Nonlinear control of electrical flexible-joint robots

This paper is devoted to the nonlinear tracking control of electrically driven flexible-joint manipulators using the voltage control strategy. Despite the torque control laws that are involved in the complexity of manipulator dynamics, the proposed control law is free from manipulator dynamics. This novelty is for adopting the voltage control strategy to derive a simple robust adaptive control under both structured and unstructured uncertainty. The proposed control approach has a fast response with a good tracking performance under the well-behaved control efforts in the form of decentralized control. The control method is justified by the stability analysis and simulated on a flexible-joint electrically driven robot manipulator.     

Impedance control of robots using voltage control strategy

Impedance control provides a unified solution for the position and force control of robot manipulators. The dynamic behavior of a robotic system in response to environment is prescribed by an impedance model formed as Thevenin model. This model is certain and linear while the robot manipulator is highly nonlinear, coupled, and uncertain. Therefore, impedance control must overcome nonlinearity, coupling, and uncertainty to convert the robotic system to the impedance model. To overcome these problems, this paper presents a novel impedance control for electrically driven robots, which is free from the manipulator dynamics. The novelty of this paper is the use of voltage control strategy to develop the impedance control. Compared with the commonly used impedance control, which is based on the torque control strategy, it is computationally simpler, more efficient, and robust. The mathematical verification and simulation results show the effectiveness of the control method.     

Optimal robust voltage control of electrically driven robot manipulators

This paper develops a novel robust optimal voltage control of electrically driven robot manipulators. The whole robotic system including the robot manipulator and motors is considered in the control problem. Particle Swarm Optimization (PSO) is used to optimize the control design parameters, thus the performance of control system is highly improved. Beside this, we use Voltage Control Strategy (VCS) which is more robust, faster, less coupled, and less computational compared with the common strategy called as Torque Control Strategy (TCS). To state these advantages, it is reasoning that the TCS is dependent on the manipulator dynamics whereas the VCS can be free from it. The robust optimal voltage control is verified by convergence analysis. A comparative study between the VCS and the TCS confirms superiority of the VCS to the TCS. Simulation results present effectiveness of the proposed methods applied on a spherical robot manipulator driven by permanent magnet dc motors.     

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.     

Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty

This paper presents a novel robust decentralized control of electrically driven robot manipulators by adaptive fuzzy estimation and compensation of uncertainty. The proposed control employs voltage control strategy, which is simpler and more efficient than the conventional strategy, the so-called torque control strategy, due to being free from manipulator dynamics. It is verified that the proposed adaptive fuzzy system can model the uncertainty as a nonlinear function of the joint position error and its time derivative. The adaptive fuzzy system has an advantage that does not employ all system states to estimate the uncertainty. The stability analysis, performance evaluation, and simulation results are presented to verify the effectiveness of the method. A?comparison between the proposed Nonlinear Adaptive Fuzzy Control (NAFC) and a Robust Nonlinear Control (RNC) is presented. Both control approaches are robust with a very good tracking performance. The NAFC is superior to the RNC in the face of smooth uncertainty. In contrast, the RNC is superior to the NAFC in the face of sudden changes in uncertainty. The case study is an articulated manipulator driven by permanent magnet dc motors.     

多机械臂搬运同一物体的协调动态载荷分配

针对多机械臂共同搬运同一物体形成闭运动链的协调系统,研究了多机械臂协调动态载荷分配存在冗余情况下的实时性分配方法文中提出了“应集中惯性质量棒”的概念,进而根据各机械臂的承载能力,采用线性加权的方法发展了一种操作物体质心处零内力的载荷分配原则。最后给出了系统载荷分配的解析表达式,有效地解决了多机械臂搬运同一物体时其动态载荷分配的实时性问题。     

Decentralized direct adaptive fuzzy control of robots using voltage control strategy

Decentralized control is the most favorite control of robot manipulators due to computational simplicity and ease of implementation. Beside that, adaptive fuzzy control efficiently controls uncertain nonlinear systems. These motivate us to design a decentralized fuzzy controller. However, there are some challenging problems to guarantee stability. The state-space model of the robotic system including the robot manipulator and motors is in a noncompanion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. For this purpose, adaptive fuzzy control may use all variable states. As a result, it suffers from computational burden. To overcome the problems, we present a novel decentralized Direct Adaptive Fuzzy Control (DAFC) of electrically driven robot manipulators using the voltage control strategy. The proposed DAFC is simple, in a decentralized structure with high-accuracy response, robust tracking performance, and guaranteed stability. Instead of all state variables, only the tracking error of every joint and its derivative are given as the inputs of the controller. The proposed DAFC is simulated on a SCARA robot driven by permanent magnet dc motors. Simulation results verify superiority of the decentralized DAFC to a decentralized PD-fuzzy controller.     

