scholarly journals Simulated Real-Time Controller for Tuning Algorithm Using Modified Hill Climbing Approach Based on Model Reference Adaptive Control System

2020 ◽  
Author(s):  
Ahmed Abdulelah Ahmed ◽  
Azura Che Soh ◽  
Mohd Khair Hassan ◽  
Samsul Bahari Mohd Noor ◽  
Hafiz Rashidi Harun
Keyword(s):  
Adaptive Control ◽  
Real Time ◽  
Error Function ◽  
Model Reference Adaptive Control ◽  
Hill Climbing ◽  
System Response ◽  
Model Reference ◽  
Hill Climbing Algorithm ◽  
Processing Power ◽  
Model Reference Adaptive

In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated by comparing the system response with a desired reference response. The algorithm tests new solution candidates using step signals iteratively. The results showed the algorithm effectiveness to drive the system response. The simulation results illustrate that the method schemes proposed in this study show a viable and versatile solution to deal with controller tuning for systems with model inaccuracies as well as controller real-time calibration problem.

Model Reference Adaptive Motion Control Research of Servo Press

2014 ◽  
Vol 532 ◽  
pp. 212-217
Author(s):  
Juan Zhang ◽  
Xing Song Wang
Keyword(s):  
Adaptive Control ◽  
Real Time ◽  
Control Strategy ◽  
Pid Control ◽  
Position Control ◽  
Model Reference Adaptive Control ◽  
Model Reference ◽  
Servo Press ◽  
Adaptive Control Strategy ◽  
Model Reference Adaptive

Servo press is a new developing trend in forming equipment. In order to improve the position control accuracy, the movement rule of crank press slide block is analyzed. In view of the servo press poison PID control algorithm parameters cant realize real-time adjustment, model reference adaptive control strategy is presented, and a real-time control experiment platform is established in xPC target environment based on MATLAB RTW. The experiment results shows that the model reference adaptive control strategy is of higher accuracy and better robustness than the PID control strategy.

scholarly journals Robust Adaptive HCS MPPT Algorithm-Based Wind Generation System Using Model Reference Adaptive Control

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5187
Author(s):  
Ziyad A. Alrowaili ◽  
Mustafa M. Ali ◽  
Abdelraheem Youssef ◽  
Hossam H. H. Mousa ◽  
Ahmed S. Ali ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Model Reference Adaptive Control ◽  
Maximum Power ◽  
Hill Climbing ◽  
Step Size ◽  
Maximum Power Point ◽  
Model Reference ◽  
Power Fluctuations ◽  
Power Point ◽  
Model Reference Adaptive

To treat the stochastic wind nature, it is required to attain all available power from the wind energy conversion system (WECS). Therefore, several maximum power point tracking (MPPT) techniques are utilized. Among them, hill-climbing search (HCS) techniques are widely implemented owing to their various features. Regarding current HCS techniques, the rotor speed is mainly perturbed using predefined constants or objective functions, which makes the selection of step sizes a multifaceted task. These limitations are directly reflected in the overall dynamic WECS performance such as tracking speed, power fluctuations, and system efficiency. To deal with the challenges of the existing HCS techniques, this paper proposes a new adaptive HCS (AD-HCS) technique with self-adjustable step size using model reference adaptive control (MRAC) based on the PID controller. Firstly, the mechanical power fluctuations are detected, then the MRAC continuously optimizes the PID gains so as to generate an appropriate dynamic step size until harvesting the maximum power point (MPP) under the optimal tracking conditions. Looking specifically at the simulation results, the proposed AD-HCS technique exhibits low oscillations around the MPP and a small settling time. Moreover, WECS efficiency is increased by 5% and 2% compared to the conventional and recent HCS techniques, respectively. Finally, the studied system is confirmed over a 1.5 MW, gird-tied, double-fed induction generator (DFIG) WECS using MATLAB/Simulink.

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