID) parameters are obtained for general process models by approximating the feedback form of an IMC Controller with a Maclaurin series in the Laplace variable. These PID parameters yield closed-loop responses that are closer to the desired responses than those obtained by PID Controllers tuned by other methods. The improvement in closed-loop control performance becomes more prominent as the dead time of the process model increases. A new design method for two degree of freedom Controllers is also proposed. Such Controllers are essential for unstable processes and provide significantly improved dynamic performance over single degree of freedom Controllers for stable processes when the disturbances enter through the process.
Sigurd Skogestad - One of the best experts on this subject based on the ideXlab platform.
-
the simc method for smooth pid Controller Tuning
2012Co-Authors: Sigurd Skogestad, Chriss GrimholtAbstract:The SIMC method for PID Controller Tuning (Skogestad in J. Process. Control 13:291–309, 2003) has already found widespread industrial usage. This chapter gives an updated overview of the method, mainly from a user’s point of view. The basis for the SIMC method is a first-order plus time delay model, and we present a new effective method to obtain the model from a simple closed-loop experiment. An important advantage of the SIMC rule is that there is a single Tuning parameter (τ c ) that gives a good balance between the PID parameters (K c ,τ I ,τ D ) and can be adjusted to get a desired trade-off between performance (“tight” control) and robustness (“smooth” control). Compared to the original paper of Skogestad (J. Process. Control 13:291–309, 2003), the choice of the Tuning parameter τ c is discussed in more detail, and lower and upper limits are presented for tight and smooth Tuning, respectively. Finally, the optimality of the SIMC PI rules is studied by comparing the performance (IAE) versus robustness (M s ) trade-off with the Pareto-optimal curve. The difference is small, which leads to the conclusion that the SIMC rules are close to optimal. The only exception is for pure time delay processes, so we introduce the “improved” SIMC rule to improve the performance for this case.
-
on line pi Controller Tuning using closed loop setpoint response
IFAC Proceedings Volumes, 2010Co-Authors: M Shamsuzzoha, Sigurd Skogestad, Ivar J HalvorsenAbstract:The proposed method is similar to the Ziegler-Nichols (1942) Tuning method, but it is faster to use and does not require the system to approach instability with sustained oscillations. The method requires one closed-loop step setpoint response experiment using a proportional only Controller with gain Kc0 . Based on simulations for a range of first-order with delay processes, simple correlations have been derived to give PI Controller settings similar to those of the SIMC Tuning rules (Skogestad, 2003). The Controller gain (Kc/Kc0) is only a function of the overshoot observed in the setpoint experiment whereas the Controller integral time (τ I) is mainly a function of the time to reach the peak (t p). Importantly, the method includes a deTuning factor F that allows the user to adjust the final closed-loop response time and robustness. The proposed Tuning method, originally derived for first-order with delay processes, has been tested on a wide range of other processes typical for process control applications and the results are comparable with the SIMC Tunings using the open-loop model.
-
simple analytic rules for model reduction and pid Controller Tuning
Modeling Identification and Control, 2004Co-Authors: Sigurd SkogestadAbstract:The aim of this paper is to present analytic rules for PID Controller Tuning that are simple and still result in good closed-loop behavior. The starting point has been the IMC-PID Tuning rules that have achieved widespread industrial acceptance. The rule for the integral term has been modified to improve disturbance rejection for integrating processes. Furthermore, rather than deriving separate rules for each transfer function model, there is a just a single Tuning rule for a first-order or second-order time delay model. Simple analytic rules for model reduction are presented to obtain a model in this form, including the 'half rule' for obtaining the effective time delay.
-
simple analytic rules for model reduction and pid Controller Tuning
Journal of Process Control, 2003Co-Authors: Sigurd SkogestadAbstract:The aim of this paper is to present analytic rules for PID Controller Tuning that are simple and still result in good closed-loop behavior. The starting point has been the IMC-PID Tuning rules that have achieved widespread industrial acceptance. The rule for the integral term has been modified to improve disturbance rejection for integrating processes. Furthermore, rather than deriving separate rules for each transfer function model, there is a just a single Tuning rule for a first-order or second-order time delay model. Simple analytic rules for model reduction are presented to obtain a model in this form, including the ‘‘half rule’’ for obtaining the effective time delay. # 2002 Elsevier Science Ltd. All rights reserved.
Yongho Lee - One of the best experts on this subject based on the ideXlab platform.
