Robot Manipulator Control System Research Articles

PID Control for a Manipulator Robot Using Internet Networking and Matlab-based

This paper presents the design to the implementation of the proportional, integral and derivative (PID) remote control system of robot manipulator using Matlab-based Internet network. These studies seek the solution of distance operations, time constraints, and monitoring the operation response of robot manipulator motion as robot that possible to carry dangerous objects which is should be monitored remotely during the operation. PID control system that is controlled remotely by the client and server systems. The monitoring process of robot manipulator is Matlab-based. Testing is done by doing observation to the speed response of the DC motor as the robot’s axis driver on open loop system condition, and then doing observation using PID control system. The test of axis robot driver has also been carried out with a variety of no-load and load conditions. The test results showed the motor driver of robot will work optimally when using PID control system. The data acquisition and the stability of data communication between the client and server are affected by the condition of the existing data transfer on the network and also the distance from the server to the plant.

Synthesis of the Decentralized Control System for Robot-Manipulator with Input Saturations

It is discussed the problem of synthesis of the decentralized adaptive-periodic control system for two degrees of freedom robotic manipulator which have an input limitations. The solution of the problem is based on the use of hyperstability criterion, L-dissipativity conditions and dynamic filter-corrector.

Robust control system for parallel kinematics robotic manipulator

Abstract This paper deals with the designing of robust trajectory tracking controller for parallel kinematics robotic manipulators that can be used for nonprehensile material handling and dynamic simulators in industrial and medical applications. The controller design is based on output control algorithm for structurally and parametrically uncertain systems called consecutive compensator. Controller performance is verified for the task of moving a ball along circular reference trajectories. Only ball coordinates on a plane are measured, but not its velocities and accelerations, while noise in measurements is assumed to be serial uncorrelated with zero mean. Taking into account control magnitude constraints, we implemented an anti-windup correction for the control law. The experimental validation is performed by a parallel manipulator ball-and-plate with tactile feedback.

Сравнительный анализ методов адаптации параметров регулятора системы управления робота-манипулятора

Сравнительный анализ методов адаптации параметров регулятора системы управления робота-манипулятора

Wave-variable framework for networked robotic systems with time delays and packet losses

ABSTRACTThis paper investigates the problem of networked control system for nonlinear robotic manipulators under time delays and packet loss by using passivity technique. With the utilisation of wave variables and a passive remote controller, the networked robotic system is demonstrated to be stable with guaranteed position regulation. For the input/output signals of robotic systems, a discretisation block is exploited to convert continuous-time signals to discrete-time signals, and vice versa. Subsequently, we propose a packet management, called wave-variable modulation, to cope with the proposed networked robotic system under time delays and packet losses. Numerical examples and experimental results are presented to demonstrate the performance of the proposed wave-variable-based networked robotic systems.

A Spintronic Memristor-Based Neural Network With Radial Basis Function for Robotic Manipulator Control Implementation

A radial basis function (RBF) neural network control algorithm can effectively improve the robotic manipulators’ performance against a large amount of uncertainty. The adaptive law can be derived by using the Lyapunov method so that the stability of robotic manipulator control system and the weight self-adaptive convergence of RBF neural networks will be guaranteed. Meanwhile, system fluctuations and even overshot phenomenon under every start-up process, which are caused by the system’s convergence from the given nonoptimal initial weight value to the optimal weight value, can be avoided by using memristors to remember the optimal weight after the system’s first operation. According to the above analysis, this correspondence paper designs a kind of RBF neural network control algorithm based on spintronic memristors, and then analyzes its theoretical derivation process and core design idea. Finally, the system simulation model, which uses a two-link robotic manipulator as control object, is built to prove the algorithm’s validity and feasibility. Simulation results show that the proposed algorithm can satisfy the effect of presupposition.

Development of an Anthropomorphic Gripping Manipulator: The Study of Kinematics and Virtual Modeling of Grip

The article is a study into the kinematic scheme of a newly developed anthropomorphic manipulator designed to perform gripping and holding tasks on items from a predefined set. Within the study is the implementation of a mathematical model describing the kinematics of a multilink manipulator using the GraspIt package. The method used in this study allows for the calculation of design parameters for manipulator grip functions at an early stage of the creation process as well as to verify the effectiveness of the kinematic scheme of the manipulator on how adequately it can perform its primary functions of griping and holding certain objects, which is vitally important in the design of universal anthropomorphic handling manipulators for special applications, such as bionic prostheses as well as manipulators with arbitrary kinematic schemes. The presented program model provides a preliminary calculation of the motion trajectories of the manipulator unit through the so-called eigengrasp (synonym-synergy, synchronous motion) and can be used as a virtual model for building embedded control systems for robot manipulators. It is shown that in the development of anthropomorphic handling manipulators for operating with small-sized objects it is more efficient to use the monkey scheme, but if the main group of target objects is primarily large items, then it is better to use the human scheme.

