A novel cascaded fractional fuzzy approach for control of fermentation process.

In this work, a cascaded control strategy based on fractional-order fuzzy PD/PI (FOFPD/PI) is proposed for temperature control of the bioreactor. The FOFPI is used to control the ethanol concentration in the inner loop, while the FOFPD is used for temperature control of the bioreactor in the outer loop. The integer order fuzzy PD/PI (IOFPD/PI), 2DOF FOPID, 2DOF PID, and PID are also designed for comparison purposes. The design parameter of FOFPD/PI and IOFPD/PI are estimated using non-dominated sorting genetic algorithm II (NSGA-II). Results revealed that the proposed cascaded control scheme reduced the IAE by 33.5 %, 40.5%, 47%, and 64% compared to IOFPD/PI, 2DOF FOPID, 2DOF PID, and PID, respectively. Hence, it can be concluded that the proposed FOFPD/PI controller provides precise control of reactor temperature in different operating conditions compared to other controllers.

Modified fractional order IMC design based drug scheduling for cancer treatment.

This paper aims to improve chemotherapy drug(s) scheduling of the drug dose injected into a patient. The existing practice has been established on experiments performed during the drug development process. In general, chemotherapeutic drugs are highly toxic in nature and directly affect the probability of a patient's survival. Therefore, a modified fractional order internal model control (MFOIMC) scheme with a minimal number of design parameters is proposed for effective drug scheduling. The proposed control scheme is a combination of fractional calculus and IMC. The fractional order IMC (FOIMC) is modified by incorporating an extra control loop with a proportional transfer function. Further, IPD and IMC control techniques are also designed for comparative analysis. The dragon fly algorithm (DA) is employed to optimize the parameters of the controller. Results show that the proposed control scheme provides a continuous and precise chemotherapeutic drug dose to the patient on a daily basis. It is also shown that MFOIMC improves IAE by 34% and 32% in comparison to IMC and FOIMC, respectively, which proves its superiority over other controllers.

Two degree of freedom PID based inferential control of continuous bioreactor for ethanol production.

This article presents the development of inferential control scheme based on Adaptive linear neural network (ADALINE) soft sensor for the control of fermentation process. The ethanol concentration of bioreactor is estimated from temperature profile of the process using soft sensor. The prediction accuracy of ADALINE is enhanced by retraining it with immediate past measurements. The ADALINE and retrained ADALINE are used along with PID and 2-DOF-PID leading to APID, A2PID, RAPID and RA2PID inferential controllers. Further the parameters of 2-DOF-PID are optimized using Non-dominated sorted genetic algorithm-II and used with retrained ADALINE soft sensor which leads to RAN2PID inferential controller. Simulation results demonstrate that performance of proposed RAN2PID controller is better in comparison to other designed controllers in terms of qualitative and quantitative performance indices.