Pooyan Alinaghi Hosseinabadi

This paper presents a novel robust Fuzzy controller for a planar manipulator robot. Also, the Model Predictive Control (MPC) and PID techniques are used to compare the results with the proposed method. The control system of the manipulator robots must have some special features that guarantee stability, fast tracking, practicability of the control signals, smooth control, etc. A comparative analysis can provide a clearer picture of the control system’s performance. This study presents a comparative analysis between a novel robust Fuzzy technique, MPC and PID controllers for a two-link planar manipulator robot. Simulink/MATLAB is used for simulations of the controllers. The results show that the proposed robust Fuzzy method performs better and is more robust than other methods. The Integral of the Absolute value of the Error (IAE) and Integral of the Time Absolute value of the Error (ITAE) performance indexes are employed for a better and more logical comparison. Moreover, the control methods are compared with the essential control features such as accuracy, fast-tracking, robustness, etc. And in all the features, the proposed Fuzzy method is better than others.

One of the most critical problems in all practical systems is the presence of uncertainties, internal and external disturbances, as well as disturbing noise, which makes the control of the system a challenging task. Another challenge with the physical systems is the possibility of cyber-attacks that the system’s cyber security against them is a critical issue. The systems related to oil and gas industries may also be subjected to cyber-attacks. The subsets of these industries can be mentioned to the oil and gas transmission industry, where ships have a critical role. This paper uses the Quantitative Feedback Theory (QFT) method to design a robust controller for the ship course system, aiming towards desired trajectory tracking. The proposed controller is robust against all uncertainties, internal and external disturbances, noise, and various possible Deception, Stealth, and Denial-of-Service (DOS) attacks. The robust controller for the ship system is designed using the QFT method and the QFTCT toolbox in MATLAB software. Numerical simulations are performed in MATLAB/Simulink for two case studies with disturbances and attacks involving intermittent sinusoidal and random behavior to demonstrate the proposed controller.

The three-area power system is widely considered a suitable example to test load frequency control of the distributed generation system. In this article, for such a system, for the power stabilization task, we introduce two controllers: Linear Quadratic Regulator (LQR), which is model-based, and Fuzzy Logic Controller (FLC), which is data-based. The purpose is to compare the two approaches from the point of view of (i) ease of implementation and tuning, and (ii) robustness to changes in the model. The model, together with controls strategies, has been implemented in the MATLAB software. Then, it has been tested for different simulation scenarios, taking into account the disturbances and faulty tie-lines between areas. Various quality measures allow to compare the performance of each control strategy. The comparison in terms of parameter change and load disturbances prompt us to propose suitable metrics and advice notes on the application of each controller.