An extremum-seeking control approach for constrained robotic motion tasks

In this paper, we propose two adaptive control schemes for multiple-input systems for execution of robot end-effector movements in the presence of parametric system uncertainties. The design of these schemes is based on Model Reference Adaptive Control (MRAC) while the adaptation of the controller parameters is achieved by Extremum Seeking Control (ESC). The two control schemes, which are called Multiple-Input ESC–MRAC and Multiple-Input Adaptive-Dynamic-Inversion ESC–MRAC, are suitable for linear and nonlinear systems respectively. Lyapunov and averaging analysis shows that the proposed schemes achieve practical asymptotic reference state tracking. The proposed methods are evaluated in simulations and in a real-world robotic experiment.     

Online stiffness estimation for robotic tasks with force observers

In this paper we propose an online stiffness estimation technique for robotic tasks based only on force data, therefore, not requiring contact position information. This allows estimations to be obtained in robotic tasks involving interactions with unstructured and unknown environments where geometrical data is unavailable or unreliable. Our technique – the Candidate Observer Based Algorithm (COBA) – uses two force observers, configured with different candidate stiffnesses, to estimate online the actual target object stiffness. COBA is embedded in a force control architecture with computed torque in the task space. The theoretical presentation of the algorithm, as well as simulation tests and experimental results with a lightweight robot arm are also presented.     

Parameterization of decoupling controllers in the unity-feedbacksystem

The problem of decoupling in the linear, time invariant, multiinput-multioutput unity-feedback system is studied. A parameterization of all stabilizing decoupling controllers and all achievable decoupled closed-loop transfer functions is obtained for full-row rank plants which do not have any coinciding poles and zeros in the undesirable region of the complex plane     

Correlation-based tuning of decoupling multivariable controllers

The iterative method labelled correlation-based tuning (CbT) is considered in this paper for tuning linear time-invariant multivariable controllers. The approach allows one to tune some elements of the controller transfer function matrix to satisfy the desired closed-loop performance, while the other elements are tuned to mutually decouple the closed-loop outputs. Decoupling is achieved by decorrelating a given reference with the non-corresponding outputs. The controller parameters are calculated either by solving a correlation equation (decorrelation procedure) or by minimizing a cross-correlation function (correlation reduction). In addition, the preferred way of exciting a 2×2 system for CbT is investigated via the accuracy of the estimated controller parameters. It is shown that simultaneous excitation of both reference signals does not improve the accuracy of the estimated controller parameters compared to the case of sequential excitation. In fact, one must choose between low experimental cost (simultaneous excitation) and better accuracy of the estimated parameters (sequential excitation). The theoretical results are illustrated via three simulation studies.     

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.     

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.     

Wiener-Hopf design of optimal decoupling one-degree-of-freedom controllers

This reasonably self-contained paper is directed to the design of a multivariable optimal one-degree-of-freedom feedback loop which incorporates a decoupling controller in the forward path. The criterion for optimality is a quadratic-cost functional that penalizes both tracking error and saturation. The controllers on which optimization is based are general enough to allow for non-unity feedback and rectangular plant transfer matrices possessing normal row rank. Nevertheless, for the sake of brevity and clarity, attention is focused mainly on the square case. Earlier treatments of the problem have employed multi-degree-of-freedom controllers. The solution we present for the one-degree-of-freedom case is considerably more difficult to obtain, especially when saturation is taken into account. Explicit formulas are derived for the set of all decoupling controllers yielding finite cost, as well as those that are optimal. It is shown that these controllers are strictly-proper under conditions usually prevailing in practice. Four fully worked examples serve to illustrate many important numerical aspects of the theory and all major proofs are transferred to the Appendix.     

A virtual centrifugal force based navigation algorithm for explorative robotic tasks in unknown environments

In many robotic tasks, there is no a priori knowledge of the environment. This makes it necessary for robots to explore the environment. Navigation algorithms for robots to map the environment completely in a short time play a very important role in the robotic task completion. A navigation algorithm based on virtual centrifugal force is proposed to complete the robotic exploration of the unknown environment using rang sensors in this paper. Collisions between a robot and an obstacle or between robots can be avoided with the application of the proposed navigation rules. The kinematics and dynamics equations of robots adopting the algorithm are also given. The simulation experiments demonstrate the operation of the algorithm. Several simulation experiments of various representative robotic tasks are carried out, based on the explorative navigation algorithm, which successfully validate the virtual centrifugal force based navigation algorithm.     

Hybrid position/force tracking for a class of constrained mechanical systems

We study the hybrid tracking problem for a class of mechanical systems, described by Euler-Lagrange equations of motion, subject to a set of holonomic and/or nonholonomic constraints in a unified fashion. Based on a QR-like decomposition of the constraint Jacobian, it is shown that the constraint-force free and reduced constrained motions of constrained mechanical systems can be naturally separated. A new hybrid control is proposed for the decomposed motions to achieve simultaneous, independent position and force tracking. Some comments about the applicability of main tracking result are given.     