Control and Parameter Optimization of Flexible Robots*

A hierarchical control concept for flexible robot manipulators is presented. The equations of motion are derived using the multibody system method, incorporating flexible links equipped with surface bonded actuating and sensing devices. Exploiting the structure of the dynamic model, the control concept allows combination of any joint level control for the gross motion of the manipulator with decentralized linear control of the elastic deformation of each flexible link. Therefore, the approach is capable of solving both the problem of fast and precise point-to-point motion, with acceptable vibration characteristics, and the problem of accurate trajectory tracking of the end-effector. Control parameters are found through parameter optimization. In order to verify the proposed control strategy, a SCARA robot with one flexible link is considered.     

An evolutionary approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. The pseudoinverse control is not repeatable, causing drift in joint space which is undesirable for physical control. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms, leading to an optimization criterion for repeatable control of redundant manipulators, and avoiding the joint angle drift problem. Computer simulations performed based on redundant and hyper-redundant planar manipulators show that, when the end-effector traces a closed path in the workspace, the robot returns to its initial configuration. The solution is repeatable for a workspace with and without obstacles in the sense that, after executing several cycles, the initial and final states of the manipulator are very close.     

A nonlinear high gain observer based input–output control of flexible link manipulator

The input–output control strategy needs all of the states feedback. However, in flexible link robot manipulators, measuring the time rate of elastic degrees of freedom is practically impossible. In this paper, a new nonlinear high gain observer has been developed to estimate the elastic degrees of freedom and their time derivatives. The control strategy is based on an output redefinition approach which stabilizes the zero dynamics of the manipulator. Finally, the results are presented by implementing the proposed observer and controller on a single link flexible manipulator. Numerical simulations will support the validity of our research results.     

漂浮基双臂空间机器人姿态与末端抓手惯性空间轨迹协调运动的模糊滑模控制

本文讨论了载体姿态受控、位置不受控制的双臂空间机器人系统的控制问题.利用拉格朗日方法并结合系统动量守恒关系,建立了双臂空间机器人系统的非线性系统动力学模型.以此为基础,考虑到空间机器人系统结构的复杂性及其某些参数的变动性,根据具有较强鲁棒性的变结构控制理论,设计了双臂空间机器人载体姿态与两机械臂末端抓手惯性空间轨迹协调运动的滑模变结构控制方案.为了克服滑模变结构控制器抖振的缺点,附加设计了一个模糊控制器,以便根据系统的输出来动态调节滑模变结构控制器等速趋近率的系数,从而既确保了系统的快速响应而又消除了原有的抖振.系统数值仿真,证明了上述控制方案良好的控制效果.     

Optimization Problems of Controlled Multibody Systems Having Spring-Damper Actuators

The optimal control of the motion of mechanical systems is studied. A characteristic feature of these systems is the presence of passive actuators (springs, dampers, etc.). Energy-optimal control laws and structural parameters of nonlinear spring–damper actuators are determined analytically, which is necessary to impart arbitrary motion to a controllable mechanical system with n degrees of freedom. As an example, a numerical solution is presented for the problem of designing an energy-optimal spring actuator for a robot manipulator of closed kinematic structure     

Discrete adaptive fuzzy control for asymptotic tracking of robotic manipulators

This paper presents a novel discrete adaptive fuzzy controller for electrically driven robot manipulators. It addresses how to overcome the nonlinearity, uncertainties, discretizing error and approximation error of the fuzzy system for asymptotic tracking control of robotic manipulators. The proposed controller is model-free in the form of discrete Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned using an adaptive mechanism derived by stability analysis. A robust control term is used to compensate the approximation error of the fuzzy system for asymptotic tracking of a desired trajectory. The controller is robust against all uncertainties associated with the robot manipulator and actuators. It is easy to implement since it requires only the joint position feedback. Compared with fuzzy controllers which employ all states to guarantee stability, the proposed controller is very simpler. Stability analysis and simulation results show its efficiency in the tracking control.     

Proper uncertainty bound parameter to robust control of electrical manipulators using nominal model

This paper focuses on the uncertainty bound parameter (UBP) to design the robust control of electrical manipulators. The UBP is commonly obtained by considering the worst case of uncertainties in bounding functions. However, too high estimation of UBP may cause saturation of input, higher frequency of chattering in the switching control laws, and thus a bad behavior of the whole system, while too low estimation of UBP may cause a higher tracking error. A proper UBP is preferred to improve the performance of robust control system. A simple, less dependent and proper UBP is proposed based on the nominal model of electrical manipulator and feedbacks of joint accelerations. This work is motivated by recent experimental results in measuring acceleration by optical encoder. Modeling of an electrical manipulator with presence of uncertainties is presented for control purposes. The proposed robust control is justified by stability analysis.     