Robust Adaptive Neural-Fuzzy Network Tracking Control for Robot Manipulator

This paper presents a robust adaptive neural-fuzzy network control (RANFNC) system for an n-link robot manipulator to achieve the highprecision position tracking. Initially, the model dynamic of an n-link robot manipulator is introduced. However, it is difficult to design a conformable model-based control scheme, for instance, external disturbances, friction forces and parameter variations. In order to deal with this problem, the RANFNC system is investigated to the joint position control of an n-link robot manipulator. In this control scheme, a four-layer neural-fuzzy-network (NFN) is used for the main role, and the adaptive tuning laws of network parameters are derived in the sense of a projection algorithm and the Lyapunov stability theorem to ensure network convergence as well as stable control performance. The merits of this model-free control scheme are that not only the stable position tracking performance can be guaranteed but also unknown system information and auxiliary control design are required in the control process. The simulation results are provided to verify the effectiveness of the proposed RANFNC methodology.

Robot manipulator control system

The paper analyzes design concepts for up-to-date robot manipulator control systems. Approaches to building software and hardware architecture are described. The developed IntNCR control system is examined.

Walk-through programming for robotic manipulators based on admittance control

SUMMARYThe present paper addresses the issues that should be covered in order to develop walk-through programming techniques (i.e. a manual guidance of the robot) in an industrial scenario. First, an exact formulation of the dynamics of the tool the human should feel when interacting with the robot is presented. Then, the paper discusses a way to implement such dynamics on an industrial robot equipped with an open robot control system and a wrist force/torque sensor, as well as the safety issues related to the walk-through programming. In particular, two strategies that make use of admittance control to constrain the robot motion are presented. One slows down the robot when the velocity of the tool centre point exceeds a specified safety limit, the other one limits the robot workspace by way of virtual safety surfaces. Experimental results on a COMAU Smart Six robot are presented, showing the performance of the walk-through programming system endowed with the two proposed safety strategies.

A Robotic Manipulator Control and Simulation System with Qt and VTK

In this paper, we present an object-oriented C++ library for robotic manipulator control and simulation, THRControl, which is inherited from Qt and VTK. The library package has advantages include support cross-platform applications; high flexibility and high computational efficiency meet the need of computations required in robot control such as forward kinematics, inverse dynamics, and jacobian. The experimental results show that it is very easy is construct a user-friendly manipulator control and simulation system.

Automatic design of control systems for robot manipulators using the bees algorithm

This paper proves the capability of the bees algorithm to solve complex parameter optimization problems for robot manipulator control. Two applications are presented. The first case considers the modelling of the inverse kinematics of an articulated robot arm using neural networks. The weights of the connections between the nodes need to be set so as to minimize the difference between the neural network model and the desired behaviour. In the proposed example, the bees algorithm is used to train three multilayer perceptrons to learn the inverse kinematics of the joints of a three-link manipulator. The second case considers the design of a hierarchical proportional–integral–derivative (PID) controller for a flexible single-link robot manipulator. The six gains of the PID controller need to be optimized so as to minimize positional inaccuracies and vibrations. Experimental tests demonstrated the validity of the proposed approach. In the first case, the bees algorithm proved very effective at optimizing the neural network models. Compared with the results obtained employing the standard back-propagation rule and an evolutionary algorithm, the bees algorithm obtained superior results in terms of training accuracy and robustness. In the second case, the proposed method demonstrated remarkable efficiency and consistency in the tuning of the PID controller parameters. In 50 independent optimization trials, the PID controllers designed using the bees algorithm consistently outperformed a robot controller designed using a standard manual technique.

Fuzzy Logic Based Impedance Control to Monitor on Torque under Impulsive Loading

This paper is devoted to design a control system for robot manipulator to optimize motor torque due to external impulsive loading exerted on the manipulator. Under impulsive loading, overloading may occur in the absence of any monitoring on the torque. To avoid the overloading, impedance control is proposed as a force control strategy. Here impedance control based on force feedback of which has hit the end-effector modifies the reference trajectory. In fact, instead of resisting against impulsive loading up to extreme power of the motor, the proposed design generates small movements in the direction of impact. Therefore, the motor produces less torque in comparison to the absence of impedance control. A supervisory system assisting fuzzy logic has been used to adapt impedance controller parameters with various impact conditions. The simulation result confirms the improvement of the manipulator behavior which yields sensible reduction in motor developed torque in comparison to single PID controller.

