Double-Loop Multi-Scale Control using Routh-Hurwitz Dimensionless Parameter Tuning for MIMO Processes

This paper presents a new approach to controlling MIMO processes by using the double-loop multi-scale control scheme in the decentralized control architecture. The decentralized PID control system has been used in process industry despite its several limitations due to process interactions, time-delays and right half plane poles. To overcome the performance limitation due to process interactions, decoupling controllers are often added to the decentralized PID control system. The proposed strategy based on the double-loop multi-scale control scheme has some advantages over the existing control strategies for MIMO processes. An advantage of the proposed scheme over the decentralized PID control with decoupling system is that, the proposed strategy has a fixed number of dimensionless tuning parameters that are easy to tune. For an n×n MIMO process, the proposed scheme requires the tuning of only 3 to 6 dimensionless parameters instead of the 3n original PID parameters

Inter-Communicative Decentralized Multi-Scale Control (ICD-MSC) Scheme: A new approach to overcome MIMO process interactions

Decentralized PID control has been extensively used in process industry due to its functional simplicity. But designing an effective decentralized PID control system is very challenging because of process interactions and dead times, which often impose limitations on control performance. In practice, to alleviate the detrimental effect of process interactions on control performance, decoupling controllers are often incorporated into a decentralized control scheme. In many cases, these conventional decoupling controllers are not physically realizable or too complex for practical implementation. In this paper, we propose an alternative scheme to overcome the performance limitation imposed by process interactions. This new control scheme is extended from the SISO multi-scale control scheme previously developed for nonminimum-phase processes. The salient feature of the new control scheme lies in its communicative structure enabling collaborative communication among all the sub-controllers in the system. This communicative structure serves the purpose of reducing the detrimental effect of process interactions leading to improved control performance and performance robustness. Extensive numerical study shows that the new control scheme is able to outperform some existing decentralized control schemes augmented with traditional decoupling controllers

Multi-Scale Control: Improved Technique to Overcome Time-Delay Limitation

This paper presents a general multi-scale control scheme which can be used to control processes with significant time-delays. The salient feature of the multi-scale control scheme is to decompose a given plant into a sum of basic factors or modes. An individual sub-controller is specifically designed to control each of the plant modes and subsequently, an overall multi-scale controller is synthesized via combining all of the sub-controllers in a manner to enhance cooperation among these different plant modes. Numerical examples show that the multi-scale control scheme can provide improved performance and robustness over the conventional single-loop PID and Smith predictor schemes

Generalized multi-scale control scheme for cascade processes with time-delays

The cascade control is a well-known technique in process industry to improve regulatory control performance. The use of the conventional PI/PID controllers has often been found to be ineffective for cascade processes with long time-delays. Recent literature report has shown that the multi-scale control (MSC) scheme is capable of providing improved performance over the conventional PID controllers for processes characterized by long time-delays as well as slow RHP zeros. This paper presents an extension of this basic MSC scheme to cascade processes with long time-delays. This new cascade MSC scheme is applicable to self-regulating, integrating and unstable processes. Extensive numerical studies demonstrate the effectiveness of the cascade MSC scheme compared with some well-established cascade control strategies

Advanced PID Controller Synthesis using Multiscale Control Scheme

For many decades, PID controller has been widely applied in industries despite the advancement in many advanced control techniques. Process models such as the First-Order plus Deadtime (FOPDT) has often been used to design or tune PID controller. Numerous PID tuning formulas have been established since the well-known Ziegler-Nichols formula introduced in the 1940s. In this paper, we present the multi-scale control approach to constructing a PID tuning formula based on the FOPDT model. The effectiveness of the proposed PID tuning formula is compared with some of the existing formulas reported in the literature

PCA-based Method of Identification of Dominant Variables for Partial Control

Since the early use of automatic control, the Partial Control strategy has frequently been adopted in complex chemical processes having more process variables than manipulated variables. The key idea of Partial Control is to find the dominant variables which can be controlled to constant setpoints and in turn leads to acceptable variations in the operating objectives in the face of external disturbances occurrence. Although the idea seems simple to understand, the identification of the dominant variables can be a daunting task where presently this is largely done based on extensive process knowledge and experience. In this paper, we present a novel methodology to identify the dominant variables based on Principal Component Analysis. The method can greatly facilitate the implementation of Partial Control strategy because it does not require extensive process experience and knowledge. The effectiveness of the methodology is demonstrated based on its application to a complex extractive fermentation process

