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An Application of STM32F4-Embedded ANFIS-Fuzzy Controller for Tower Crane Nguyen, Ngoc-Truong-Son; Dang, Quang-Hai; Nguyen, Dang-Khang; Lam, Duc-Quan; Nguyen, Vo-Hoai-Nam; Le, Nguyen-Phap-Tri; Tran, Nguyen-Khang; Bui, Van-The-Hieu; Nguyen, Thai-Hoa; Le, ThiHongLam
Journal of Fuzzy Systems and Control Vol. 2 No. 3 (2024): Vol. 2, No. 3, 2024
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v2i3.260

Abstract

In this paper, we examine tower crane – a MIMO under-actuated system- which is popular in both academia and industry. From a successful PID controller for this model, we design a fuzzy controller that is generated by the ANFIS toolbox from MATLAB. The proposed controller is shown to be viable based on both the simulation and experimental results obtained. In experiments, the angle of load vibrates a maximum of 10 degrees around the set angle and the settling error is a maximum of 1 degree. Also, the settling time of the trolley is a maximum of 12 sec. These results are acceptable. This control method controls positions and decreases the fluctuation of this model. In the hardware platform, STM32F4 Discovery is used as a control board, and it is well-embedded by fuzzy blocks to prove its ability in future intelligent control.
Application of Genetic Algorithm for Optimizing Continuous and Discrete PID to Control Antenna Azimuth Position Nguyen, Binh-Hau; Cao, Hoang-Thanh-Tuan; Nguyen, Thai-Toan; Pham, Minh-Duc; Pham, Van-Thuan-Em; Nguyen, Tuan-Anh; Ho, Van-Nguyen; Ngo, Gia-Dat; Tran, Dinh-Nam-Phat; Le, Thanh-Dat; Phan, Cong-Duc-Quyen; Le, Van-Khai; Le, ThiHongLam
Journal of Fuzzy Systems and Control Vol. 2 No. 1 (2024): Vol. 2, No. 1, 2024
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v2i1.154

Abstract

In the paper, we introduce a continuous and discrete PID optimization method by using genetic algorithm (GA) to analyze and control antenna position – a typical model in control engineering. From analizing kinematic equations of this model, we propose continuous and discrete PID controllers to stabilize it. The control result in the case of the empirically selected K matrix (Kp, Ki, Kd) is compared to the case of the K matrix optimized by GA. From this, we can compare the system's output response with the above continuous and discrete PID controllers. The results show that continuously and discrete optimized PID controllers by GA are better than PIC controllers from empirical test through simulation.
Modeling and Optimal Control for Two-Wheeled Self-Balancing Robot Do, Quoc-Thinh; Tran, Van-Thanh; Ngo, Minh-Thai; Tran, Minh-Quan; Thiem, Quan-Linh; Nguyen, Hoang-Son; Pham, Ba-Khoi; Phan, Nguyen-Phuoc-An; Nguyen, Duy-Hieu; Nguyen, Duc-Hoc; Nguyen, Van-Hoc; Tran, Ho-Minh-Quang; Le, ThiHongLam
Journal of Fuzzy Systems and Control Vol. 2 No. 1 (2024): Vol. 2, No. 1, 2024
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v2i1.162

Abstract

The two-wheeled self-balancing robot based on an inverted pendulum model is a nonlinear object with uncertain parameters that are difficult to control with 6 state variables. This is a multiple input-multiple output (MIMO) under-actuated system that is very complex and causes many challenges for the operator. This paper analyzed the mathematical equation of a two-wheeled self-balancing robot vehicle system. Then, the Linear Quadratic Regulator (LQR) control is applied to the system through simulation on Matlab/Simulink and experiment. The results show that the LQR algorithm has been successfully applied in many moving cases.