An adaptive fuzzy strategy for motion control of robot manipulators

This paper makes an attempt to develop a self-tuned proportional-integral-derivative (PID)-type fuzzy controller for the motion control of robot manipulators. In recent past, it has been widely believed that static fuzzy controllers can not be suitably applied for controlling manipulators with satisfaction because the robot manipulator dynamics is too complicated. Hence more complicated and sophisticated neuro-fuzzy controllers and fuzzy versions of nonlinear controllers have been more and more applied in this problem domain. The present paper attempts to look back at this widely accepted idea and tries to develop a self-tuned fuzzy controller with small incremental complexity over conventional fuzzy controllers, which can yet attain satisfactory performance. The proposed controller is successfully applied in simulation to control two-link and three-link robot manipulators.     

A class of nonlinear PD-type controllers for robot manipulators

In this article we present the stability analysis of a class of PD-type controllers for position and motion control of robot manipulators. The main feature of this class of controllers is that the proportional and derivative gains can be nonlinear functions of the robot states. These controllers can be obtained from control strategies that adjust the controller gains depending on the robot states. It is shown that global asymptotic stability of the control system is achieved provided that the P and D gains have suitable structure. As an outcome, we propose a global regulator constrained to deliver torques within prescribed limits of the actuator's capabilities. Experimental results on a two degrees of freedom direct drive arm show the usefulness of the proposed scheme. © 1996 John Wiley & Sons, Inc.     

Compound control of a compound cosine function neural network and PD for manipulators

In this paper, a compound cosine function neural network controller for manipulators is presented based on the combination of a cosine function and a unipolar sigmoid function. The compound control scheme based on a proportional-differential (PD) feedback control plus the cosine function neural network feedforward control is used for the tracking control of manipulators. The advantages of the compound control are that the system model does not need to be identified beforehand in the manipulator control system and it can achieve better adaptive control in an on-line continuous learning manner. The simulation results for the two-link manipulator show that the proposed compound control has higher tracking accuracy and better robustness than the conventional PD controllers in the position trajectory tracking control for the manipulator. Therefore, the compound cosine function neural network controller provides a novel approach for the manipulator control with uncertain nonlinear problems.     

Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic

Many robot controllers require not only joint position measurements but also joint velocity measurements; however, most robotic systems are only equipped with joint position measurement devices. In this paper, a new output feedback tracking control approach is developed for the robot manipulators with model uncertainty. The approach suggested herein does not require velocity measurements and employs the adaptive fuzzy logic. The adaptive fuzzy logic allows us to approximate uncertain and nonlinear robot dynamics. Only one fuzzy system is used to implement the observer-controller structure of the output feedback robot system. It is shown in a rigorous manner that all the signals in a closed loop composed of a robot, an observer, and a controller are uniformly ultimately bounded. Finally, computer simulation results on three-link robot manipulators are presented to show the results which indicate good position tracking performance and robustness against payload uncertainty and external disturbances.     

Adaptive intelligent cascade control of a ball-riding robot for optimal balancing and station-keeping

This paper presents an adaptive intelligent cascade control strategy to maintain the dynamic stability of a ball-riding robot (BRR). The four-wheeled mechanism beneath the robot body balances it on a spherical wheel. The BRR is modeled as a combination of two decoupled inverted pendulums. Therefore, two independent controllers are used to control its pitch and roll rotations. An incremental proportional–integral–derivative (PID) is implemented in the inner loop of the cascade to maintain the vertical balance. A generic PD controller is used in the outer loop to keep the station by controlling its spatial position. The controller parameters are automatically tuned via a fuzzy adaptation mechanism. The centers of fuzzy output membership functions are dynamically updated via an extended Kalman filter (EKF). The proposed controller quickly responds to changes in system’s state and effectively rejects the exogenous disturbances. The results of real-time experiments are presented to validate the effectiveness of the proposed hybrid controller over the conventional classical controllers.     

Control of three degrees-of-freedom underactuated manipulator using fuzzy based switching

A novel concept for designing a fuzzy logic-based switching controller to control underactuated manipulators is presented. The proposed controller employs elemental controllers, which are designed in advance. Parameters of both antecedent and consequent parts of a fuzzy indexer are optimized by using evolutionary computation. Design parameters of the fuzzy indexer are encoded into chromosomes, i.e., the shapes of the Gaussian membership functions and corresponding switching laws of the consequent part are evolved to minimize the angular position errors. Then, these trained fuzzy rules can be brought into the online operation of underactuated manipulators. Simulation results show that the new methodology is effective in designing controllers for underactuated robot manipulators.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

A multivariable control scheme for robot manipulators

The article puts forward a simple scheme for multivariable control of robot manipulators to achieve trajectory tracking. The scheme is composed of an inner loop stabilizing controller and an outer loop tracking controller. The inner loop utilizes a multivariable PD controller to stabilize the robot by placing the poles of the linearized robot model at some desired locations. The outer loop employs a multivariable PID controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated on-line to cope with variations in the robot model during gross motion and for payload change. Alternatively, the use of high gain controllers for gross motion and payload change is discussed. Computer simulation results are given for illustration.     

