Deals with adaptive control of a class nonlinear dynamic systems preceded by unknown backlash-like hysteresis nonlinearities, where the is modeled differential equation. By exploiting solution properties equation and combining those techniques, robust algorithm developed without constructing inverse. The new law ensures global stability system achieves both stabilization tracking to within desired precision. Simulations performed on illustrate clarify approach.

Piezo-actuated stages have become more and promising in nanopositioning applications due to the excellent advantages of fast response time, large mechanical force, extremely fine resolution. Modeling control are critical achieve objectives for high-precision motion. However, piezo-actuated themselves suffer from inherent drawbacks produced by creep hysteresis nonlinearities vibration caused lightly damped resonant dynamics, which make modeling such systems challenging. To address these...

Smart actuators employed in micropositioning are known to exhibit strong hysteresis nonlinearities, which may be asymmetric and could adversely affect the positioning accuracy. In this paper, analytical inverse of a generalized Prandtl-Ishlinskii model is formulated compensate for nonlinearities smart actuators. The was modified ensure its continuity, validity characterizing different properties briefly demonstrated by comparing responses with measured data magnetostrictive, shape memory...

An adaptive tracking control architecture is proposed for a class of continuous-time nonlinear dynamic systems, which an explicit linear parameterization the uncertainty in dynamics either unknown or impossible. The employs fuzzy are expressed as series expansion basis functions, to adaptively compensate plant nonlinearities. Global asymptotic stability algorithm established Lyapunov sense, with errors converging neighborhood zero. Simulation results unstable included demonstrate that...

Robots with coordinated dual arms are able to perform more complicated tasks that a single manipulator could hardly achieve. However, rigorous motion precision is required guarantee effective cooperation between the arms, especially when they grasp common object. In this case, internal forces applied on object must also be considered in addition external forces. Therefore, prescribed tracking performance at both transient and steady states first specified, then, controller synthesized...

Mobile robots tracking a reference trajectory are constrained by the motion limits of their actuators, which impose requirement for high autonomy driving capabilities in robots. This paper presents model predictive control (MPC) scheme incorporating neural-dynamic optimization to achieve nonholonomic mobile (NMRs). By using derived tracking-error kinematics robots, proposed MPC approach is iteratively transformed as quadratic programming (QP) problem, and then primal-dual neural network used...

This paper presents a modified Prandtl-Ishlinskii (P-I) (MPI) model for the asymmetric hysteresis description and compensation of piezoelectric actuators. Considering fact that classical P-I (CPI) is only efficient symmetric description, MPI proposed to describe nonlinearity piezoceramic actuators (PCAs). Different from commonly used approach development models by replacing play operator with complex nonlinear operators, still utilizes as elementary operator, while generalized input function...

In this paper, a novel control scheme is developed for teleoperation system, combining the radial basis function (RBF) neural networks (NNs) and wave variable technique to simultaneously compensate effects caused by communication delays dynamics uncertainties. The system set up with TouchX joystick as master device simulated Baxter robot arm slave robot. haptic feedback provided human operator sense interaction force between environment when manipulating stylus of joystick. To utilize...

This paper presents adaptive impedance control of an upper limb robotic exoskeleton using biological signals. First, we develop a reference musculoskeletal model the human and experimentally calibrate to match operator's motion behavior. Then, proposed novel algorithm transfers stiffness from operator through surface electromyography (sEMG) signals, being utilized design optimal model. Considering unknown deadzone effects in robot joints absence precise knowledge robot's dynamics, neural...

Due to strongly coupled nonlinearities of the grasped dual-arm robot and internal forces generated by objects, control with uncertain kinematics dynamics raises a challenging problem. In this paper, an adaptive fuzzy scheme is developed for robot, where approximate Jacobian matrix applied address kinematic control, while decentralized logic controller constructed compensate robotic arms manipulated object. Also, novel finite-time convergence parameter adaptation technique estimation...

To perform power augmentation tasks of a robotic exoskeleton, this paper utilizes fuzzy approximation and designed disturbance observers to compensate for the torques caused by unknown input saturation, errors, viscous friction, gravity, payloads. The proposed adaptive control with updated parameters' mechanism additional torque inputs using are exerted into exoskeleton via feedforward loops counteract disturbances. Through such an approach, system does not need any requirement built-in...

