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Fed-batch fermentation processes are commonly used in bioprocessing industry. A
fed-batch fermentation process often exhibits integrating/unstable type of dynamics
with multiple right-half plane zeros. A class of fourth-order integrating model can be
used to adequately represent such a complex dynamics of the fed-batch fermentation
process. In this...
Citations
... where R is a setpoint, E is an error, C is a controller output, Di is an input disturbance, Do is an output disturbance, Y is output or controlled variable, Gc is a controller transfer function or sub-system and Gp is a process transfer function or sub-system. The closed-loop characteristic equation is expressible by a general characteristics polynomial equation [31,32] (Equation (6)): ...
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.
... using platinum and gamma-alumina as the medium activation energy is at 37.1 J/mol. The bimetallic catalyst activation energy was reported at 23.9 J/mol using Platinum and nickel with activated carbon as the catalyst medium [9]. Both catalysts for monometallic and bimetallic were observed and it shows that the superiority of the catalyst favours the bimetallic. ...
Sulfur-Iodine Thermochemical cycle (SITC) process can be broken down into 3 sections. Based on the literature, there is limited study on the third section which is hydrogen iodide (HI) decomposition. In this work, a study to develop a model and controller of the HI decomposition is carried out. The goal of this work is to address this important gap, and more specifically to focus on the controllability of the HI decomposition section. Before the control and simulation study can be performed, a dynamic model of a HI decomposer is first established to obtain the baseline for the necessary data to be fed into the Artificial Neural Network for training to predict the correct outcome accordingly. The proposed controller is a Multi-Scale Control (MSC) integrated into an Artificial Neural Network (ANN) model (ANN-MSC-based-PID). It is worth highlighting that; the proposed model-based control strategy has proven to effectively control the HI decomposition reactor.
... Interesting approach of PID controller tuning using dominant pole placement is presented in Zítek & Fišer (2018) and Mandić et al. (2017). Seer & Nandong (2019) calculated the stability region of controller parameters for the fourth-order integrating nonminimum-phase systems, while Novella-Rodriquez et al. (2019) deal with the stability problem of delayed systems with two unstable poles. The optimal tuning process of PID and fractional order PID controllers using modern intelligent optimization algorithms can be found in Bingul & Karahan, 2018b). ...
This paper presents a new optimization method for PID controller cascaded with a lead-lag compensator (PIDC). Parameters of PIDC controller are obtained by solving the constrained optimization problem. We propose two variants of optimality criterion. First one is defined through the max-min optimization problem wherein objective function is the amplitude frequency response of the PIDC controller. Second one is based on an effective approximation of the minimum value of the amplitude frequency response of PIDC controller. Consequently, the resulting max optimization problem is defined as simplified setup of the first one criterion to obtain computationally less expensive problem. Both variants of optimality criterion result in efficient load disturbance rejection evaluated by the Integrated Absolute Error (IAE). Robustness is ensured by constraining the value of the maximum sensitivity Ms, while efficient noise rejection is guaranteed by the desired value of the sensitivity to measurement noise Mn. Good reference shaping is supported with proper constraints based on the Amplitude Optimum (AO) principle. Numerous batches of processes typically encountered in the industry are used to demonstrate the effectiveness of the proposed design method.
... high-frequency noise are involved because of the noise sensitivity introduced by the derivative part [6], [7]. Therefore, conventional PI controllers are inadequate to be employed in a delayed environment, high-frequency noise, and other uncertainty systems [8]- [10]. In such environments, if the PI controllers are used, the system will lead to oscillatory and unstable response because of the limited gain constant [11], [12]. ...
In most of the industrial process plants, PI/PID controllers have been widely used because of its simple design, easy tuning, and operational advantages. However, the performance of these controllers degrades for the processes with long dead-time and variation in set-point. Up next, a PPI controller is designed based on the Smith predictor to handle dead-time processes by compensation technique, but it failed to achieve adequate performance in the presence of external noise, large disturbances, and higher-order systems. Furthermore, the model-based controllers structure is complex in nature and requires the exact model of the process with more tunable parameters. Therefore, in this research, a fractional-order predictive PI controller has been proposed for dead-time processes with added filtering abilities. The controller uses the dead-time compensation characteristics of the Smith predictor and the fractional-order controller's robustness nature. For the high peak overshoot, external noise, and disturbance problems, a new set-point and noise filtering technique is proposed, and later it is compared with different conventional methods. In servo and regulatory operations, the proposed controller and filtering techniques produced optimal performance. Multiple real-time industrial process models are simulated with long dead-time to evaluate the proposed technique's flexibility, set-point tracking, disturbance rejection, signal smoothing, and dead-time compensation capabilities.
