A decentralized kinematic control architecture for collaborative and cooperative multi-arm systems

In this paper a two-layer decentralized framework for kinematic control of cooperative and collaborative multi-robot systems is developed. The motion of the system is specified at the workpiece level, by adopting a task-oriented formulation for cooperative tasks. The first layer computes the motion of the single arms in the system. In detail, the control unit of each robot computes the end-effector motion references in a decentralized fashion on the basis of the knowledge of the assigned cooperative task and the motion references computed by its neighbors. Then, in the second layer, each control unit computes the reference joint motion of the corresponding manipulator from the end-effector reference motion. The approach is, then, tested in simulation on a work-cell composed by several manipulators, and experimentally on a dual-arm kinematically redundant work-cell composed by industrial manipulators.     

Neural-Network-Based Terminal Sliding-Mode Control of Robotic Manipulators Including Actuator Dynamics

A neural-network-based terminal sliding-mode control (SMC) scheme is proposed for robotic manipulators including actuator dynamics. The proposed terminal SMC (TSMC) alleviates some main drawbacks (such as contradiction between control efforts in the transient and tracking errors in the steady state) in the linear SMC while maintains its robustness to the uncertainties. Moreover, an indirect method is developed to avoid the singularity problem in the initial TSMC. In the proposed control scheme, a radial basis function neural network (NN) is adopted to approximate the nonlinear dynamics of the robotic manipulator. Meanwhile, a robust control term is added to suppress the modeling error and estimate the error of the NN. Finite time convergence and stability of the closed loop system can be guaranteed by Lyapunov theory. Finally, the proposed control scheme is applied to a robotic manipulator. Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.      

A Robust Position and Force Control Strategy for 7-DOF Redundant Manipulators

This paper is concerned with robust position and contact force control for 7-DOF redundant robot arms. An outer-inner loop controller, called the augmented hybrid impedance control scheme is developed. A 6-DOF force/torque sensor is used to measure the interaction forces. These are fed back to the outer-loop controller that implements either a force or an impedance controller in each of the 6 DOF of the tool frame. The force controller is provided with a force set point, and desired inertia and damping are introduced in the force control loop to improve transient performance. The inner loop consists of a Cartesian-level potential difference controller, a redundancy resolution scheme at the acceleration level, and a joint-space inverse dynamics controller. Experimental results for two 7-DOF robot arms (redundant, dextrous, isotropically enhanced, seven-turning pair robot (REDIESTRO) and Mitsubishi PA10-7C) are given to illustrate the performance of the force control strategy. A successful application of the proposed scheme to a surface cleaning task is described using the REDIESTRO, while position and force tracking experiments are described for the Mitsubishi PA10-7C robot.     

An admittance based hierarchical control framework for dual-arm cobots

Dual-arm robotic platforms have solid arguments to match the growing need for versatility in the industry. Coupling the control of two manipulators for cooperative purposes enlarges the scope of feasible operations, while adding perception capabilities allows to navigate in dynamic environments. In this respect, we propose a complete online kinematic control framework for dual-arm robots operating in unstructured industrial settings. We base our approach on admittance control in the cooperative task space. Regulating internal and external efforts offer safe bimanual task execution and enables physical interaction. We implement a hierarchical quadratic programming architecture that applies a prioritization of tasks: most efforts are concentrated on the proper tracking of relative motions of the arms, which is the most critical for safety reasons. We demonstrate the performance of our framework through a “teaching-by-demonstration” experiment on the dual-arm mobile cobot BAZAR.     

Adaptive two-loop Voltage-mode control of DC-DC switching converters

A new two-loop control scheme for voltage-mode control (VMC) of dc-dc switching converters is presented. The proposed method adds a high-gain robust loop with two controllers to the conventional VMC loop, achieving an analog "adaptive" loop in which the "equivalent voltage regulator" varies with the changing power stage parameters given as follows: 1) input voltage; 2) load; and 3) component tolerances. The loop significantly improves the disturbance rejection of the control system, i.e., closed-loop output impedance and audiosusceptibility while preserving the stability and the loop gain crossover frequency to a significant extent. Both the small-signal analysis and the experimental results carried out on a buck converter demonstrate the superiority of the proposed scheme with respect to the conventional single loop.     

机械臂变指数趋近律滑模控制律设计

针对机械臂滑模控制中存在抖振的问题,采用改进趋近律的思想来设计滑模控制律,以达到有效抑制抖振的目的。在对滑模控制的特点和常用的指数趋近律进行分析的基础上,提出了一种变指数趋近律,并对其趋近性能进行了分析;结合机械臂动力学模型和改进的趋近律设计了相应的滑模控制策略,对其控制效果进行了验证。仿真结果表明,该控制策略不仅有效地抑制了系统的抖振,而且保证了机械臂系统对期望轨迹的快速跟踪性,进而提高了机械臂的工作性能。     

A Solution to the Accuracy/Robustness Dilemma in Impedance Control

It has been reported that, in impedance control, there exists a dilemma between impedance accuracy and robustness against modeling error. As a solution to this dilemma, an accurate and robust impedance control technique is developed based on internal model control structure and time-delay estimation: the former injects desired impedance and corrects modeling error, the latter estimates and compensates the nonlinear dynamics of robot manipulators. Owing to the simple structure, the proposed control is designed without requiring entire model computation or complex algorithms. In 2-DOF SCARA-type robot experiments, the accuracy and robustness of the proposed control are confirmed through comparisons with other competent controllers including impedance control with disturbance observer.     

