Optimization in the Design and Control of Robotic Manipulators: A Survey

1989 ◽  
Vol 42 (4) ◽  
pp. 117-128 ◽  
Author(s):  
S. S. Rao ◽  
P. K. Bhatti
Keyword(s):  
Optimal Control ◽  
Robot Manipulator ◽  
Research Effort ◽  
Industrial Robot ◽  
Load Capacity ◽  
Robotic Manipulators ◽  
Optimization Techniques ◽  
Highly Nonlinear ◽  
Manipulator Design ◽  
And Control

Robotics is a relatively new and evolving technology being applied to manufacturing automation and is fast replacing the special-purpose machines or hard automation as it is often called. Demands for higher productivity, better and uniform quality products, and better working environments are primary reasons for its development. An industrial robot is a multifunctional and computer-controlled mechanical manipulator exhibiting a complex and highly nonlinear behavior. Even though most current robots have anthropomorphic configurations, they have far inferior manipulating abilities compared to humans. A great deal of research effort is presently being directed toward improving their overall performance by using optimal mechanical structures and control strategies. The optimal design of robot manipulators can include kinematic performance characteristics such as workspace, accuracy, repeatability, and redundancy. The static load capacity as well as dynamic criteria such as generalized inertia ellipsoid, dynamic manipulability, and vibratory response have also been considered in the design stages. The optimal control problems typically involve trajectory planning, time-optimal control, energy-optimal control, and mixed-optimal control. The constraints in a robot manipulator design problem usually involve link stresses, actuator torques, elastic deformation of links, and collision avoidance. This paper presents a review of the literature on the issues of optimum design and control of robotic manipulators and also the various optimization techniques currently available for application to robotics.

Integrated Model Of Industrial Robot For Control Applications

1992 ◽  
pp. 27-41
Author(s):  
Johari Halim Shah Osman
Keyword(s):  
Robot Manipulator ◽  
Industrial Robot ◽  
Realistic Model ◽  
Integrated Model ◽  
Control Synthesis ◽  
Real Situation ◽  
Highly Nonlinear ◽  
Gear Trains ◽  
And Control ◽  
Space Description

This paper deals with the development of an intergrated mathematical model of a robot manipulator. The model of the system comprises the mechanical part of the robot as well as the actuators and the gear trains. Two different approaches of deriving the integrated model are presented which results in two different forms of the integrated dynamic model of the robot manipulator in state space description. Both types of the integrated model are highly nonlinear, time varying, and represent a more realistic model of the robotic system. The integrated model and the approach are useful and suitable for dynamic analysis and control synthesis purposes, and will provide a more efficient approach to the real situation.

Experimental Validation of a Dynamic Model (Equivalent Rigid Link System) on a Single-Link Flexible Manipulator

1989 ◽  
Vol 111 (4) ◽  
pp. 667-672 ◽  
Author(s):  
R. P. Petroka ◽  
Liang-Wey Chang
Keyword(s):  
Dynamic Model ◽  
Robot Manipulator ◽  
Flexible Manipulator ◽  
Flexible Manipulators ◽  
Rigid Link ◽  
Future Design ◽  
Single Link ◽  
Manipulator Design ◽  
And Control ◽  
Improved Accuracy

Flexibility effects on robot manipulator design and control are typically ignored which is justified when large, bulky robotic mechanisms are moved at slow speeds. However, when increased speed and improved accuracy are desired in robot system performance it is necessary to consider flexible manipulators. This paper simulates the motion of a single-link, flexible manipulator using the Equivalent Rigid Link System (ERLS) dynamic model and experimentally validates the computer simulation results. Validation of the flexible manipulator dynamic model is necessary to ensure confidence of the model for use in future design and control applications of flexible manipulators.

Optimal, Model-Based Design of Soft Robotic Manipulators

2007 ◽  
Author(s):  
Deepak Trivedi ◽  
Dustin Dienno ◽  
Christopher D. Rahn
Keyword(s):  
Nonlinear Models ◽  
Load Capacity ◽  
Robotic Manipulators ◽  
Maximum Pressure ◽  
Cluttered Environments ◽  
Rod Theory ◽  
Cosserat Rod ◽  
Manipulator Design ◽  
Air Muscle ◽  
Muscle Actuators

Soft robotic manipulators, unlike their rigid-linked counterparts, deform continuously along their lengths similar to elephant trunks and octopus arms. Their excellent dexterity enables them to navigate through unstructured and cluttered environments and handle fragile objects using whole arm manipulation. Soft robotic manipulator design involves the specification of air muscle actuators and the number, length and configuration of sections that maximize dexterity and load capacity for a given maximum actuation pressure. This paper uses nonlinear models of the actuators and arm structure to optimally design soft robotic manipulators. The manipulator model is based on Cosserat rod theory, accounts for large curvatures, extensions, and shear strains, and is coupled to nonlinear Mooney-Rivlin actuator model. Given a dexterity constraint for each section, a genetic algorithm-based optimizer maximizes the arm load capacity by varying the actuator and section dimensions. The method generates design rules that simplify the optimization process. These rules are then applied to the design of pneumatically and hydraulically actuated soft robotic manipulators, using 100 psi and 1000 psi maximum pressure, respectively.