Multi-scale models for the optimization of batch bioreactors

Process models play an important role in the bioreactor design, optimisation and control. In previous work, the bioreactor models have mainly been developed by considering the microbial kinetics and the reactor environmental conditions with the assumption that the ideal mixing occurs inside the reactor. This assumption is relatively difficult to meet in the practical applications. In this paper, we propose a new approach to the bioreactor modelling by expanding the so-called Herbert’s Microbial Kinetics (HMK) model so that the developed models are able to incorporate the mixing effects via the inclusion of the aeration rate and stirrer speed into the microbial kinetics. The expanded models of Herbert’s microbial kinetics allow us to optimize the bioreactor’s performances with respects to the aeration rate and stirrer speed as the decision variables, where this optimisation is not possible using the original HMK model of microbial kinetics. Simulation and experimental studies on a batch ethanolic fermentation demonstrates the use of the expanded HMK models for the optimisation of bioreactor’s performances. It is shown that the integration of the expanded HMK model with the Computational Fluid Dynamics (CFD) model of mixing, which we call it as a Kinetics Multi-Scale (KMS) model, is able to predict the experimental values of yield and productivity of the batch fermentation process accurately (with less than 5% errors)

Effect of Mixing on a Lab-Scale Bioreactor Productivity

In this paper, we study the impact of variable mixing conditions arising from the different sets of aeration rate and stirrer speed on the ethanolic fermentation process, which utilizes the hydrolyzed cassava starch as carbon source. Interestingly, over the ranges of aeration rate and stirrer speed used in the study, the ethanol yield varied from 10% to 85% of theoretical maximum yield. Additionally over these experimental conditions, the selectivity of ethanol over glycerol varied from 3.6 to 12.3. One conclusion that can be drawn from this experimental study is that, the large variations in yield, selectivity and ethanol formation rate were more likely due to the different mixing conditions resulting from different values of aeration rate and stirrer speed, and less likely due to glucose and growth rates as previously reported

Modelling of carbon dioxide absorption into aqueous ammonia solution in a wetted wall column

© 2015 Universiti Putra Malaysia Press. In this paper, a mathematical model is developed based on mass and momentum balance for carbon dioxide absorption into aqueous ammonia solution. The model is simplified based on the assumption that the CO2 absorption into aqueous ammonia is a pseudo-first-order reaction. Laplace transform method is applied in order to solve the partial differential model equation. Finally, the CO2 molar flux is expressedas a function of partial pressure of CO2, concentration of aqueous ammonia, temperature and gas-liquidcontact area. Variation of CO2 molar flux with partial pressure of CO2 and temperature is discussedand a comparison is performed with experimental data from literature. Variation of CO2 molar flux isalso shown with gas-liquid contact area. The calculated flux from the model follows the same trend asthat of the experimental data reported in literature and the accuracy is within the accepted limit. The mathematical model is very helpful to predict the CO2 molar flux as a function of partial pressure of CO2, concentration of aqueous ammonia, temperature and gas-liquid contact area

Biohydrogen production: A new controllability criterion for analyzing the impacts of dark fermentation conditions

Biohydrogen production from renewable resources using dark fermentation has become an increasingly attractive solution in sustainable global energy supply. So far, there has been no report on the controllability analysis of biohydrogen production using dark fermentation. Process controllability is a crucial factor determining process feasibility. This paper presents a new criterion for assessing biohydrogen process controllability based on PI control. It proposes the critical loop gain derived via Routh stability analysis as a measure of process controllability. Results show that the dark fermentation using the bacteria from anaerobic dairy sludge and substrate source from sugarcane vinasse can lead to a highly controllable process with a critical loop gain value of 4.3. For the two other cases, an increase of substrate concentration from 10 g/L to 40 g/L substantially reduces the controllability. The proposed controllability criterion is easily adopted to assess the process feasibilty based on experimental data