-
pid Controller Tuning for integrating and unstable processes with time delay
Chemical Engineering Science, 2000Co-Authors: Yongho Lee, Jeong Seok Lee, Sunwon ParkAbstract:A new method for PID Controller Tuning based on process models for integrating and unstable processes with time delay is proposed in this paper. The proposed method is an extension of the PID Controller Tuning method by Lee, Lee, Park and Brosilow (1998) to general unstable and integrating processes with time delay. The proposed method is simpler to use because the proposed method is an explicit Tuning method compared with other frequency response methods. Closed-loop responses tuned by the proposed method are compared with those of existing methods. The results show that the proposed Tuning method gives better closed loop performance than the existing methods.
-
pid Controller Tuning for desired closed loop responses for si so systems
Aiche Journal, 1998Co-Authors: Yongho Lee, Sunwon Park, Moonyong Lee, Coleman BrosilowAbstract:Proportional integral, and derivative (PID) parameters are obtained for general process models by approximating the feedback form of an IMC Controller with a Maclaurin series in the Laplace variable. These PID parameters yield closed-loop responses that are closer to the desired responses than those obtained by PID Controllers tuned by other methods. The improvement in closed-loop control performance becomes more prominent as the dead time of the process model increases. A new design method for two degree of freedom Controllers is also proposed. Such Controllers are essential for unstable processes and provide significantly improved dynamic performance over single degree of freedom Controllers for stable processes when the disturbances enter through the process.
Gilberto Reynosomeza - One of the best experts on this subject based on the ideXlab platform.
-
evolutionary multi objective optimisation with preferences for multivariable pi Controller Tuning
Expert Systems With Applications, 2016Co-Authors: Gilberto Reynosomeza, J Sanchis, X Blasco, Roberto Zanetti FreireAbstract:We present an evolutionary multiobjective optimisation approach for PI Controller Tuning.This approach incorporates designer's preferences into the optimisation process.The methodology is evaluated in a multivariable process.It is possible to improve pertinency of the approximated Pareto front. Multi-objective optimisation design procedures have shown to be a valuable tool for control engineers. They enable the designer having a close embedment of the Tuning process for a wide variety of applications. In such procedures, evolutionary multi-objective optimisation has been extensively used for PI and PID Controller Tuning; one reason for this is due to their flexibility to include mechanisms in order to enhance convergence and diversity. Although its usability, when dealing with multi-variable processes, the resulting Pareto front approximation might not be useful, due to the number of design objectives stated. That is, a vast region of the objective space might be impractical or useless a priori, due to the strong degradation in some of the design objectives. In this paper preference handling techniques are incorporated into the optimisation process, seeking to improve the pertinency of the approximated Pareto front for multi-variable PI Controller Tuning. That is, the inclusion of preferences into the optimisation process, in order to seek actively for a pertinent Pareto front approximation. With such approach, it is possible to tune a multi-variable PI Controller, fulfilling several design objectives, using previous knowledge from the designer on the expected trade-off performance. This is validated with a well-known benchmark example in multi-variable control. Control tests show the usefulness of the proposed approach when compared with other Tuning techniques.
-
pid Controller Tuning for unstable processes using a multi objective optimisation design procedure
IFAC-PapersOnLine, 2016Co-Authors: Gilberto Reynosomeza, J Carrilloahumada, Yadira Boada, Jesus PicoAbstract:Abstract Multi-objective optimisation techniques have shown to be a useful tool for Controller Tuning applications. Such techniques are useful when: 1) it is difficult to find a Controller with a desirable trade-off between conflictive objectives; or 2) it is valuable to extract an additional knowledge from the process by analysing trade-off among possible Controllers. In this work, we propose a multi-objective optimisation design procedure for unstable process, using PID Controllers. The provided examples show the usability of the procedure for this kind of process, sometimes difficult to control; comparison with existing Tuning rule methods provide promising results for this Tuning procedure.
-
multiobjective evolutionary algorithms for multivariable pi Controller design
Expert Systems With Applications, 2012Co-Authors: Gilberto Reynosomeza, J Sanchis, X Blasco, J M HerreroAbstract:A multiobjective optimisation engineering design (MOED) methodology for PI Controller Tuning in multivariable processes is presented. The MOED procedure is a natural approach for facing multiobjective problems where several requirements and specifications need to be fulfilled. An algorithm based on the differential evolution technique and spherical pruning is used for this purpose. To evaluate the methodology, a multivariable control benchmark is used. The obtained results validate the MOED procedure as a practical and useful technique for parametric Controller Tuning in multivariable processes.