Adaptive PD networks tracking control with full-state constraints for redundant parallel manipulators

Nguyen, Van‐Truong; Lin, Chia Ching; Su, Shun‐Feng; Nguyen, Ngoc-Quan; Tran, Quoc‐Viet

doi:10.1109/ifsa-scis.2017.8023289

Cited by 10 publications

(4 citation statements)

References 11 publications

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“…where θ l (t) ∈ R n and θ r (t) ∈ R n are respectively left and right antennae for searching the optimal joint angle by the beetle, R(•) : R n → R n denotes the searching limit function, θ(t) ∈ R n denotes the current joint angle of the redundant manipulator at time instant t, λ(t) ∈ R denotes the antenna length/distance of the beetle as the exploration parameter, and b ∈ R n denotes the randomly-generated searching direction Initially generate δ(t) and λ(t) according to (12) and (13) 6for i <= n do ii) Compute antennaes θ l (t) ∈ R n and θ r (t) ∈ R n with b according to formulas (8) and (9) 9iii) Make θ l (t) and θ r (t) within the exploration limit based on 1010 iv) Calculate the fitness of the antennaes using 711 v) Determine the position of the ith beetle using (11) and standardize it into the allowed space with (10)…”

Section: A Generating Searching Antennae For Beetle In Joint Spacementioning

confidence: 99%

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Cheng

et al. 2020

IEEE Access

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Redundant manipulators play important roles in many industrial and service applications by assisting people fulfill heavy and repetitive jobs. However, redundant manipulators are coupled highlynonlinear systems which exert difficulty of redundancy resolution computation. Conventional methods such as pseudo-inverse-based approaches obtain the resolved joint angles from joint velocity level, which may bring about more computational cost and may neglect joint velocity limits. In this work, a motion planning method based on beetle antennae search algorithm (BAS) is proposed for motion planning of redundant manipulators with the variable joint velocity limit. Such proposed work does not need to resolve the velocity kinematics equation as the conventional methods do, and the proposed method can directly deal with the forward kinematics equation to resolve the desired joint angles. The simulation and experiment on the five-link planar manipulator and the Kuka industrial manipulator system demonstrate the efficiency of the proposed method for motion planning of redundant manipulator, and reveal the reliable performance of the BAS algorithm as compared with genetic algorithm (GA), particle swarm optimization (PSO), firefly algorithm(FA) and quantum behaved particle swarm algorithm(QPSO) methods.

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Section: A Generating Searching Antennae For Beetle In Joint Spacementioning

confidence: 99%

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Cheng

et al. 2020

IEEE Access

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“…A neural network-based motor control system has a high ability to address the system's structure uncertainty and disturbance, but it takes more computer power and data storage space [45]. Even for uncertain nonlinear systems, fuzzy control theory usually provides nonlinear controllers capable of performing many sophisticated nonlinear control actions [46]. Unlike traditional control design, an FLC does not necessitate accurate knowledge of the system model, such as the system transfer function's poles and zeroes.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

Shamseldin

2022

Journal of Robotics and Control

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This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID).

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“…Parallel manipulators have potential advantages, such as high stiffness, accuracy, high overload driven capability, and so on. In the era of industry 4.0, they are widely used in robotic hands, machine tools, high precision, haptic display, micro-mechanisms, and so on [1]. Unfortunately, parallel manipulators face many complex uncertainties caused by unknown dynamic model, external disturbances, and nonlinear frictions forces.…”

Section: Introductionmentioning

confidence: 99%

Adaptive finite‐time neural network control for redundant parallel manipulators

Nguyen

Wang

et al. 2019

Asian Journal of Control

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This paper reports our study of an adaptive finite-time neural network control scheme for redundant parallel manipulators. The proposed controller is based on fully tuned radial basis function neural networks (RBFNs), nonsingular fast terminal sliding mode control (NFTSMC), and nonlinearities in output feedback. RBFNs with a fully online update on the output weights and both the centers and variances of Gaussian functions are used to estimate system uncertainties and disturbances. The proposed approach possesses several advantages over other existing approaches like robustness, rapid response, nonsingularity, higher precision, finite-time convergence, and better tracking control performance. The stability of the parallel manipulators is ensured by the Lyapunov theory. Finally, simulation results validate the effectiveness of the proposed methodology.

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Adaptive PD networks tracking control with full-state constraints for redundant parallel manipulators

Cited by 10 publications

References 11 publications

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

Adaptive finite‐time neural network control for redundant parallel manipulators

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