Dual Mode Control of an Elastic Robotic Arm: Nonlinear Inversion and Stabilization by Pole Assignment

An approach to control of a class of nonlinear flexible robotic systems is presented. For simplicity, a robot arm (PUMA-type) with three rotational joints is considered. The third link is assumed to be elastic. An adaptive torquer control law is derived for controlling the joint angles. This controller includes a dynamic system in the feedback path, requires only joint angle and rate for feedback, and asymptotically decomposes the elastic dynamics into two subsystems representing the transverse vibrations of the elastic link in two orthogonal planes. To damp out the elastic vibration, a force control law using modal feedback is synthesized. The combination of the torque and force control laws accomplishes joint angle control and elastic mode stabilization.

Control of elastic robotic systems with rotational joints is considered. The control system design treats the large joint-angle maneuver problem separately from the terminal stabilization problem. First, a nonlinear adaptive control law is derived such that in the closed-loop system the joint-angles are precisely controlled to track reference trajectories. Once the joint angle enters the vicinity of the desired terminal value, a stabilizer designed using a linear model of the arm is switched to accomplish the final capture of the desired state. Extensive simulation results showed that in the closed-loop system accurate trajectory tracking and elastic mode stabilization can be accomplished.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Pole assignment is a well-established controller synthesis technique used in control engineering. An important drawback of the pole assignment technique is poor numerical accuracy of the resulting compensators especially for high order systems, when fixed precision arithmetic is used in calculations. Obviously there are several parameters that affect the performance of the pole assignment algorithms. It has been, for example, already shown that increasing the order of the system causes an exponential increase in the numerical errors made in pole assignment. In this paper, the effect of the ratio of real poles to all poles of the open-loop (and closed-loop) system (real pole ratio - RPR) to the performance of the pole assignment algorithms is investigated for the first time.

Kinematic modeling and control of a robot arm using unit dual quaternions

The so-called "New Space era" has seen a disruptive change in the business models and manufacturing technologies of launch vehicle companies. However, limited consideration has been given to the benefits that innovation in control theory can bring; not only in terms of increasing the limits of performance but also reducing mission preparation or "missionisation" efforts. Moreover, there is a gap between the current state-of-practice that still relies on linear controls and other modern control techniques that could bring relevant improvements in launcher attitude control; this is the case for nonlinear control algorithms, especially those based on Nonlinear Dynamic Inversion (NDI). NDI is a technique that basically 'cancels' the nonlinearities of a class of nonlinear systems, allowing for a single linear control law to be applied without the need for gain-scheduling across different operational points. Incremental NDI (INDI) is a variation of NDI that generates incremental commands and employs acceleration feedback to reduce model dependency, making it easier to design, and results in being more robust in closed-loop. While INDI has been applied successfully to several aerospace applications, its applicability to launch vehicles has not yet been adequately investigated. The objective of this paper is therefore to introduce and raise awareness of the INDI method among the launcher guidance, navigation, and control (GNC) community, showcasing its implementation on a representative launch ascent application scenario which highlights INDI's strengths and challenges. We present a new, practical approach for stability analysis of INDI for attitude control, and compare INDI with scheduled PD controllers with-and without angular acceleration estimates. Results show that, while INDI controllers are generally more sensitive to sensor noise and actuator delay than linear controllers, their potential benefits outweigh these limitations in terms of robustness and performance.

&lt;p&gt;The accelerated growth of an increasingly automated industry requires the use of autonomous robotic systems. However, the use of these systems commonly requires an enormous amount of sensors. In this paper we evaluate the performance of a new system for visual control of a selective compliance assembly robot arm (SCARA) robotic arm using a monocular depth map that only requires one monocular camera. This system aims to be an efficient alternative to reduce the number of sensors in the robotic arm area while maintaining the effectiveness of traditional vision algorithms that use stereoscopic architectures of cameras. For this purpose, this system is compared with representative state-of the-art vision algorithms focused on the control of robotic arms. The results are statistically analyzed, indicating that the algorithm proposed in this research has competitive performance compared to state-of-the-art robotic arm visual control algorithms only using a single monocular camera.&lt;/p&gt;

The unstable and nonlinear nature of small ducted fan unmanned aerial vehicles that can hover and transition to forward flight make the design of control systems for this type of vehicle challenging. In this paper a nonlinear dynamic inversion control system is designed and evaluated for a small ducted fan UAV. The approach taken completes a nonlinear dynamic inversion by incorporating experimental wind tunnel data and full state feedback. Special attention is given to the issue of robustness to plant uncertainty in both hover and forward flight. A discussion of the techniques used to design and optimize outer loop feedback regulators such that the system demonstrates good gust rejection and robustness to plant uncertainty is included. This paper also describes a method to control the velocity of the vehicle. Results demonstrating the simulated responses of the vehicle with the optimized control laws are presented.

Trying to record vibration of an elastic arm for identifying behavior of robot, is one of important case studies in mechatronic science. So in this paper designing an electrical interface with a six channel strain gage data logger, is presented. The high speed vibration of a flexible robotic arm compared to the low speed of software and hardware interface between the computer and experimental setup is one of the most important obstacles for measuring and control of such a systems. In this paper, a combination of using high speed digital to analog convertor (DAC) components on an electrical interface board and using National Instrument's LABVIEW software package is proposed as a solution for this problem. Dynamic modeling of the system is developed based on Gibbs-Appell (G-A) formulation and Assumed Mode Method (AMM). An experimental setup of a Two-link elastic robotic arm is prepared and the electrical interface board works between this experimental setup, user and computer. The input data by the electrical interface board are the number of mode shapes up to 4 for one-link elastic arm and 2 for two-link elastic arm and the profile of the input torque via time. Then these data transferred to the Elastic arm robotic system. Finally user can see the vibration of the elastic link in graphical interface environment and model validation carried out by comparing both experimental and theoretical results.

