Dynamic two arm hybrid position/force control

A useful two arm robot system will not only need to cooperatively manipulate the same object, but also need the ability for external force control. As an example, assume two robots are building a space station, which requires them to connect a structure to a partially built space station. This implies that they need to cooperatively move the object to the desired position, and then apply a force to connect it. Therefore, two arm hybrid position/force control is necessary. To accomplish this task quickly and accurately the dynamics of arm 1, arm 2, and the object must be taken into account. The external and internal forces must be clearly defined to be used in the servo control loop. There are several ways to choose the internal force: zero internal force, arbitrary force distribution, minimizing object strain energy, and minimizing the total torque. An example is shown to illustrate the trade-offs. A controller is presented which incorporates the dynamics of each arm, the dynamics of the object, and servos on the internal and external force. Experimental results show that servoing on the internal force will reduce the force error significantly.     

Fuzzy-neuro position/force control for robotic manipulators with uncertainties

The performance of a controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and the environmental stiffness. This paper aims to improve the controller’s robustness by applying the neural network to compensate for the uncertainties of the robot model at the input trajectory level rather than at the joint torque level. A self-adaptive fuzzy controller is introduced for robotic manipulator position/force control. Simulation results based on a two-degrees of freedom robot show that highly robust position/force tracking can be achieved, despite the existence of large uncertainties in the robot model.     

Adaptive positioning control of an ultrasonic linear motor system

A 3PRR parallel precision positioning system, driven by three ultrasonic linear motors, was designed for use as the object stage of a scanning electron microscope (SEM). To improve the tracking accuracy of the parallel platform, the positioning control algorithms for the drive joints needed to be studied. The dead-zone phenomenon caused by static friction reduces the trajectory tracking accuracy significantly. Linear control algorithms such as PID (Proportion Integration Differentiation) are unable to compensate effectively for the dead-zone nonlinearity. To address this problem, two types of feedforward compensation control algorithms have been investigated. One is constant feedforward with the integral separation PID; the other is adaptive feedback and feedforward based on the model reference adaptive control (MRAC). Simulations and experiments were conducted using these two control algorithms. The results demonstrated that the constant feedforward with integral separation PID algorithm can compensate for the time-invariant system after identifying the dead-zone depth, while the adaptive feedback and feedforward algorithm is more suitable for the time-varying system. The experimental results show good agreement with the simulation results for these two control algorithms. For the dead-zone nonlinearity caused by the static friction, the adaptive feedback and feedforward algorithm can effectively improve the trajectory tracking accuracy.     

Remote control of an ultrasonic motor by using a GSM mobile phone

In this study, remote control of an ultrasonic motor has been implemented by using a standard GSM mobile phone. To drive the ultrasonic motor a digitally controlled drive system has been designed. Then a tone decoder circuit and microcontroller have been added between output of a mobile phone and the drive system of the motor. This system is flexible to be controlled with both GSM and DTMF based phones. With the developed drive and control system the overall control of the ultrasonic motor has been achieved. The system has been tested for different speed, position and direction conditions successfully. The experimental results verify that the GSM controlled drive system is highly effective, reliable, proper and applicable to achieve remote control of the ultrasonic motor. This study gets novel and important point of view for GSM based remote control applications addition to the control of ultrasonic motors.     

Dynamic hybrid position/force control of a two degree-of-freedom flexible manipulator

In this article, a method is proposed whereby both contact force exerted by a flexible manipulator and position of end-effector while in contact with a surface are controlled. We approximate elastic deformations by means of B-spline functions and derive dynamic equations of joint angles, vibration of the flexible link, and constraint force. A controller for the hybrid position/force control of the flexible manipulator is designed on the basis of the singular perturbation method. Simulation results confirm that the controller performs remarkably well. © 3994 John Wiley & Sons, Inc.     

Adaptive Jacobian position/force tracking control of free-flying manipulators

This paper solves the problem of position/force tracking control of a free-flying space manipulator with uncertain kinematics and dynamics. A free-flying manipulator interacting with an uncertain compliant surface is considered. To cope with the uncertainties arising from free-flyer’s kinematics, dynamics and surface stiffness and position, an adaptive Jacobian controller is devised. The convergence of the force and position tracking errors is proved based on Lyapunov stability analysis. Numerical simulation is presented to show the performance of the controller.     