多自由度机械臂的饱和输出反馈有限时间同步位置控制EI北大核心CSCD

针对输入受限的多自由度机械臂高精度位置控制问题,本文充分考虑驱动器饱和非线性的影响,提出了多自由度机械臂输出反馈饱和有限时间比例–微分(PD)+同步位置控制策略,应用Lyapunov稳定性理论和几何齐次性技术证明了闭环系统的全局有限时间稳定性.非线性饱和函数的恰当引入,使得所提出的控制器具有清晰明确的上界,可以通过预先选择满足特定条件的控制器参数有效避免驱动器饱和问题;同步控制项的恰当引入,使得所提出的控制器兼顾了多自由度机械臂各轴间的同步协调性,从而获得更快的收敛速度和更好的系统整体性能,满足工程实际对机械臂的高精度要求.本文的数值仿真结果验证了所提出的控制方法的有效性和可行性.     

Decentralized adaptive control of manipulators

This article presents two new adaptive schemes for motion control of robot manipulators. The first controller possesses a partially decentralized structure in which the control input for each task variable is computed based on information concerning only that variable and on two “scaling factors” that depend on the other task variables. The need for these scaling factors is eliminated in the second controller by exploiting the underlying topology of the robot configuration space, and this refinement permits the development of a completely decentralized adaptive control strategy. The proposed controllers are computationally efficient, do not require knowledge of either the mathematical model or the parameter values of the robot dynamics, and are shown to be globally stable in the presence of bounded disturbances. Furthermore, the control strategies are general and can be implemented for either position regulation or trajectory tracking in joint-space or task-space. Computer simulation results are given for a PUMA 762 manipulator, and these demonstrate that accurate and robust trajectory tracking is achievable using the proposed controllers. Experimental results are presented for a PUMA 560 manipulator and confirm that the proposed schemes provide simple and effective real-time controllers for accomplishing high-performance trajectory tracking. © 1994 John Wiley & Sons, Inc.     

Robustness improvement of a nonlinear H∞ controller for robot manipulators via saturation functions

In this paper, previous works on nonlinear H_∞ control for robot manipulators are extended. In particular, integral terms are considered to cope with persistent disturbances, such as constant load at the end‐effector. The extended controller may be understood as a computed‐torque control with an external PID, whose gain matrices vary with the position and velocity of the robot joints. In addition, in order to increase the controller robustness, an extension of the algorithms with saturation functions has been carried out. This extension deals with the resulting nonlinear equation of the closed‐loop error. A modified expression for the required increment in the control signal is provided, and the local closed‐loop stability of this approach is discussed. Finally, simulation results for a two‐link robot and experimental results for an industrial robot are presented. The results obtained with this technique have been compared with those attained with the original controllers to show the improvements achieved by means of the proposed method. © 2005 Wiley Periodicals, Inc.     

Globally asymptotically stable ‘PD+’ controller for robot manipulators

We describe a globally stable tracking controller for robot manipulators. The controller is an extension of Takegaki and Arimoto's position controller to the tracking case where a theorem of Matrosov is used to prove its stability. An attractive feature of this controller is its resemblance to the computed torque controller with the inertia matrix outside the position and velocity feedback loops. Thus, our controller is decomposed into an inner PD loop and an outer dynamic compensation loop. This structure allows the simple PD computations to be run at a higher speed than the dynamic compensation loop in digital implementations.     

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.     

Joint stick-slip friction compensation of robot manipulators by using smooth robust controllers

In this article, two new smooth robust nonlinear compensators have been developed, respectively, for positional regulation and trajectory tracking of rigid robot manipulators with internal joint stick-slip friction. The proposed controllers can improve not only the positioning accuracy but also the smoothness of motion. No exact knowledge of the friction models is required for the design of the controllers. Furthermore, the tracking controller is also robust with respect to the uncertain link parameters. Using Lyapunov's direct method, we can show that the time-invariant positional regulation controller guarantees the global boundedness stability of the closed-loop system, while the time-varying positional tracking controller guarantees the global asymptotic stability of the closed-loop system. The numerical simulations of the controllers on a two-link robot are presented as illustrations. © 1994 John Wiley & Sons, Inc.     