Solving time-varying inverse kinematics problem of wheeled mobile manipulators using Zhang neural network with exponential convergence

A mobile manipulator is a robotic device composed of a mobile platform and a stationary manipulator fixed to the platform. The forward kinematics problem for such mobile manipulators has a mathematical analytic solution; however, the inverse kinematics problem is mathematically intractable (especially for satisfying real-time requirements). To obtain the accurate solution of the time-varying inverse kinematics for mobile manipulators, a special class of recurrent neural network, named Zhang neural network (ZNN), is exploited and investigated in this article. It is theoretically proven that such a ZNN model globally and exponentially converges to the solution of the time-varying inverse kinematics for mobile manipulators. In addition, the kinematics equations of the mobile platform and the manipulator are integrated into one system, and thus the resultant solution can co-ordinate simultaneously the wheels and the manipulator to fulfill the end-effector task. For comparison purposes, a gradient neural network (GNN) is developed for solving time-varying inverse kinematics problem of wheeled mobile manipulators. Finally, we conduct extensive tracking-path simulations performed on a wheeled mobile manipulator using such a ZNN model. The results substantiate the efficacy and high accuracy of the ZNN model for solving time-varying inverse kinematics problem of mobile manipulators. Besides, by comparing the simulation results of the GNN and ZNN models, the superiority of the ZNN model is demonstrated clearly.     

空间机械臂非完整运动规划的最优控制

讨论空间机械臂系统的运动规划问题，利用系统的非完整特性，将空间机械臂动力学方程转化为非线性控制系统的状态方程，给出一种最优控制的数值自满。通过仿真计算，表明该算法的有效性。     

Nonlinear response of a flexible Cartesian manipulator with payload and pulsating axial force

In this present work, the nonlinear response of a single-link flexible Cartesian manipulator with payload subjected to a pulsating axial load is determined. The nonlinear temporal equation of motion is derived using D’Alembert’s principle and generalised Galerkin’s method. Due to large transverse deflection of the manipulator, the equation of motion contains cubic geometric and inertial types of nonlinearities along with linear and nonlinear parametric and forced excitation terms. Method of normal forms is used to determine the approximate solution and to study the dynamic stability and bifurcations of the system. These results are found to be in good agreement with those obtained by numerically solving the temporal equation of motion. Influences of amplitude of the base excitation, mass ratio, and amplitude of static and dynamic axial load on the steady state responses of the system are investigated for three different resonance conditions. For some specific conditions, the results obtained in this work are found to be in good agreement with the previously published experimental work. The results obtained in this work will find applications in the design of flexible Cartesian manipulators with payload.     

Realization of a Given Relative Motion of two Rigid Bodies by a Two-Armed Robot

The formulation of a new task of realizing a given relative motion of two rigid bodies by means of a robot having two manipulators is given. A method for constructing the movements of two-armed robots is proposed, which consists of solving the direct and inverse problems of manipulator kinematics, taking into account additional conditions for eliminating the dangerous rapprochement of links.Equations of relationships of parameters of relative motion of the working links of the manipulators are obtained with the relative movements of their adjacent links assumed for control functions. Expressions for control functions of manipulators are obtained for the realization of a given relative motion of the general form of two rigid bodies, and also for plane motion.Pointing to the possibility of crossing the working links under the action ofmanipulators in one work area, and obtained the relationships that allow these intersections to be avoided.     

Trajectory tracking control using velocity observer and disturbances observer for uncertain robot manipulators without tachometers

This paper deals with trajectory tracking control for rigid robot manipulators with model uncertainty and subject to external disturbances. The approach suggested herein does not require velocity measurement, because these robots are not equipped by tachometers for velocity measurement. For this purpose, two observers are proposed. The first is a velocity observer to estimate the missing velocity, and the second one is a disturbance observer to estimate the disturbance. Thereafter, these observers are integrated with the controller. Furthermore, semi-global asymptotic stability conditions of the composite controller consisting of a nonlinear controller, the velocity observer and the disturbance observer are established, and an estimate region of attraction is also given. This proof is based on Lyapunov theory. Finally, simulation results on two-links manipulator are provided to illustrate the effectiveness of the velocity observer based control using disturbance estimation (namely VOBCDE), when the Coulomb and viscous friction is considered as an external disturbance.