Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm Optimization

This paper endeavors to contribute to the field of optimal control via presenting an optimal fuzzy Proportional Derivative (PD) controller for a RPP (Revolute-Prismatic-Prismatic) robot manipulator based on particle swarm optimization and inverse dynamics. The Denavit-Hartenberg approach and the Jacobi method for each of the arms of the robot are employed in order to gain the kinematic equations of the manipulator. Furthermore, the Lagrange method is utilized to obtain the dynamic equations of motion. Hence, in order to control the dynamics of the robot manipulator, inverse dynamics and a fuzzy PD controller optimized via particle swarm optimization are used in this research study. The obtained results of the optimal fuzzy PD controller based on the inverse dynamics are compared to the outcomes of the PD controller, and it is illustrated that the optimal fuzzy PD controller shows better controlling performance in comparison with other controllers.

[1]  M. Tomizuka,et al.  Constrained Iterative Learning Control with PSO-Youla Feedback Tuning for Building Temperature Control * *This work was supported by the National Foundation of Research (NRF) of Singapore and China Scholarship Council (CSC) Scholarship. , 2017 .

[2]  F. Khoshahval,et al.  Performance evaluation of PSO and GA in PWR core loading pattern optimization , 2011 .

[3]  Shital S. Chiddarwar,et al.  Novel integrated offline trajectory generation approach for robot assisted spray painting operation , 2015 .

[4]  Jamshid Dehmeshki,et al.  An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System , 2012, IEEE Transactions on Fuzzy Systems.

[5]  Magdalene Marinaki,et al.  Fuzzy control optimized by PSO for vibration suppression of beams , 2010 .

[6]  Manukid Parnichkun,et al.  Position control of a pneumatic surgical robot using PSO based 2-DOF H∞ loop shaping structured controller , 2017 .

[7]  Vivekananda Mukherjee,et al.  MPP detection of a partially shaded PV array by continuous GA and hybrid PSO , 2015 .

[8]  Raynald Guilbault,et al.  Formula derived from particle swarm optimization (PSO) for optimum design of cylindrical roller profile under EHL regime , 2015 .

[9]  Debashisha Jena,et al.  PSO based neuro fuzzy sliding mode control for a robot manipulator , 2017 .

[10]  Amir Rezaei,et al.  An interval-valued fuzzy controller for complex dynamical systems with application to a 3-PSP parallel robot , 2014, Fuzzy Sets Syst..

[11]  Martin Pfurner.  Closed form inverse kinematics solution for a redundant anthropomorphic robot arm , 2016, Comput. Aided Geom. Des..

[12]  Zafer Bingul,et al.  A Fuzzy Logic Controller tuned with PSO for 2 DOF robot trajectory control , 2011, Expert Syst. Appl..

[13]  L F Xie,et al.  PD plus error-dependent integral nonlinear controllers for robot manipulators with an uncertain Jacobian matrix. , 2012, ISA transactions.

[14]  Héctor Pomares,et al.  Multiobjective Optimization and Comparison of Nonsingleton Type-1 and Singleton Interval Type-2 Fuzzy Logic Systems , 2013, IEEE Transactions on Fuzzy Systems.

[15]  Mounir Ayadi,et al.  PID-type fuzzy logic controller tuning based on particle swarm optimization , 2012, Eng. Appl. Artif. Intell..

[16]  Ken Chen,et al.  Base position optimization for mobile painting robot manipulators with multiple constraints , 2018, Robotics and Computer-Integrated Manufacturing.

[18]  Hanlei Wang,et al.  Adaptive inverse dynamics control of robots with uncertain kinematics and dynamics , 2009, Autom..

[19]  Abdullah Al Mamun,et al.  PSO-Optimized Fuzzy Logic Controller for a Single Wheel Robot , 2010, FIRA RoboWorld Congress.

[20]  Yogesh Singh,et al.  Inverse dynamics and robust sliding mode control of a planar parallel (2-PRP and 1-PPR) robot augmented with a nonlinear disturbance observer , 2015 .

[21]  Yoshiaki Shirai,et al.  Dynamic analysis of a needle insertion for soft materials: Arbitrary Lagrangian-Eulerian-based three-dimensional finite element analysis , 2014, Comput. Biol. Medicine.

[22]  Uthman A. Baroudi,et al.  A Behavioral Adaptive Fuzzy controller of multi robots in a cluster space , 2016, Appl. Soft Comput..

[23]  H. Asada,et al.  Inverse Dynamics of Flexible Robots; Modeling and Recursive Computation Using Virtual Rigid Link Coordinate Systems , 1989, 1989 American Control Conference.

[24]  Hüseyin Canbolat,et al.  Simulation of a SCARA robot with PD and learning controllers , 2008, Simul. Model. Pract. Theory.

[25]  Oscar Castillo,et al.  Type-1 and Type-2 fuzzy logic controller design using a Hybrid PSO-GA optimization method , 2014, Inf. Sci..

[26]  Chien-Lung Chan,et al.  A cautious PSO with conditional random , 2015, Expert Syst. Appl..

[27]  Jun Zhou,et al.  Position control of nonlinear hydraulic system using an improved PSO based PID controller , 2017 .

[28]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[29]  Weixing Chen,et al.  Kinematic accuracy research of a novel six-degree-of-freedom parallel robot with three legs , 2016 .

