Adaptive Neural Network Fixed-Time Control Design for Bilateral Teleoperation With Time Delay.

In this article, subject to time-varying delay and uncertainties in dynamics, we propose a novel adaptive fixed-time control strategy for a class of nonlinear bilateral teleoperation systems. First, an adaptive control scheme is applied to estimate the upper bound of delay, which can resolve the predicament that delay has significant impacts on the stability of bilateral teleoperation systems. Then, radial basis function neural networks (RBFNNs) are utilized for estimating uncertainties in bilateral teleoperation systems, including dynamics, operator, and environmental models. Novel adaptation laws are introduced to address systems' uncertainties in the fixed-time convergence settings. Next, a novel adaptive fixed-time neural network control scheme is proposed. Based on the Lyapunov stability theory, the bilateral teleoperation systems are proved to be stable in fixed time. Finally, simulations and experiments are presented to verify the validity of the control algorithm

A Tele-Operated Display With a Predictive Display Algorithm

Tele-operated display systems with head mounted displays (HMD) are becoming popular as visual feedback systems for tele-operation systems. However, the users are suffered from time-varying bidirectional delays caused by the latency and limited bandwidth of wireless communication networks. Here, we develop a tele-operated display system and a predictive display algorithm allowing comfortable use of HMDs by operators of tele-operation systems. Inspired by the kinematic model of the human head-neck complex, we built a robot neck-camera system to capture the field of view in any desired orientation. To reduce the negative effects of the time-varying bidirectional communication delay and operation delay of the robot neck, we developed a predictive display algorithm based on a kinematic model of the human/robot neck-camera system, and a geometrical model of a camera. Experimental results showed that the system provide predicted images with high frame rate to the user

Sensors Allocation and Observer Design for Discrete Bilateral Teleoperation Systems with Multi-Rate Sampling

This study addresses sensor allocation by analyzing exponential stability for discrete-time teleoperation systems. Previous studies mostly concentrate on the continuous-time teleoperation systems and neglect the management of significant practical phenomena, such as data-swap, the effect of sampling rates of samplers, and refresh rates of actuators on the system’s stability. A multi-rate sampling approach is proposed in this study, given the isolation of the master and slave robots in teleoperation systems which may have different hardware restrictions. This architecture collects data through numerous sensors with various sampling rates, assuming that a continuous-time controller stabilizes a linear teleoperation system. The aim is to assign each position and velocity signals to sensors with different sampling rates and divide the state vector between sensors to guarantee the stability of the resulting multi-rate sampled-data teleoperation system. Sufficient Krasovskii-based conditions will be provided to preserve the exponential stability of the system. This problem will be transformed into a mixed-integer program with LMIs (linear matrix inequalities). These conditions are also used to design the observers for the multi-rate teleoperation systems whose estimation errors converge exponentially to the origin. The results are validated by numerical simulations which are useful in designing sensor networks for teleoperation systems

An adaptive fuzzy control for human-in-the-loop operations with varying communication time delays

Time delay, especially varying time delay, is always an important factor affecting the stability to the human-in-the-loop system. Previous research usually focuses on the performance of the internal signal transmission part, but rarely considers the whole system with human and environmental factors comprehensively. For the problem, we investigate this issue by using an improved proportional-derivative-like plus damping (PD-like + d) control method, the derivative term of which is calculated based on the estimation of time delays. An embedded adaptive fuzzy logic systems (FLS)-based observer is developed to estimate and compensate for the errors caused by time delay estimations and uncertain force/ torque measuring errors. The advantages of the proposed control scheme are discussed by building an environmental input energy function and the effectiveness is also verified by the comparative simulations. The results show that under the same simulation conditions, the follower can track the leader's movements well, and the energy introduced into the environment is the same as that of the leader, which means the extra energy is dissipated to enable the object to be manipulated as desired by the leader side

Design of feedforward and feedback position control for passive bilateral teleoperation with delays

Bilateral teleoperation systems connected to computer networks such as the internet must be able to operate with varying time delays since such systems can easily become unstable. A passivity concept has been used as the framework to solve the stability problem in the bilateral control of teleoperation systems. Passivity and tracking performance are recovered using a control architecture that incorporates time varying gains into the transmission path, feedforward, and feedback position control. The proposed architecture has an inner component that can accommodate any configuration but still remain stable and passive even with varying time delay. The simulation results for a single degree of freedom master/slave system demonstrate the performance of the proposed control architecture

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Design, Fabrication, and Control of an Upper Arm Exoskeleton Assistive Robot

Stroke is the primary cause of permanent impairment and neurological damage in the United States and Europe. Annually, about fifteen million individuals worldwide suffer from stroke, which kills about one third of them. For many years, it was believed that major recovery can be achieved only in the first six months after a stroke. More recent research has demonstrated that even many years after a stroke, significant improvement is not out of reach. However, economic pressures, the aging population, and lack of specialists and available human resources can interrupt therapy, which impedes full recovery of patients after being discharged from hospital following initial rehabilitation. Robotic devices, and in particular portable robots that provide rehabilitation therapy at home and in clinics, are a novel way not only to optimize the cost of therapy but also to let more patients benefit from rehabilitation for a longer time. Robots used for such purposes should be smaller, lighter and more affordable than the robots currently used in clinics and hospitals. The common human-machine interaction design criteria such as work envelopes, safety, comfort, adaptability, space limitations, and weight-to-force ratio must still be taken into consideration.;In this work a light, wearable, affordable assistive robot was designed and a controller to assist with an activity of daily life (ADL) was developed. The mechanical design targeted the most vulnerable group of the society to stroke, based on the average size and age of the patients, with adjustability to accommodate a variety of individuals. The novel mechanical design avoids motion singularities and provides a large workspace for various ADLs. Unlike similar exoskeleton robots, the actuators are placed on the patient\u27s torso and the force is transmitted through a Bowden cable mechanism. Since the actuators\u27 mass does not affect the motion of the upper extremities, the robot can be more agile and more powerful. A compact novel actuation method with high power-to-weight ratio called the twisted string actuation method was used. Part of the research involved selection and testing of several string compositions and configurations to compare their suitability and to characterize their performance. Feedback sensor count and type have been carefully considered to keep the cost of the system as low as possible. A master-slave controller was designed and its performance in tracking the targeted ADL trajectory was evaluated for one degree of freedom (DOF). An outline for proposed future research will be presented