scholarly journals Optimization pitch angle controller of rocket system using improved differential evolution algorithm

2017 ◽  
Vol 3 (1) ◽  
pp. 27 ◽  
Author(s):  
Dwi Lastomo ◽  
Herlambang Setiadi ◽  
Muhammad Ruswandi Djalal
Keyword(s):  
Differential Evolution ◽  
Pitch Angle ◽  
Pid Controller ◽  
Mimo System ◽  
Differential Evolution Algorithm ◽  
Evolution Algorithm ◽  
Robust Control Design ◽  
Improved Differential Evolution Algorithm ◽  
System Time ◽  
Rocket System

Pitch angle of rocket system is the important parts of the rocket. This part corresponds to the movement of the rocket system. Rocket system is fell into multi-input and multi-output (MIMO) system. The most challenge factor in MIMO system is designing the controller, if the design is not appropriate, it may lead to the unstable condition. Hence, appropriate and robust control design is inevitable. This paper introduces PID controller as pitch angle control of rocket system. Furthermore, PID controller parameter is optimized using improved differential evolution algorithm (IDEA). To analyze the performance of rocket system, time domain simulation is implemented. From the simulation result, it is found by using PID controller based on IDEA, the performance of pitch angle of rocket system is enhanced.

Fractional Active Disturbance Rejection Controller Based on Improved Differential Evolution Algorithm

2021 ◽  
Author(s):  
Henghui Liang ◽  
Wei Yu ◽  
Rui Chen ◽  
Ying Luo
Keyword(s):  
Differential Evolution ◽  
Fractional Order ◽  
Disturbance Rejection ◽  
Differential Evolution Algorithm ◽  
Order Information ◽  
Fractional Order Systems ◽  
Control Performance ◽  
Active Disturbance Rejection ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm

Abstract Although the active disturbance rejection controller can obtain good control performance without relying on specific model information, it targets integer-order systems. Fractional-order characteristics are commonly existed in practical systems. For fractional-order systems, it is more targeted to use the order information of the fractional-order model to design the active disturbance rejection controller, so as to obtain better control performance. A fractional active disturbance rejection controller composed of FOESO and FOPID (IDE-FOPID-FOESO) is proposed in this paper. The fractional-order extended state observer (FOESO) is designed based on the order information and the nonlinear state error feedback is replaced by the fractional-order PID controller (FOPID) whose parameters are obtained by the improved differential evolution algorithm (IDE). For IDE algorithm, the basis vector is randomly selected from the optimal individual population in the mutation strategy, and the scaling factor and cross-probability factor are adaptively adjusted according to the information of the successfully mutated individual in the search process to improve the exploration and mining capabilities of the algorithm. The simulation results show that the IDE algorithm can obtain the better parameters of FOPID faster compared with traditional DE algorithm and the IDE-FOPID-FOESO controller can be better applied to fractional-order systems with better control performance.

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

2020 ◽  
Vol 13 (3) ◽  
pp. 384-395
Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li
Keyword(s):  
Differential Evolution ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Bee Colony ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Dynamic Economic Dispatch ◽  
Integrated Power System

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

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