... high-frequency noise are involved because of the noise sensitivity introduced by the derivative part [6], [7]. Therefore, conventional PI controllers are inadequate to be employed in a delayed environment, high-frequency noise, and other uncertainty systems [8]- [10]. In such environments, if the PI controllers are used, the system will lead to oscillatory and unstable response because of the limited gain constant [11], [12]. ...
... Bolstered bunch aging procedures are ordinarily utilized in the bioprocessing industry. A class of fourth-arrange incorporating model can be utilized to enough speak to such unpredictable elements of the fed-cluster aging procedure, numerous modern procedures and other mechanical frameworks include elements [2]. Endeavors towards getting low-arrange models from high-degree frameworks are identified with the points of determining stable lessened request models from stable unique ones and guaranteeing that the diminished request show matches comparable qualities of unique higher request system [3]. ...
Genetic algorithm (GA) based PID (proportional integral derivative) controller has been proposed for tuning advanced PID parameters in a Reduced-Order of Rotational Mechanical System utilizing a weighted blend of target capacities, to be specific, integral square error (ISE), integral absolute error (IAE), and integrated time absolute error (ITAE). Some classical control methods like (PID) using Ziegler-Nichols strategy, Linear-Quadratic Regulator (LQR) are also implemented for comparison. The problem here, reducing the large scale model of mechanical system and controlling by using optimal approach (GA). The results show that the GA based PID controller tuned with settled PID parameters gives acceptable execution regarding set point following when compared with classical PID and LQR.
... Shi Min Lim et al., Int. J. of Integrated Engineering Vol. 12 No. 2 (2020) p.[19][20][21][22][23][24][25][26][27][28][29] ...
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.
Aim
A robust and advanced controller for pH monitoring and control is necessary in industrial processes inorder to treat the effluents to protect the flora and fauna in the environment. Advanced controllers such as fractional controllers could be used for effective control with increased accuracy and reliability.
Materials and Methods
This study includes a comparison of conventional controllers with advanced fractional order controllers to improve the performance of pH control in effluents from the industrial plants.
Results
A fractional order predictive proportional integral (FOPPI) controller for effective control of pH was designed and simulated. This controller includes the advantages of a smith predictor for dead time compensation and the robustness of a fractional order controller. The presented method shows an improvement in control performance in terms of rise time (32 s), settling time (140 s), lesser oscillations (2%), and lesser integral of the absolute error of 171.
Conclusion
FOPPI provides efficient control of pH in all regions of the titration curve and can be used for the control of pH in industrial waste water.
It is known that the key indicators of batch processes are controlled by conventional proportional–integral–derivative (PID) strategies from the view of one‐dimensional (1D) framework. Under such conditions, the information among batches cannot be used sufficiently; meanwhile, the repetitive disturbances also cannot be handled well. In order to deal with such situations, a novel two‐dimensional PID controller optimized by two‐dimensional model predictive iterative learning control (2D‐PID‐MPILC) is proposed. The contributions of this paper can be summarized as follows. First, a novel two‐dimensional PID (2D‐PID) controller is developed by combining the advantages of a PID‐type iterative learning control (PIDILC) strategy and the conventional PID method. This novel 2D‐PID controller overcomes the aforementioned disadvantages and extends the conventional PID algorithm from one‐dimension to two‐dimensions. Second, the tuning guidelines of the presented 2D‐PID controller are obtained from the two‐dimensional model predictive control iterative control (2D‐MPILC) method. Thus, the proposed approach inherits the advantages of both PID control, PIDILC strategy, and 2D‐MPILC scheme. The superiority of the proposed method is verified by the case study on the injection modelling process.
