Improved temperature control of a batch reactor with actuation constraints

Identification and Autotuning of Temperature-Control System With Application to Injection Molding

“…To demonstrate identification robustness in the presence of measurement noise, random noise of , causing , as used by Panda and Yu [27], is added to the process-output measurement, which is then used for the relay feedback. Based on the averaging for five oscillation periods in the time interval of [10,50] s, the limit-cycle data are computed as , and . Accordingly, the proposed algorithm yields the process model, , indicating improved identification robustness as compared to that of Panda and Yu [27].…”

“…Consider the high-order integrating process studied in [28] Based on the process step-response data, Ingimundarson and Hägglund [28] gave an FOPDT model, . Using the measured data in the time interval of [10,30] s of the unity step response, the proposed identification method composed of (4), (5), (6), and 7gives a SOPDT model, . For comparison, by letting , the proposed algorithm can also be used to obtain an FOPDT model, .…”

“…An iterative-learning-control scheme was proposed in [9] to guarantee temperature uniformity during system operation. Valigi et al [10] and Shahrokhi and Nejati [11] discussed some implementation constraints in temperature control design. Grassi and Tsakalis [12] proposed a frequency loop-shaping method for controller tuning to accommodate for such implementational constraints.…”

Fuzzy Temperature Control in a Batch Polymerization Reactor Using ANFIS Method

“…Therefore, there is an increasing awareness of the need for practical approaches to aid engineers to better understand and perform complex modeling and control tasks [17]. Incorporating actuation constraints is a brilliant idea that can be observed in few works like [18]. In the present work, we tried to develop a practicable controller by taking some practical constraints into account.…”