Adaptive neuro fuzzy based hybrid force/position control for an industrial robot manipulator

In this paper an ANFIS-PD+I (AFSPD+I) based hybrid force/position controller has been proposed which works effectively with unspecified robot dynamics in the presence of external disturbances. A constraint is put to limit the movement of manipulator in XY Cartesian coordinates. The validity of the proposed controller has been tested using a 6-degree of freedom PUMA robot manipulator. The performance comparison have been done with the fuzzy proportional derivative plus integral, fuzzy proportional integral derivative and conventional proportional integral derivative controllers subjected to the same data set with proposed controller. The projected AFSPD+I controller adhered to the desired path closer and smoother than the other mentioned controllers.     

Features of designing combined force/position manipulator control systems

A synthesis method of combined force/position control systems of multilink manipulators is proposed. A self-adjusting control systems synthesized on the basis of this method provide fast tracking of arbitrary spatial trajectories along complex surfaces by the processing tool with high dynamic precision and simultaneous creation of required force action on these surfaces (processed objects).     

On the invariance of the hybrid position/force control

Recently, the noninvariance nature of the Raibert and Craig hybrid control scheme, based on the work of Mason and others, has been pointed out. In fact, on the basis of the screw theory, Lipkin and Duffy demonstrated that the selection of the position and force controlled degrees of freedom in the Raibert and Craig scheme, may give wrong results if a translation or change in unit length of the coordinate frame is performed. A general theoretical solution to this problem, called kinestatic filtering, has been given by Lipkin and Duffy. In this paper, the two approaches are summarized and discussed. First, the conditions in which the Mason filtering technique fails are determined and, second, the situations where the Lipkin and Duffy approach cannot be applied owing to degeneracy of the twist and wrench spaces, are reported. As a consequence of this analysis, a new invariant kinestatic filtering method is proposed. The method here presented is based on the original Mason approach and requires the definition of a task-dependent filter based on the knowledge of the position of the compliant frame. Examples are presented and discussed.     

Kinematic analysis and position/force control of the Anthrobotdextrous hand

The increasing demand for robotic applications in unstructured environments is motivating the need for dextrous end-effecters which can cope with the wide variety of tasks and objects encountered in these environments. A new anthropomorphic robot hand (Anthrobot) which was designed for these environments is described. In this paper the problem of developing the kinematics and unit consistent hybrid position/force control of the Anthrobot fingers is considered as the first step toward its utilization for either teleoperation or autonomous operation. A dynamic model of the fingers is identified and used to develop the control laws. The experimental results of applying the control to the Anthrobot are discussed.     

Stabilizing position/force control of robots interacting with environment by learning connectionist structures

This paper is mostly concerned with the application of connectionist architectures for fast on-line learning of robot dynamic uncertainties used at the executive hierarchical control level in robot contact tasks. The connectionist structures are integrated in non-learning control laws for contact tasks which enable stabilization and good tracking performance of position and force. It has been shown that the problem of tracking a specified reference trajectory and specified force profile with a present quality of their transient response can be efficiently solved by means of the application of a four-layer perceptron. A four-layer perceptron is part of a hybrid learning control algorithm through the process of synchronous training which uses fast learning rules and available sensor information in order to improve robotic performance progressively in the minimum possible number of learning epochs. Some simulation results of the deburring process with robot MANUTEC r3 are shown to verify effectiveness of the proposed control learning algorithms.     

Adaptive force and position control of manipulators

The article presents simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecture. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal, and a force feedforward term, and achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers as well as an auxiliary signal, and accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in online control with high sampling rates. The methods are applied to a two-link manipulator for simultaneous force and position control. Simulation results confirm that the adaptive controllers perform remarkably well under different conditions.     

超声波电机转速的PIDNN控制

针对行波超声波电机运行过程中的较强时变性与非线性特征,引入了一种比例—积分—微分神经元网络(PIDNN)电机速度控制器.控制器网络融合了状态转换函数,具备动态映射能力,利用PID控制律先验知识确定权值初值,通过可变学习速度反传算法(VLBP)在线学习,使训练结果快速收敛,不易陷入局部极小,从而实现对超声波电机稳定快速的控制.采用参数变化电机模型对控制器进行仿真校验,仿真结果表明:方法具有较快的响应速度和较高的鲁棒性,能通过在线学习补偿电机运行过程中的非线性.     

Self-tuning speed control of ultrasonic motor combined with efficiency optimization

Aiming at the nonlinear characteristics of ultrasonic motor (USM) control system, a self-tuning pole assignment speed control strategy is proposed in this paper. The parameters of motor system are identified online, and then the controller is modified online according to the identified parameters of motor. In view of the short-time working characteristic of USM, a method for determining initial values of parameters with online identification algorithms is presented. Using this method, efficient self-tuning control can be realized using a small quantity of testing data. The proposed strategy is robust and relatively simple. Experimental results indicate that the speed control performance is good.     