Impedance control of an active suspension system

A novel control system is developed to control dynamic behavior of a vehicle subject to road disturbances. The novelty of this paper is to apply the impedance control on an active vehicle suspension system operated by a hydraulic actuator. A relation between the passenger comfort and vehicle handling is derived using the impedance parameters. The impedance control law is simple, free of model and can be applied for a broad range of road conditions including a flat road. Impedance control is achieved through two interior loops which are force control of the actuator by feedback linearization and fuzzy control loop to track a desired body displacement provided by the impedance rule. The system stability is analyzed. A quarter-car model of suspension system and a nonlinear model of hydraulic actuator are used to simulate the control system.     

A fully neural-network-based planning scheme for torqueminimization of redundant manipulators

The aim of this paper is to develop a new method for minimizing joint torques of redundant manipulators in the Chebyshev sense and to present a fully neural-network-based computational scheme for its implementation. Minimax techniques are used to determine the null space acceleration vector which can guarantee to minimize the maximum joint torque. For real-time implementation, we transform the proposed method into a computation of a recurrent neural network. At each time step, the neural network is adopted for both the solution of the least-norm joint acceleration and the determination of the optimum null space acceleration vector. Compared with previous torque minimization schemes, the proposed method enables more direct monitoring and control of the magnitudes of the individual joint torques than does the minimization of the sum of squares of the components. Simulation results demonstrate that the proposed method is effective for the torque minimization control of redundant manipulators     

Experimental Evaluation of Dynamic Redundancy Resolution in a Nonholonomic Wheeled Mobile Manipulator

Mobile manipulators derive significant novel capabilities for enhanced interactions with the world by merging mobility with manipulation. However, a careful resolution of the redundancy and active control of the reconfigurability, created by the surplus articulated DOFs and actuation, are the keys to unlocking this potential. Nonholonomic wheeled mobile manipulators, formed by mounting manipulator arms on disc-wheeled mobile bases, are a small but important subclass of mobile manipulators. The primary control challenges arise due to the dynamic-level coupling of the nonholonomy of the wheeled mobile bases with the inherent kinematic and actuation redundancy within the articulated chain. The solution approach in this paper builds upon a dynamically consistent and decoupled partitioning of the articulated system dynamics between the external (task) space and internal (null) space. The independent controllers, developed within each decoupled space, facilitate active internal reconfiguration, in addition to resolving redundancy at the dynamic level. Specifically, two variants of null-space controllers are implemented to improve disturbance rejection and active reconfiguration during performance of end-effector tasks by a primary end-effector impedance mode controller. These algorithms are evaluated within an implementation framework that emphasizes both virtual prototyping and hardware-in-the-loop testing with representative case studies.     

稳定回路智能分区PID控制方案研究

目前工程上普遍采用经典PID控制方法对稳定回路进行控制。但是,由于非线性因素的存在,实际产品往往高频去耦指标较差。以某型系统结构为研究对象,不基于模型的辨识,在模糊PID的基础上,提出并设计了一种智能分区PID控制方案。通过Simulink仿真验证,与传统PID控制方法相比,智能分区PID控制方案对稳定回路的动态特性有明显的改善,对齿隙等非线性因素有很好的抑制能力。     

The Tricept robot: dynamics and impedance control

The Tricept is a novel industrial robot characterized by a hybrid kinematic design featuring a three-degrees-of-freedom (3-DOF) structure of parallel type and a 3-DOF spherical wrist. In this work the authors focus on the derivation of a dynamic model to be used for both simulation and control purposes. Two different approaches are discussed and compared in terms of inverse dynamics computation. Then, a model-based control is derived aimed at enforcing a 6-DOF impedance behavior at the end effector to manage interaction with the environment. Simulation results are presented to evaluate the accuracy of an approximate dynamic model computation as well as to test the effectiveness of the proposed impedance control strategy.     

Computationally Efficient Predictive Robot Control

Conventional linear controllers (PID) are not really suitable for the control of robot manipulators due to the highly nonlinear behavior of the latter. Over the last decades, several control methods have been proposed to circumvent this limitation. This paper presents an approach to the control of manipulators using a computationally-efficient-model-based predictive control scheme. First, a general predictive control law is derived for position tracking and velocity control, taking into account the dynamic model of the robot, the prediction and control horizons, and also the constraints. However, the main contribution of this paper is the derivation of an analytical expression for the optimal control to be applied that does not involve a numerical procedure, as opposed to most predictive control schemes. In the last part of the paper, the effectiveness of the approach for the control of a nonlinear plant is illustrated using a direct-drive pendulum, and then, the approach is validated and compared to a PID controller using an experimental implementation on a 6-DOF cable-driven parallel manipulator.     

