Simple Robust Dead-Time Compensator for First-Order Plus Dead-Time Unstable Processes

2008 ◽  
Vol 47 (14) ◽  
pp. 4784-4790 ◽  
Author(s):  
Julio E. Normey-Rico ◽  
Eduardo. F. Camacho
2016 ◽  
Vol 136 (5) ◽  
pp. 676-682 ◽  
Author(s):  
Akihiro Ishimura ◽  
Masayoshi Nakamoto ◽  
Takuya Kinoshita ◽  
Toru Yamamoto

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1519
Author(s):  
Mikulas Huba ◽  
Pavol Bistak ◽  
Damir Vrancic ◽  
Katarina Zakova

The article reviews the results of a number of recent papers dealing with the revision of the simplest approaches to the control of first-order time-delayed systems. The concise introductory review is extended by an analysis of two discrete-time approaches to dead-time compensation control of stable, integrating, and unstable first-order dead-time processes including simple diagnostics of the model used and focusing on the possibility of simplified but reliable plant modelling. The first approach, based on the first historically known dead-time compensator (DTC) with possible dead-beat performance, is based on the reconstruction of the actual process variables and the compensation of input disturbances by an extended state observer (ESO). Such solutions play an important role both in a disturbance observer (DOB) based control and in an active disturbance rejection control (ADRC). The second approach considered comes from the Smith predictor with two degrees of freedom, which combines feedforward control with output disturbance reconstruction and compensation by the parallel plant model. It is shown that these two approaches offer advantageous properties in the case of actuator limitations, in contrast to the commonly used PID controllers. However, when applied to integrating and unstable first-order systems, the unconstrained and possibly unobservable output disturbance signal of the second solution must be eliminated from the control loop, due to the hidden structural instability of the Smith predictor-like solutions. The modified solutions, usually referred to as filtered Smith predictor (FSP), then no longer provide a disturbance signal and thus no longer fully fit into the concept of Industry 4.0, which is focused on further optimization, predictive maintenance in dynamic systems, diagnosis, fault detection and fault identification of dynamic processes and forms the basis for the digitalization of smart production. Nevertheless, the detailed analysis of the elimination of the unstable disturbance response mode is also worth mentioning in terms of other possible solutions. The application of both approaches to the control of a thermal process shows almost equivalent quality, but with different dependencies on the tuning parameters used. It is confirmed that a more detailed identification of the controlled process and the resulting higher complexity of the control algorithms does not necessarily lead to an increase in the resulting quality of the transients, which underlines the importance of the simplified plant modelling for practice.


2018 ◽  
Vol 7 (4) ◽  
pp. 2800
Author(s):  
Avani Kirit Mehta ◽  
R. Swarnalatha

Dead-time is common to real time processes and occurs when the process variable doesn’t acknowledge to any changes in the set point. Existence of dead time in the systems poses a challenge to control and stabilize, especially in a control feedback loop. Padé approximation provides a determinate approximation of the dead time in the continuous process systems, which can be utilized in the further simulations of equivalent First Order plus Dead Time Models. However, the standard Padé approximation with the same numerator- denominator derivative power, exhibits a jolt at time t=0. This gives an inaccurate approximation of the dead time. To avoid this phenomenon, increasing orders of Padé approximation is applied. In the following manuscript, equivalent First Order plus Dead-Time models of two blending systems of orders four and seven are analysed for the same. As the orders of the Padé approximation increases, the accuracy of the response also increases. The oscillations are increased on a much smaller scale rather than having one big dip in the negative region (as observed in the first few orders of Padé approximation), and the approximation tries to synchronize with the desired response curve in the positive region. All the simulations are done in MATLAB.  


10.5772/19258 ◽  
2011 ◽  
Author(s):  
Dennis Brandao ◽  
Nunzio Torrisi ◽  
Renato F. Fernandes Jr

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