Nondaily behavior detection monitoring system for elderly people based on bayesian network representation of omnidirectional vision sensor

AbstractThis paper describes an unusual behavior detection system based on an omnidirectional vision sensor, as one of the important elements in realizing “Sensing and Robotic Support Rooms” for elderly people. Such support rooms are expected to be further developed in the future with advanced abilities to automatically recognize elderly people's actions and behavior patterns, to detect unusual patterns by using sensors, and to support their daily motions by using robotic manipulator control systems. The proposed monitoring system using an omnidirectional vision sensor automatically learns daily behavior patterns and detects unusual behavior patterns and actions by using the Bayesian network approach. The Bayesian network is constructed by using image feature values such as area and center‐of‐gravity values extracted from a captured image sequence, and the respective behavior patterns are represented as conditional probabilities. Unusual behavior patterns can be automatically detected on the basis of the low generation probability values. Experiments based on the investigation of elderly people's typical daily behavior patterns have shown the effectiveness of the proposed system. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 172(3): 42–51, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20990

Open Architecture of Robot Control System Based on PROFI-BUS

A PROFI-BUS based industrial robot control system is introduced from the viewpoint of both software and hardware. It is discussed about how to use PC technology and field-bus technology to design an open robot control system. The system adopts a three- layer structure, which is mainly configured with universal control devices, to realize a modular and universal design. A high-speed field-bus is designed for connecting servo system and IPC, to ensure real-time capability; another low-speed Field-bus is used to connect IPC and PLC, HMI, teaching panel and other devices for data exchange, while reducing the occupancy of system resources. The software system adopts the modular design with Windows NT and RTX, which fully exploits the powerful functions of Window NT system and meets the requirements of real-time system. This open structure greatly enhances the system's flexibility and openness.

全方位センサのベイジアンネットワーク表現に基づく高齢者非日常行動検出モニタリングシステム

This paper describes an unusual behavior detection system based on an omni-directional vision sensor as one of the important elements in realizing “Sensing and Robotic Support Room” for elderly people. Such support rooms are expected to be further developed in the future with the high performance to automatically recognize elderly people's actions and behavior patterns and detect the unusual patterns using some sensors and to support their daily motions using some robotic manipulator control systems. The proposed monitoring system using an omni-directional vision sensor automatically learns the daily behavior patterns and detects the unusual behavior patterns and actions using Bayesian Network approach. The Bayesian Network is constructed using image feature values such as the area and center of gravity values extracted from the captured image sequence and the respective behavior patterns are represented as the conditional probabilities. Unusual behavior patterns can be automatically detected based on the low generation probability values. Some experiments based on the investigation of elderly people's typical daily behavior patterns show the effectiveness of the proposed system.

Distributed control system for robotic manipulators

Abstract This paper deals with the modern methods of stationary industrial robots control by the using of multi-processor system. Distributed control system is the system where the problem solving or control process is distributed between several nodes. These nodes have to able to execute the specific operation and process the analogue or digital signals. That control system conception requires very fast and reliable communication. On the base of these requirements the CAN (Controller Area Network) was selected. The system is modular, it allows connection of another CPU board (e.g. radio communication module) for concrete task.

A design of digital adaptive control systems for space robot manipulators using a transpose of the generalized Jacobian matrix

We propose a digital control method for space robot manipulators using the transpose of the generalized Jacobian matrix. The method, however, is developed on the supposition that all the physical parameters of the robot manipulator are known. Therefore, if the end-effector of the manipulator captures an object whose mass is unknown, the stability of the control system cannot be maintained because the physical parameters are changed. This article presents the adaptive control version.

Neural-fuzzy control system for robotic manipulators

This article presents a control system structure, as well as a control algorithm, that combines neural networks with fuzzy logic for dynamical compensation of both structured and unstructured uncertainties. <P xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A new fuzzy reasoning method is derived in the neural mechanism and implemented with a cerebellar model articulation controller (CMAC), which outperforms conventional fuzzy controllers by reducing computational complexity and providing a learning ability that conventional fuzzy systems do not have. The overall control system is proven to be stable. The simulation results confirm that the system can track the desired position for both set-point and dynamic tracking in the presence of uncertainties such as changing payload, various frictions, and unknown disturbances.</P>

A PC-based open robot control system: PC-ORC

An open architecture manufacturing system pursues to integrate manufacturing components on a single platform. Therefore, a particular component can be easily added and/or replaced. In this paper, a modular and object-oriented approach for the PC-based open robot control (PC-ORC) system is investigated. A standard reference model for controlling robots, which consists of a hardware platform, an operating system module, and various application software modules, is first proposed. Then, PC-ORC system, which can reconfigure the control system in various production environments, is developed. The PC-ORC is constructed based upon the object-oriented method. Hence, it allows an easy implementation and modification of various modules. The PC-ORC consists of basic software, application objects, and additional hardware devices on a PC platform. Finally, by applying the proposed PC-ORC to a SCARA robot, the performance of the PC-ORC is examined.