Particle Swarm Optimization aided PID gait controller design for a humanoid robot

Kashyap, Abhishek; Parhi, Dayal R.

doi:10.1016/j.isatra.2020.12.033

Cited by 69 publications

(27 citation statements)

References 48 publications

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“…The OA provides an effective solution for this issue in various control applications for conventional methods [61,62]. The solution process of the OA ensures the determination of the optimal global solutions for complex optimization models [63][64][65][66][67][68][69]. The use of statistical tests was investigated in [70] for comparing swarm and evolutionary computing algorithms.…”

Section: Optimization Algorithms-based Optimality 21 Overviewmentioning

confidence: 99%

Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-Operative Optimization Algorithm

et al. 2021

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The tracking of a predefined trajectory with less error, system-settling time, system, and overshoot is the main challenge with the robot-manipulator controller. In this regard, this paper introduces a new design for the robot-manipulator controller based on a recently developed algorithm named the butterfly optimization algorithm (BOA). The proposed BOA utilizes the neighboring butterflies’ co-operation by sharing their knowledge in order to tackle the issue of trapping at the local optima and enhance the global search. Furthermore, the BOA requires few adjustable parameters via other optimization algorithms for the optimal design of the robot-manipulator controller. The BOA is combined with a developed figure of demerit fitness function in order to improve the trajectory tracking, which is specified by the simultaneous minimization of the response steady-state error, settling time, and overshoot by the robot manipulator. Various test scenarios are created to confirm the performance of the BOA-based robot manipulator to track different trajectories, including linear and nonlinear manners. Besides, the proposed algorithm can provide a maximum overshoot and settling time of less than 1.8101% and 0.1138 s, respectively, for the robot’s response compared to other optimization algorithms in the literature. The results emphasize the capability of the BOA-based robot manipulator to provide the best performance compared to the other techniques.

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Section: Optimization Algorithms-based Optimality 21 Overviewmentioning

confidence: 99%

Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-Operative Optimization Algorithm

et al. 2021

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“…In order to get better performance from any controller, its parameters need good optimization. Various optimization algorithms are widely used in industrial control systems, such as genetic algorithms, ant colony algorithms, bacteria foraging optimization algorithms, intelligent crow search algorithms, and particle swarm algorithms [34][35][36][37]. Du et al [36] used PSO optimization algorithms for power-sharing hybrid electric vehicle energy management strategies.…”

Section: Introductionmentioning

confidence: 99%

“…Du et al [36] used PSO optimization algorithms for power-sharing hybrid electric vehicle energy management strategies. Kashyap and Parhi [37] used a particle swarm algorithm to rectify a conventional PID controller to achieve the humanoid robot gait stability. Elsisi et al [38] proposed a new optimization algorithm, named the mayfly optimization algorithm (MOA), to find the optimal parameters of the proportional integral derivative (PID) controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations.…”

Section: Introductionmentioning

confidence: 99%

Multiparameter Control Strategy and Method for Cutting Arm of Roadheader

Wang

Yang

et al. 2021

Shock and Vibration

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A multiparameter control strategy and method for the cutting arm of a roadheader is proposed through the operation analysis of roadheader. The method can address the problems of low intelligence and low cutting efficiency faced by the roadheader in the cutting process. The control strategy is divided into two parts: the cutting load identification part and the swing speed control part. The former part is designed using a backpropagation neural network that is optimized by an improved particle swarm optimization algorithm. The latter part is optimally designed using a fuzzy PID controller with improved simulated annealing particle swarm optimization. The simulation analysis in SIMULINK showed that the response time was reduced, proving the robustness of the method. In addition, experimental studies verified the good control effect of the method under different cutting states. The proposed method uses multiparameter to intelligently change the swing speed, providing a theoretical and practical basis for the realization of intelligent and unmanned cutting of roadheader.

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“…PID control proposed by many researchers because Due to its simplicity and ease of implementation. Abhishek and Dayal presented PID controller optimized by Particle Swarm Optimization (PSO) to stabilize the gait humanoid robot [2]. Ignacio proposed design an adaptive PID controller based reinforcement learning [3].…”

Section: Introductionmentioning

confidence: 99%

Robust Computed Torque Control for Uncertain Robotic Manipulators

Ahmed¹,

Mary²,

Jasim³

2021

alkej

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This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem. The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.

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Particle Swarm Optimization aided PID gait controller design for a humanoid robot

Cited by 69 publications

References 48 publications

Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-Operative Optimization Algorithm

Improvement of Trajectory Tracking by Robot Manipulator Based on a New Co-Operative Optimization Algorithm

Multiparameter Control Strategy and Method for Cutting Arm of Roadheader

Robust Computed Torque Control for Uncertain Robotic Manipulators

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