In this paper, the following three topics are dealt with : (i) vibration control method of flexible robotic arms in precise positioning control to suppress bending vibrations during and after rotation of arms, based on the hybrid model, where an arm is simply modelled as an elastic beam, including aspects of actuator energy input and control performance, (ii) application of elastic arms to contouring control with constant contact force, as an example of force feedback control, (iii) a simple method of reliable control system structure on the basis of the fault tolerant configuration, employing dual processor control system and fault detection system for the safety and the reliability of robotic operations, and finally those experimental results in simplified models, based on the results obtained in the above.

Continuous estimation of joint angles based on surface electromyography (sEMG) signals is a promising method for naturally controlling prosthetic limbs and assistive devices. However, conventional methods based on neural networks have limitations such as long training times and calibration burdens. This study investigates the use of an echo state network (ESN), which enables fast training, to estimate wrist joint angles from sEMG. Five participants mimicked the motion of a 1-degree-of-freedom robotic arm by flexing and extending their wrist, while sEMG signals from the wrist flexor and extensor muscles and the robotic arm’s angle were recorded. The ESN was trained to take two sEMG channels as input and the robotic joint angle as output. High-accuracy estimation with a median coefficient of determination R2 = 0.835 was achieved for representative ESN parameters. Additionally, the effects of the reservoir size, spectral radius, and time constant on estimation accuracy were evaluated using data from a single participant. Furthermore, online estimation of joint angles based on sEMG signals enabled successful control of the robotic arm. These results suggest that sEMG-based ESN estimation offers fast, accurate joint control and could be useful for prosthetics and fundamental studies on body perception.

This paper presents a transformation-based robust nonlinear control design framework based on the concepts of incremental nonlinear dynamic inversion (INDI) and quasi-linear parameter-varying (q-LPV) control. The duality between these popular control design paradigms is investigated. Control-oriented q-LPV model representations of INDI and nonlinear dynamic inversion (NDI)-based closed-loop systems are presented for various inversion strategies, which creates a basis for robust synthesis and analysis of INDI and NDI-based designs in the LPV sense. This includes extensions to singular perturbations that limit exact inversion in reality. The presented approach is demonstrated in a design case study for a nonlinear aeroservoelastic system, where INDI-based controllers are synthesized and quantitatively compared with direct q-LPV control based on linear fractional transformations.

Legged mobile manipulators are receiving much more attention. Mobile platforms can infinitely expand the workspace of robotic arms, providing more possibilities for robot application scenarios. Compared with wheeled mobile manipulators, legged mobile manipulators have higher requirements for cooperative control of legged robots and robotic arms. This work decouples the control of the robotic arm and the legged robot. On the legged robot side, we explicitly estimate the wrench exerted by the robotic arm on the base and bring it into the legged robot’s dynamics, and then use a nonlinear model predictive controller (NMPC) to control the legged robot. On the robotics arm side, we adopt an impedance controller to realize the end-effector’s force control, and the introduction of impedance control has improved the safety and interactivity of legged mobile manipulators. We conducted experiments on physical robot to compare the differences between decoupled control and independent control, and the results show that the stability and robustness of robot systems have improved using decoupled control.

Nonlinear Inverse and Predictive End Point Trajectory Control of Flexible Macro-Micro Manipulators

The question of control and stabilization of flexible space robots is considered. Although, this approach is applicable to space robots of other configurations, for definiteness, a flexible planar two-link robot, mounted on a rigid floating platform in space, is considered. The robotic arm has two revolute joints and its links undergo elastic deformation in the plane of rotation. Based on nonlinear inversion technique, a control law is derived for controlling output variables describing the position and orientation of the platform and the joint angles of the robot. Although, the inverse controller accomplishes reference trajectory tracking, it excites the elastic modes of the arm. Using linear quadratic optimal control theory, a composite stabilizer for stabilization of the rigid and flexible modes and a decoupled flexible mode stabilizer are designed for regulating the end point of the robot to the target point and vibration suppression. Stabilization using only elastic mode velocity feedback is also considered. For large maneuvers, first the inverse controller is active, and the stabilizer is switched for regulation when the motion of the robot lies in the neighborhood of the terminal equilibrium state. Simulation results are presented to show that in the closed-loop system including the inverse controller and the stabilizer, trajectory tracking and stabilization of elastic modes are accomplished.

This article addresses the problem of control of robotic arm with a hysteretic joint behaviour. The mechanical design of the one-degree of freedom robotic arm is presented where the joint is actuated by a Shape Memory Alloy (SMA) wire. The SMA wire based actuation of the joint makes the robotic arm lightweight but at the same time introduces hysteresis type nonlinearities. The nonlinear dynamic model of the robotic arm is introduced and an Adaptive control solution is presented to perform the joint reference tracking in the presence of unknown hysteresis behaviour. The Lyapunov stability analysis of the closed loop system is presented and finally proposed adaptive control solution is validated through simulation study on the proposed nonlinear hysteretic robotic arm.