[30]  Jovitha Jerome,et al.  Adaptive PSO for optimal LQR tracking control of 2 DoF laboratory helicopter , 2016, Appl. Soft Comput..

[31]  H. Shayeghi,et al.  Multi-stage fuzzy load frequency control using PSO , 2008 .

[32]  P. D. Darade,et al.  Displacement Control of Photostrictive Actuators for Vibration Control with the Aid of Fuzzy Logic Control along with PSO Algorithm , 2017 .

[33]  Zhimei Chen,et al.  On PSO Based Fuzzy Neural Network Sliding Mode Control for Overhead Crane , 2011 .

[34]  P. Constantin.  Lagrangian-eulerian methods for uniqueness in hydrodynamic systems , 2014, 1812.00039.

[35]  M. A. Serna,et al.  Inverse dynamics of flexible robots , 1996 .

[36]  Stefan Staicu,et al.  Inverse dynamics of the 3-PRR planar parallel robot , 2009, Robotics Auton. Syst..

[37]  Soosan Beheshti,et al.  Particle swarm optimization based fuzzy gain scheduled subspace predictive control , 2018, Eng. Appl. Artif. Intell..

[38]  Jerry M. Mendel,et al.  Design of Novel Interval Type-2 Fuzzy Controllers for Modular and Reconfigurable Robots: Theory and Experiments , 2011, IEEE Transactions on Industrial Electronics.

[39]  Ahmad Bagheri,et al.  Optimal robust sliding mode tracking control of a biped robot based on ingenious multi-objective PSO , 2014, Neurocomputing.

[40]  A. Alimi,et al.  Inverse Kinematics Using Particle Swarm Optimization, A Statistical Analysis , 2013 .

[41]  S. Kahla,et al.  Fuzzy-PSO controller design for maximum power point tracking in photovoltaic system , 2017 .

[42]  Gregory S. Chirikjian,et al.  Workspace density and inverse kinematics for planar serial revolute manipulators , 2013 .

[43]  Antonio Morell,et al.  Solving the forward kinematics problem in parallel robots using Support Vector Regression , 2013, Eng. Appl. Artif. Intell..

[44]  Wei Zhang,et al.  Control strategy PSO , 2016, Appl. Soft Comput..

[45]  Chaoyi Zhang,et al.  An optimal PSO distributed precoding algorithm in QRD-based multi-relay system , 2013, Future Gener. Comput. Syst..

[46]  V. Jeyalakshmi,et al.  PSO-scaled fuzzy logic to load frequency control in hydrothermal power system , 2016, Soft Comput..

[47]  Dario Antonelli,et al.  Qualification of a Collaborative Human-robot Welding Cell☆ , 2016 .

[48]  Fernando Reyes,et al.  Polynomial family of PD-type controllers for robot manipulators , 2005 .

[49]  Panfeng Huang,et al.  Coupling dynamics modelling and optimal coordinated control of tethered space robot , 2015 .

[50]  Aria Alasty,et al.  Multi-variable control of chaos using PSO-based minimum entropy control , 2011 .

[51]  F. N. Hassan,et al.  Optimal PID control of a brushless DC motor using PSO and BF techniques , 2014 .

[52]  Claudio Melchiorri,et al.  Inverse Kinematics of Serial Manipulators in Cluttered Environments using a new Paradigm of Particle Swarm Optimization , 2014 .

[53]  Xianbo Xiang.  Coordinated 3D Path Following for Autonomous Underwater Vehicles Via Classic PID Controller , 2013, ICONS.

[54]  F. Chu,et al.  Chapter 7 – Kinematics with Four Points′ Cartesian Coordinates for Spatial Parallel Manipulator , 2014 .

[55]  Hazriq Izzuan Jaafar,et al.  Sliding Mode Controller Design with Optimized PID Sliding Surface Using Particle Swarm Algorithm , 2017 .

[56]  Javier Moreno-Valenzuela,et al.  Time-scale separation of a class of robust PD-type tracking controllers for robot manipulators. , 2013, ISA transactions.

[57]  A. Ghanbarzadeh,et al.  Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand est , 2010 .

[58]  Santhakumar Mohan,et al.  Inverse dynamics and control of a 3-DOF planar parallel (U-shaped 3-PPR) manipulator , 2015 .

[59]  Antonio Rodríguez Díaz,et al.  Optimization of Type-2 Fuzzy Logic Controllers Using PSO Applied to Linear Plants , 2011, Soft Computing for Intelligent Control and Mobile Robotics.

[60]  H. M. A. A. Al-Assadi,et al.  An adaptive-learning algorithm to solve the inverse kinematics problem of a 6 D.O.F serial robot manipulator , 2006, Adv. Eng. Softw..

[61]  Prashant K. Jamwal,et al.  Forward kinematics modelling of a parallel ankle rehabilitation robot using modified fuzzy inference , 2010 .

[62]  Qinqin Chai,et al.  A computational method for free terminal time optimal control problem governed by nonlinear time delayed systems , 2018 .

[63]  Xiao-Feng Liu,et al.  Dynamics analysis of flexible space robot with joint friction , 2015 .

[64]  Rafiq Ahmad,et al.  Safe and Automated Assembly Process using Vision Assisted Robot Manipulator , 2016 .