Robotic excavator trajectory control using an improved GA based PID controller

Feng, Hao; Yin, Chenbo; Weng, Wen-wen; Ma, Wei; Zhou, Jie; Jia, Wenhua; Zhang, Zili

doi:10.1016/j.ymssp.2017.12.014

Cited by 113 publications

(48 citation statements)

References 29 publications

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“…The reasons for the wide use of pID control are simple structure, robustness, and easy application. The optimal parameters of pID control have a very important effect on the system where the control is applied 15 . The control signal according to the pID control method can be calculated as in Eqn.…”

Section: Walking Pattern Of the Quadruped Robotmentioning

confidence: 99%

Shooting Control Application from a Quadruped Robot with a Weapon System via Sliding mode Control Method

2020

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With the developing technological process, it is expected that the usage of robots will increase in defense systems as in every field. One of the main objectives of the robotic studies for the defense industry is to capture the targeted success under all kinds of disruptive effects with robotic systems and to present this technology to the service of the army. A weapon system with a single degree of freedom was placed on a quadruped robot. System’s dynamic behavior, which has 12 degrees of freedom and planar movements, is modeled mathematically. Simulations of the shots made to the fixed targets were carried out during the walking of the quadruped robot. The gun barrel stabilization was realized to achieve accurate shots under disruptive effects. The sliding-mode control method was used to perform the barrel stabilisation. In this study, it is shown that a quadruped robot with a weapon system can perform successful shots against fixed targets. MATLAB is used for simulations and the results are shown with figures, graphics, and tables.

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Section: Walking Pattern Of the Quadruped Robotmentioning

confidence: 99%

Shooting Control Application from a Quadruped Robot with a Weapon System via Sliding mode Control Method

2020

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“…There are two ways that can be used to tune the PID parameters adaptively. One is Lyapunov-based adaptive PID control [44][45][46][47], and the other is the self-tuning PID control based on minimizing the tracking error [49][50][51]. In the first method, the PID parameters are considered as the adaptive parameters of the controller.…”

Section: Introductionmentioning

confidence: 99%

Parameter Self-Tuning PID Control for Greenhouse Climate Control Problem

2020

IEEE Access

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The difficulty of the greenhouse climate control is the great uncertainties of the weather and greenhouse climate. Although many control approaches have been proposed to solve this problem, the structures of the controllers are usually complex, and the reliability of the controllers is usually not good in practice. Therefore, to improve the reliability of the controllers, this paper proposes a parameter self-tuning PID control approach (STPID). In this PID control scheme, three environmental outputs including the inside temperature, humidity and CO 2 concentration are firstly transformed into four equivalent unit outputs, and the equivalent outputs are controlled by four PID controllers respectively. Thus, each PID controller and the corresponding equivalent output construct a single closed-loop system, and the original system can be decoupled. To ensure the desired control performance, the Levenberg-Marquart (LM) algorithm is introduced to tune the PID parameters. Based on the real weather data, a simulation was performed to illustrate the effectiveness of the proposed method, and a comparison study was done to observe the performance of the proposed method. The results indicate that control performance is good.

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“…However, tuning of the PID gains to adapt with the change of working conditions is difficult and depending In recent times, in order to deal with this problem, some optimization techniques such as artificial neural network (ANN), ant colony optimization (ACO), etc., have been applied to optimize the PID parameters. In [17], an genetic algorithm (GA) is used to determine the PID gains for trajectory tracking control of robotic excavator. The presented scheme gave the good performances in comparison with some given methods.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Controller Design for Excavator Arm

Vu¹

2020

IJMERR

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This paper presents a robust adaptive controller that does not depend on the system parameters for an excavator arm. Firstly, the model of the excavator arm is demonstrated in the Euler-Lagrange form considering with overall excavator system. Next, a robust adaptive controller has been constructed from information of state error. In this paper, the stability of overall system is mathematically proven by using Lyapunov stability theory. Also, the proposed controller is model free then the closed loop system is not affected by disturbances and uncertainties. Finally, the simulation is executed in Matlab/Simulink for both presented scheme and the PD controller under some conditions to ensure that the proposed algorithm given the good performances for all cases.

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Robotic excavator trajectory control using an improved GA based PID controller

Cited by 113 publications

References 29 publications

Shooting Control Application from a Quadruped Robot with a Weapon System via Sliding mode Control Method

Shooting Control Application from a Quadruped Robot with a Weapon System via Sliding mode Control Method

Parameter Self-Tuning PID Control for Greenhouse Climate Control Problem

Robust Adaptive Controller Design for Excavator Arm

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