Approximate Jacobian control with task-space damping for robot manipulators

In this note, we propose two new approximate Jacobian control laws with task-space damping for setpoint control of robot manipulators. The proposed controllers do not require exact knowledge of the Jacobian matrix and dynamics of the robots. We will show that the end-effector's position converges to a desired position in a finite task space even when the kinematics and Jacobian matrix are uncertain. Experimental results are presented to illustrate the performance of the proposed controllers.     

Two adaptive control structures of robot manipulators

This paper proposes two simple adaptive control schemes of robot manipulators. The first one is the state feedback control which consists of feedforward from the desired position trajectory, PD feedback from the actual trajectory, and an auxiliary input. The second one is the feedforward/feedback control which consists of a feedforward term from the desired position, velocity, and acceleration trajectory based on the inverse of robot dynamics. The feedforward, feedback, and auxiliary gains are adapted using simple equations derived from the decentralized adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the detail parameters of the manipulator or the payload. Simulation results are presented in support of the proposed schemes. The results demonstrate that both controllers perform well with bounded adaptive gains.     

On cooperative manipulation of dynamic objects

This paper proposes a decentralized position/internal force hybrid control approach for multiple robot manipulators to cooperatively manipulate an unknown dynamic object. In this approach, each autonomous robot has its own controller and uses its own sensor information in performing the fast cooperation. This approach eliminates a lot of information communications between each robot and reduces numerous computations. The influences of the position and the internal force estimation errors to the overall control system is analyzed. A cooperative identification method for each autonomous robot to identify the object's complex dynamics, cooperatively, is presented. In addition, the trade-off between the unilateral force constraint and the robots' position response is studied. Experiments show the effectiveness of this control approach.     

Motion control of mechanical manipulators

The theory and implementation results of a recently developed class of adaptive and repetitive controllers used for motion control of robot manipulators are presented. The repetitive controller, which learns the input torque corresponding to a repetitive desired trajectory, requires no explicit knowledge of the manipulator equations of motion. The adaptive controller, on the other hand, which estimates the robot dynamic parameters on-line, may be used for more general trajectories but requires more detailed modeling information. Both schemes are computationally efficient and require no acceleration feedback of any kind; only standard position and velocity feedback information is utilized.The performance of both the adaptive and repetitive controllers was experimentally evaluated on an IBM 7545 robot. The experimental results of these controllers confirm a significant improvement in tracking accuracy over conventional Computed Torque and PD controllers.This work was supported by the National Science Foundation under grant MSS-8910427.     

Adaptive tracking control of flexible‐joint manipulators without overparametrization

In this paper, an adaptive controller is designed for rigid‐link flexible‐joint robot manipulators based on link and actuator position measurements only. It is based on the adaptive integrator backstepping method and the link and actuator velocity filters are used to estimate the unknown velocity terms. Moreover, the proposed controller exploits the estimate of the joint stiffness matrix inverse to overcome the overparametrization problem, which has been a significant drawback in adaptive partial state feedback controllers. It achieves asymptotic tracking of link positions while keeping all states and signals bounded. The tracking capability of the presented method is shown through simulation results of one‐ and two‐link flexible joint manipulators. © 2004 Wiley Periodicals, Inc.     

Global positioning of robot manipulators with mixed revolute and prismatic joints

The existing controllers for robot manipulators with uncertain gravitational force can globally stabilize only robot manipulators with revolute joints. The main obstacles to the global stabilization of robot manipulators with mixed revolute and prismatic joints are unboundedness of the inertia matrix and the Jacobian of the gravity vector. In this note, a class of globally stable controllers for robot manipulators with mixed revolute and prismatic joints is proposed. The global asymptotic stabilization is achieved by adding a nonlinear proportional and derivative term to the linear proportional-integral-derivative (PID) controller. By using Lyapunov's direct method, the explicit conditions on the controller parameters to ensure global asymptotic stability are obtained.     

Adaptive tracking control of manipulators: Theory and experiments

This paper considers the trajectory tracking problem for uncertain robot manipulators and proposes two adaptive controllers as solutions to this problem. The first controller is derived under the assumption that the manipulator state is measurable, while the second strategy is developed for those applications in which only position measurements are available. The adaptive schemes are very general and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the manipulator dynamics, and are implemented without calculation of the robot inverse dynamics or inverse kinematic transformation. It is shown that the control strategies ensure uniform boundedness of all signals in the presence of bounded disturbances, and that the ultimate size of the tracking errors can be made arbitrarily small. Experimental results are presented for a PUMA 560 manipulator and demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed controllers.