Mimo and siso self-tuning hybrid position/force control of robotic manipulators

This article presents a new approach for the hybrid position/force control of a manipulator by using self-tuning regulators (STR). For this purpose, the discrete-time stochastic multi-input multi-output (MIMO) and single-input single-output (SISO) models are introduced. The MIMO model's output vector has the positions and velocities of the gripper expressed in the world (xyz) coordinate system as the components. The SISO model outputs are the hybrid errors consisting of the derivatives of the position and force errors at the joints. The inputs of both models are the joint torques. The unknown parameters of those models can be calculated recursively on-line by the square-root estimation algorithm (SQR). An adaptive MIMO and SISO self-tuning type controllers are then designed by minimizing the expected value of a quadratic criterion. This performance index penalizes the deviations of the actual position and force path of the gripper from the desired values expressed in the Cartesian coordinate system. An integrating effect is also included in the performance index to remove the steady-state errors. Digital simulation results using the parameter estimation and the control algorithms are presented and the performances of those two controllers are discussed. © 1996 John Wiley & Sons, Inc.     

Enhanced myoelectric control against arm position change with weighted recursive Gaussian process

Neural Computing and Applications - In the last decade, there has been huge advancement in biomechatronic systems by the integration of pattern recognition and regression algorithms. In many...     

Torque sensorless force/position decentralized control for constrained reconfigurable manipulator with harmonic drive transmission

International Journal of Control, Automation and Systems - The difficulty of addressing the decentralized control problem for a torque sensorless constrained reconfigurable manipulator is...     

A new approach to robust position/force control of flexible-joint robot manipulators

In this paper a new approach employing smooth robust compensators is proposed for the control of uncertain elastic-joint robot manipulators during contact tasks. It is assumed that the flexible-joint manipulators consist of two subsystems: the rigid subsystem and the flexible subsystem. The output of the flexible subsystem is assumed to be the input of the rigid subsystem. The control design is carried out in two steps. First, a desired input is designed for the rigid subsystem, which can robustly stabilize it. Second, a robust controller is designed to stabilize the flexible subsystem so that it generates the necessary torque designed for the rigid subsystem. By using this approach, the robot manipulator can exert a preset amount of force on the environment while tracking a desired trajectory with global asymptotic stability. Lyapunov's direct method is used here to prove the global asymptotic stability of the closed-loop system. The assumption of weak joint elasticity is relaxed and exact knowledge of joint stiffness is not required for the control design. Also, exact knowledge of robot kinematic and dynamic parameters and actuator parameters are not required. Unlike other approaches, this approach takes the environmental stick-slip friction as well as its dependency on normal contact force into consideration. It compensates for the adverse effects of the stick-slip friction. The proposed controller produces a smooth control action, and ensures smooth motion on the contact surface. The efficacy of the proposed controller is illustrated with the help of a numerical example of a two-link flexible-joint robot. © 1996 John Wiley & Sons, Inc.     

Continuous shape-grinding experiment based on model-independent force/position hybrid control method with on-line spline approximation

Based on the analysis of interaction between manipulator’s hand and working object, a model representing the constrained dynamics of robot is first discussed. The constraint forces are expressed by algebraic function of states, input generalized forces, and constraint condition, and then a decoupling control method of force and position of manipulator’s hand tip is proposed. In order to give the grinding system the ability to adapt to any object shape being changed by the grinding, estimating function of the constraint condition in real time for the adaptive force/position control was added, which is indispensable for the proposed method without using force sensor. This paper explores whether the performance of the proposed controller is independent of alloy work-piece models or not. The experimental result is shown to verify the feature of the decoupling control of force and position of the tip.     

Two-stage adaptive robot position/force control using fuzzy reasoning and neural networks

Many studies have been performed on the position/force control of robot manipulators. Since the desired position and force required to realize certain tasks are usually designated in the operational space, the controller should adapt itself to an environment and generate the control force vector in the operational space. On the other hand, the friction of each joint of a robot manipulator is a serious problem since it impedes control accuracy. Therefore, the friction should be effectively compensated for in order to realize precise control of robot manipulators. Recently, soft computing techniques (fuzzy reasoning, neural networks and genetic algorithms) have been playing an important role in the control of robots. Applying the fuzzy-neuro approach (a combination of fuzzy reasoning and neural networks), learning/adaptation ability and human knowledge can be incorporated into a robot controller. In this paper, we propose a two-stage adaptive robot manipulator position/force control method in which the uncertain/unknown dynamic of the environment is compensated for in the task space and the joint friction is effectively compensated for in the joint space using soft computing techniques. The effectiveness of the proposed control method was evaluated by experiments.