INTELLIGENT OPTIMAL CONTROL OF ROBOTIC MANIPULATORS USING WAVELETS

2008 ◽  
Vol 06 (04) ◽  
pp. 575-592 ◽  
Author(s):  
A. KARAMI ◽  
H. R. KARIMI ◽  
P. JABEHDAR MARALANI ◽  
B. MOSHIRI
Keyword(s):  
Neural Networks ◽  
Optimal Control ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Robot Manipulator ◽  
Tracking Error ◽  
Nonlinear Function ◽  
Robotic Manipulators ◽  
Lyapunov Theory ◽  
Modeling Uncertainties

The paper is concerned with the application of wavelet-based neural networks for optimal control of robotic manipulators motion. The model of robotic manipulators with regard to frictions and disturbances is nonlinear and uncertain. Optimal control law is found by the optimization of the Hamilton–Jacobi–Bellman (H-J-B) equation and it shows how wavelet-based neural networks can overcome nonlinearities through optimization without preliminary off-line learning phase. The neural network is learned as on-line and an adaptive learning algorithm is derived from the Lyapunov theory. This is so that both tracking stability and error convergence of the estimation for the nonlinear function can be guaranteed in the closed-loop system. The Lyapunov function for the nonlinear analysis is derived from the user input in terms of a specified quadratic performance index. Simulation results on a three-link robot manipulator show the satisfactory performance of the proposed control schemes even in the presence of large modeling uncertainties and external disturbances. Furthermore, it is shown that the tracking error for wavelet neural networks is less than conventional neural networks.

Optimal, Model-Based Design of Soft Robotic Manipulators

2008 ◽  
Vol 130 (9) ◽  
Author(s):  
Deepak Trivedi ◽  
Dustin Dienno ◽  
Christopher D. Rahn
Keyword(s):  
Nonlinear Models ◽  
Load Capacity ◽  
Robotic Manipulators ◽  
Cluttered Environments ◽  
Rod Theory ◽  
Cosserat Rod ◽  
Manipulator Design ◽  
Air Muscle ◽  
Muscle Actuators ◽  
General Method

Soft robotic manipulators, unlike their rigid-linked counterparts, deform continuously along their lengths similar to elephant trunks and octopus arms. Their excellent dexterity enables them to navigate through unstructured and cluttered environments and to handle fragile objects using whole arm manipulation. This paper develops optimal designs for OctArm manipulators, i.e., multisection, trunklike soft arms. OctArm manipulator design involves the specification of air muscle actuators and the number, length, and configuration of sections that maximize dexterity and load capacity for a given maximum actuation pressure. A general method of optimal design for OctArm manipulators using nonlinear models of the actuators and arm mechanics is developed. The manipulator model is based on Cosserat rod theory, accounts for large curvatures, extensions, and shear strains, and is coupled to the nonlinear Mooney–Rivlin actuator model. Given a dexterity constraint for each section, a genetic algorithm-based optimizer maximizes the arm load capacity by varying the actuator and section dimensions. The method generates design rules that simplify the optimization process. These rules are then applied to the design of pneumatically and hydraulically actuated OctArm manipulators using 100psi and 1000psi maximum pressures, respectively.

Dynamic Modeling and Optimal Control of a Wind Turbine with Doubly Fed Induction Generator Using Imperialist Competitive and Artificial Bee Colony Algorithms

2019 ◽  
Vol 28 (04) ◽  
pp. 1950070
Author(s):  
Javad Salehi ◽  
Arman Amini Badr
Keyword(s):  
Optimal Control ◽  
Artificial Bee Colony ◽  
Optimization Techniques ◽  
Dynamic Responses ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Bee Colony ◽  
Single Machine Infinite Bus ◽  
Doubly Fed ◽  
And Control

This paper addresses modeling, stability analysis and control of the doubly fed induction generator (DFIG) for wind turbines (WTs). In the present work, imperialist competitive and artificial bee colony algorithms are used for optimizing parameters of controllers of a WT with DFIG. Algorithms for optimizing the controllers’ parameters are described. Based on this, an eigenvalue-based objective function is utilized to optimize the parameters. To evaluate the optimized gains, simulations are performed on a single machine-infinite bus system, and the dynamic responses of system with parameters obtained from two optimization techniques are compared.

scholarly journals Development of an Experimental Robotic Complex for Direct Metal Deposition and Testing of Deposition Modes for Heat-Resistant Powder Material

2022 ◽  
Author(s):  
M.A. Oleynik
Keyword(s):  
Mathematical Model ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
Metal Deposition ◽  
Direct Metal Deposition ◽  
Joint Work ◽  
Control Programs ◽  
Tool Trajectory ◽  
Working Together ◽  
And Control

Abstract. The paper considers the issue of optimizing the movement of an industrial robot used in additive manufacturing in the technology of direct metal deposition of parts. The developed mathematical model that takes into account the joint work of a six-axis robot manipulator and a two-axis positioner is described. The algorithm for calculating the motion based on the relative position of two adjacent points of the working tool trajectory relative to the rotary axis of the positioner with a given accuracy is described. The simulation of processing is carried out both when working only with the manipulator, and when working together with a two-axis positioner, and control programs with recalculated coordinates and rotation angles of the positioner are obtained.

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