In this paper, a general skeleton on modeling, controller design, and applications of the piezoelectric positioning stages is presented. Toward framework, model first proposed to characterize dynamic behaviors stage, including frequency response voltage-charge hysteresis nonlinear electric behavior. To illustrate validity model, backlash-like adopted as one models describe effect, which confirmed by experimental tests. Thus, developed provides frame for design. As an illustration aspect,...

This paper describes a novel development of lower limber exoskeleton for physical assistance and rehabilitation. The developed is motorized leg device having total 4 DOF with hip, knee, ankle actuated in the sagittal plane. applies forces learns impedance parameters both robot human. An adaptive control scheme by incorporating learning approaches into system to help movement on desired periodic trajectory handle uncertainties known periods. proposed approach does not require muscle model can...

It has been established that the transfer of human adaptive impedance is great significance for physical human-robot interaction (pHRI). By processing electromyography (EMG) signals collected from muscles, limb could be extracted and transferred to robots. The existing interfaces rely only on visual feedback and, thus, may insufficient skill in a sophisticated environment. In this paper, haptic mechanism introduced result muscle activity would generate EMG natural manner, order achieve...

In this paper, two upper limbs of an exoskeleton robot are operated within a constrained region the operational space with unidentified intention human operator's motion as well uncertain dynamics including physical limits. The new human-cooperative strategies developed to detect subject's movement efforts in order make behavior flexible and adaptive. extracted from measurement muscular effort terms applied forces/torques can be represented derive reference trajectory his/her limb using...

This paper investigates the distributed finite-time fault-tolerant containment control problem for multiple unmanned aerial vehicles (multi-UAVs) in presence of actuator faults and input saturation. The sliding-mode observer (SMO) is first developed to estimate reference each follower UAV. Then, based on estimated knowledge, controller recursively designed guide all UAVs into convex hull spanned by trajectories leader with help a new set error variables. Moreover, unknown nonlinearities...

Control of nonlinear systems preceded by unknown hysteresis nonlinearities is a challenging task and has received increasing attention in recent years due to growing industrial demands involving varied applications. In the literature, many mathematical models have been proposed describe nonlinearities. The challenge addressed here how fuse those with available robust control techniques basic requirement stability system. purpose note show such possibility using Prandtl-Ishlinskii (PI) model....

This paper concerns a problem of robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> control for class uncertain nonlinear networked systems (NCSs), which can be represented by T-S fuzzy model with uncertainties. Both network-induced delay and packet dropout are addressed. The controller design method is presented based on delay-dependent approach, the gain matrices obtain solving set linear matrix inequalities (LMIs). Moreover,...

Smart actuators, such as shape memory alloy (SMA) and magnetostrictive exhibit saturation nonlinearity hysteresis that may be symmetric or asymmetric. The Prandtl–Ishlinskii model employing classical play operators has been used to describe the properties of smart actuators are in nature. In this study, application a generalized operator capable characterizing well asymmetric with output is explored formulating model. employs different envelope functions under increasing decreasing inputs...

Recently, through the use of parameterized fuzzy approximators, various adaptive control schemes have been developed to deal with nonlinear systems whose dynamics are poorly understood. An important class approximators is constructed using radial basis function (RBF) as a membership function. However, some tuneable parameters in RBF appear nonlinearly and determination law for such nontrivial task. In this paper, we propose new method an effort tune all thereby reducing approximation error...

This paper presents fuzzy approximation-based adaptive backstepping control of an exoskeleton for human upper limbs to provide forearm movement assistance so that a can track any continuous desired trajectory (or constant setpoint) in the presence parametric/functional uncertainties, unmodeled dynamics, actuator and/or disturbances from environments. Given trajectories positions, developed control, approximators are used estimate dynamical uncertainties human-robot system, and iterative...

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties multiple mobile manipulators carrying a common object cooperative manner. Firstly, concise dynamics systems consisting single master robot, coordinated slave robots, the are developed task space. To handle asymmetric time-varying communication channels unknown dead zones, nonlinear system transformed into two...