基于降阶位置/力模型的机器人神经网络控制

双足机器人的双脚支撑期是实现其步行运动的重要过程,然而耦合的位置/力控制难以保证其稳定平滑运动.本文提出了一种基于降阶位置/力模型的机器人控制策略,整合了位置控制子空间模型和力控制子空间模型,通过模型降阶减小了控制器设计的复杂度,并采用神经网络自适应控制方法综合多控制目标,实现了双足机器人的平滑稳定控制并有效地抑制了系统外扰和参数不确定性的影响.最后,仿真算法验证了该控制方法和模型的有效性.     

Stability of hybrid position and force control for robotic manipulator with kinematics and dynamics uncertainties

Most research so far on hybrid position and force control laws of robotic manipulator has assumed that knowledge of kinematics is known exactly. In the presence of modeling errors, it is unknown whether the stability of the constrained robot system can still be ensured. In this paper, stability and setpoint control problems of constrained robot with kinematics and dynamics uncertainties are formulated and solved. We shall show that the manipulator end-effector's motion is asymptotically stable even in the presence of such uncertainties.     

Implementation of position–force and position–position teleoperator controllers with cable-driven mechanisms

Bilateral teleoperation involves the motion control of a slave mechanism with a master mechanism that is capable of reflecting the sensory information such as force and torque signals captured from the master mechanism. Normally, the master and slave mechanisms in a teleoperator system are physically separated and are connected via some communication interface. As technology in robotic mechanism design continuously develops, advanced teleoperator systems are emerging. From the handling of hazardous and delicate materials in nuclear decommissioning to medical applications such as orthopedic and laparoscopic surgery, the demand for high bandwidth and fine-force reflecting bilateral teleoperator systems has become more and more important. This paper focuses on the implementation of an advanced master–slave teleoperator system using cable-driven WAM and PHANToM devices. Special emphasis is placed on the pragmatic issues on the implementation based two different designs of the teleoperator control schemes and the performance of the system under these two teleoperator control schemes.     

Parameter optimization for decoupling controllers of 4WS vehicles

In this paper, performance analysis of physical models and parameter optimization of two typical decoupling controllers are considered. Firstly, new relationship between velocity and acceleration for the nonlinear performance is established. Then, for the decoupled quasi-linearized system, the parameter region is optimized, in which the damping is bigger than one and eigenvalues are smaller than any negative number. For the decoupled linearized system, the necessary and sufficient conditions, that overshoot and irritating are avoided and measurement-error disturbance is attenuated to under any positive number, are deduced. Simulations show that safety and comfort are improved obviously.     

Parameterization of the class of deadbeat controllers via thetheory of decoupling

A novel approach is presented for parameterizing the class of minimum-time deadbeat controllers (MTDC) through the minimum number of parameters. The approach is based on the theory of decoupling and the properties of square decouplable systems. The main result is a compact parametric form for the class of MTDC of a discrete-time system. Contrary to many existing techniques, no special assumption on the invertibility of the transition matrix is required     

Fixed modes in multivariable systems using constrained controllers

A general expression is derived relating an arbitrary output feedback controller to the resulting closed-loop characteristic polynomial in terms of suitably defined zero polynomials of the system. This expression is then used to characterize the fixed modes of a multivariable system with respect to controllers of any desired structure.     

Robotic visual servoing and robotic assembly tasks

Visual feedback has traditionally been used in the assembly process to a very limited extent. By incorporating high bandwidth visual feedback into the manipulator feedback loop, more flexible and adaptable robotic assembly systems can be developed. The authors present experimentally tested algorithms and propose solutions for the problem of dynamic sensor placement in assembly tasks     

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.     

Design of distributed controllers with constrained and noisy links

In this paper we consider some design aspects of distributed controllers that guarantee a ??_∞ performance level. In particular, we consider two design problems. First, is the case where, without loss of generality, there are two distributed subcontrollers connected to a (generalized) plant and the interest is placed in minimizing the number of noise‐free (and dynamics free) communication channels between the subcontrollers needed to provide a given performance. The second is the case where, given a distributed controller designed in the first case, communication noise is present and we seek an optimal choice of the communication signals to guarantee a performance level while keeping the communication signal to noise power limited. We take a linear matrix inequality (LMI) approach to provide solution procedures to these problems and present examples that demonstrate their efficiency. Copyright © 2006 John Wiley & Sons, Ltd.     

Perception of cloth in assistive robotic manipulation tasks

Natural Computing - Assistive robots need to be able to perform a large number of tasks that imply some type of cloth manipulation. These tasks include domestic chores such as laundry handling or...