A neural network compensator for uncertainties of roboticsmanipulators

A neural network controller for trajectory control of robotic manipulators that is used not to internalize the inverse dynamic model of the controlled object but to compensate only the uncertainties of the robotic manipulator is presented. Its performance is compared with that of the conventional adaptive scheme. The results show the ability of the neural network controller to adapt to unstructured effects. A learning method for the neural network compensator with true teaching signals is shown. The tracking error of the robotic manipulator was greatly reduced when this controller was used     

Novel three-controller average current mode control of DC-DC PWMconverters with improved robustness and dynamic response

This paper presents a novel average current mode control (ACC) strategy for the control of pulse width modulated (PWM) DC-DC converters, which represents a drastic improvement over conventional ACC. This new method consists of the addition of an auxiliary controller into the control loop, besides the current and voltage regulators. The model-based auxiliary controller can increase the closed loop small-signal bandwidth of Buck derived converters, preserving loop gain crossover frequency and stability margins over significant changes of the power stage passive elements values, the load and the line voltage. Moreover, this control scheme shows much better disturbance rejection properties, i.e., closed loop impedance and audiosusceptibility, than conventional ACC. From a control theory point of view, robust performance is achieved preserving stability. A Buck prototype has been experimentally tested with different LC output filters, line and load conditions, including discontinuous conduction mode. Measurements of the small signal frequency response of the converter have been carried out, showing the improvement achieved by the proposed control scheme. The empirical large signal response of the converter under load steps is also shown in order to validate the concept     

Damping a hybrid stepping motor with estimated position and velocity

It is well known that microstepping reduces the resonance behavior of stepping motors since the rotor moves in a sequence of very small steps. However, the under-damped nature of the motor does not change. In this paper, a scheme that uses microstepping and closed loop position control to stabilize and reduce resonance damping of the motor is proposed. The motor currents are controlled in a frame rotating synchronously with the excitation frequency. The d-axis current provides the torque to oppose the external load, and the q-axis current provides the transient torque to damp the motor. The motor velocity and position are estimated via an observer that tracks the angle of the motor back EMF voltage. The response of the closed loop system is independent of the external load level. Both simulation and experimental results have shown that the proposed control scheme is very effective in damping out the resonance of microstepping-controlled motors.     

Image reconstruction using interval simulated annealing in electrical impedance tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.     

Single-phase high power factor pre-regulator with three-level modulation scheme

A control scheme for the single-phase three-level pulse-width modulation active rectifier is proposed. A hysteresis current control scheme is used to draw the sinusoidal line current in phase with the mains voltage. The line current command is derived from a voltage controller and a phase-locked loop circuit. The blocking voltage of each power device is clamped to half of the DC-link voltage in the proposed active rectifier. In order to generate the three-level voltage pattern on the DC side of the active rectifier, the region detector of the line voltage, capacitor voltage compensator and hysteresis current comparator are employed in the adopted control algorithm to achieve high input power factor and low current distortion. To investigate the proposed control algorithm, the adopted rectifier is simulated and experimental tests from a laboratory prototype undertaken.     

Small signal analysis of the LCC-type parallel resonant converterusing discrete time domain modeling

Discrete state-space modeling of the LCC-type parallel resonant power converter is presented. Using these large signal equations, small signal modeling of the power converter is obtained. Multiple loops have been used for the closed loop operation. State variable feedback control has been integrated with the linear small signal state-space model and the associated control aspects are studied. The small signal state-space model has been used to study the small signal behavior of the power converter for open loop and closed loop operation for parameters like control to output transfer function, audio-susceptibility and output impedance. Key theoretical results have been experimentally verified     

Robust average current-mode control of multimodule parallel DC-DCPWM converter systems with improved dynamic response

This paper presents a novel average current-mode control (ACC) strategy for the control of multimodule parallel pulsewidth modulation DC-DC converters, which represents a drastic improvement over conventional ACC. This new method consists of the addition of an auxiliary controller into the control loop, besides the current and voltage regulators. The reference-model-based auxiliary controller improves the robustness of the ACC dynamics in buck-derived distributed power systems, preserving loop gain crossover frequency and stability margins over significant changes of the number of connected modules, the load and the line voltage. Moreover, this control scheme shows much better disturbance rejection properties, i.e., closed-loop output impedance and audiosusceptibility, than conventional ACC. From a control theory point of view robust performance is achieved, preserving stability. A multimodule buck prototype has been experimentally tested with different numbers of modules on stream, line, and load conditions, including discontinuous conduction mode. Measurements of the small-signal frequency response of the converter have been carried out, showing the improvement achieved by the proposed control scheme. The empirical large-signal response of the converter under load steps is also shown in order to validate the concept