Design of Interval Type-2 Fractional-Order Fuzzy Logic Controller for Redundant Robot with Artificial Bee Colony

HIL co-simulation of an optimal hybrid fractional-order type-2 fuzzy PID regulator based on dSPACE for quadruple tank system

Accurate regulation of the liquid level in a quadruple tank system (QTS) is not easy and imposes higher requirements on control strategies, so the design of controllers in these systems is challenging due to the difficulty of dynamic analysis of its nonlinear characteristics and parametric uncertainties. To overcome these problems in liquid level regulation and increase the robustness to the pump coefficients, this article proposes and investigates the use of an optimal hybrid fractional-order type-2 fuzzy-PID (OH-FO-T2F-PID) regulator using a combination of two bio-inspired evolutionary optimizers, namely augmented grey wolf optimizer and cuckoo search optimizer, which gives rise to the new hybrid A-GWOCS algorithm. This control mechanism was chosen to facilitate the convergence of the water liquids in the two tanks as quickly as possible to the corresponding required values. In addition, a collaborative optimization technique with several objectives is used to adjust the regulator parameters. The capability and efficiency of the suggested regulator is first investigated through computer simulation results and then confirmed by real-time control experimental results on the QTS based on dSPACE 1104 computation engine. The findings showed that the suggested OH-FO-T2F-PID regulator significantly outperformed both the optimized ADRC and the OH-FO-T1F-PID regulators. Specifically, it reduced the rising time by 17.02% and 95.21%, respectively, and the settling time by 25.13% and 74.28%. Additionally, the designed OH-FO-T2F-PID regulator successfully eliminated the steady-state error and overshoot, enabling precise regulation of the QTS, and maintenance the liquid level at the desired set point under a wide range of working situations. The robustness of the recommended regulator is also studied by considering - 50% disturbance in the QTS parameters, and the findings showed that the OH-FO-T2F-PID regulator is less susceptible to variations in parameters.

Closed loop automated drug infusion regulation based on optimal 2-DOF TID control approach for the mean arterial blood pressure

This work aims to design an optimal controller for regulating mean arterial blood pressure (MAP) during the cardiac cycle in surgical and post-surgical conditions to enhance automated drug infusion. MAP controllers must address uncertainties like external disturbances, time-varying parameters, and noise. Thus, closed-loop control is essential to normalize MAP regardless of the patient's pharmacokinetics during surgery. A two-degree-of-freedom tilt integral derivative (2-DOF TID) controller, tuned by the Chernobyl Disaster Optimizer (CDO) algorithm, is proposed to dynamically adjust sodium nitroprusside (SNP) infusion rates in various conditions. The performance of this 2-DOF TID controller is compared with CDO-based PID, 2-DOF PID, and TID controllers. The results demonstrate the effectiveness and robustness of the proposed controller in achieving and maintaining MAP at 100 mmHg. All controllers are evaluated on different patient responses, including fixed and time-varying sensitivities, to SNP infusion, external disturbances, and noise. The study reveals which controller performs best in terms of overshoot, settling time, error, disturbance rejection, and anti-interference ability, confirming the 2-DOF TID controller as a strong candidate for automated drug infusion systems in clinical settings.

Seismic structural control using magneto-rheological dampers: A decentralized interval type-2 fractional-order fuzzy PID controller optimized based on energy concepts

In this paper, a combination of the interval type-2 fuzzy logic controller (IT2FLC) with the fractional-order proportional-integral-derivative (FOPID) controller, namely optimal interval type-2 fractional-order fuzzy proportional-integral-derivative controller (OIT2FOFPIDC), is developed for enhancing the seismic performance and robustness in seismic structural control applications. Based on the energy concepts, a decentralized framework of the OIT2FOFPIDC is proposed for easy and simple implementation in structures during earthquakes. For this purpose, a coot optimization algorithm (COA), as a powerful optimization algorithm, is also applied to adjust the membership functions (MFs), scaling factors, and the main controller parameters. Three controllers, namely optimal type-1 fuzzy proportional-integral-derivative controller (OT1FPIDC), optimal interval type-2 fuzzy proportional-integral-derivative controller (OIT2FPIDC), and optimal proportional-integral-derivative controller (OPIDC), are also proposed for comparison purposes. The seismic performances of the suggested controllers are examined with the evaluation of nine seismic performance indices and different ground accelerations in a 6-story smart structure equipped with two dampers. The robustness of the four controllers in the presence of the stiffness uncertainties is also compared in this study. On average, a reduction of 25.0%, 18.8%, and 18.5% in peak displacement, inter-story drift, and acceleration of stories is obtained for the OIT2FOFPIDC over the OT1FPIDC, respectively. Similarly, these reductions in comparison with the OIT2FPIDC are 16.3%, 13.3%, and 12.0%. Also, these reductions, in comparison with the OPIDC, are 33.3%, 27.8%, and 25.8%. Furthermore, simulation results show that the OIT2FOFPIDC is more robust than the other proposed controllers against uncertainties due to structural stiffness.