Flexible robotic endoscopy for treating gastrointestinal neoplasms

Therapeutic flexible endoscopic robotic systems have been developed primarily as a platform for endoscopic submucosal dissection(ESD)in the treatment of earlystage gastrointestinal cancer.Since ESD can only be performed by highly skilled endoscopists,the goal is to lower the technical hurdles to ESD by introducing a robot.In some cases,such robots have already been used clinically,but they are still in the research and development stage.This paper outlined the current status of development,including a system by the author’s group,and discussed future challenges.

Adaptive Fuzzy Backstepping Tracking Control for Flexible Robotic Manipulator

In this paper,an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator system.The considered system contains unknown nonlinearfunction and actuator saturation.Fuzzy logic systems(FLSs)and a smooth function are used to approximate the unknownnonlinearities and the actuator saturation,respectively.By com-bining the command-filter technique with the backsteppingdesign algorithm,a novel adaptive fuuzy tracking backsteppingcontrol method is developed.It is proved that the adaptive fuuzycontrol scheme can guarantee that all the variables in the closed-loop system are bounded,and the system output can track thegiven reference signal as close as possible.Simulation results areprovided to illustrate the effectiveness of the proposed approach.

Bionic autonomous learning control of a two-wheeled self-balancing flexible robot

This paper presents an OCPA （operant conditioning probabilistic automaton） bionic autonomous learning system based on Skinner＇s operant conditioning theory for solving the balance control problem of a two-wheeled flexible robot. The OCPA learning system consists of two stages： in the first stage, an operant action is selected stochastically from a set of operant actions and then used as the input of the control system; in the second stage, the learning system gathers the orientation information of the system and uses it for optimization until achieves control target. At the same time, the size of the operant action set can be automatically reduced during the learning process for avoiding little probability event. Theory analysis is made for the designed OCPA learning system in the paper, which theoretically proves the convergence of operant conditioning learning mechanism in OCPA learning system, namely the operant action entropy will converge to minimum with the learning process. And then OCPA learning system is applied to posture balanced control of two-wheeled flexible self-balanced robots. Robot does not have posutre balanced skill in initial state and the selecting probability of each operant in operant sets is equal. With the learning proceeding, the selected probabilities of optimal operant gradually tend to one and the operant action entropy gradually tends to minimum, and so robot gradually learned the posture balanced skill.

The Controllability of Cartesian Flexible Robot System

The control system of X-Y Catesian flexible robot is considered in present paper.We have established the evolution equation model in an appropriate Hilbert space for the system of one-link flexible arm with payload, and used operator semigroup approach to have proved the controllability of the closeloop system.

DYNAMIC ANALYSIS OF FLEXIBLE-LINK AND FLEXIBLE-JOINT ROBOTS

The dynamic modeling and simulation of an N-flexible-link and N-flexiblejoint robot is reported. Each flexible joint is modeled as a linearly elastic torsional spring and the approach of assumed modes is adopted to describe the deformation of the flexiblelink. The complete governing equations of motion of the flexible-link-joint robots are derived via Kane＇s method. An illustrative example is given to validate the algorithm presented and to show the effects of flexibility on the dynamics of robots.

Sliding Mode Control in a Nonlinear Flexible Robot System

This paper is devoted to the investigation of variable structure control in a nonlinear flexible robot system.With the help of the theory of functional analysis and the operator semigroup,we have proved that the given nonlinear flexible robot system is exponential stable under the appropriate sliding mode control.

Design of Robust Controller for Flexible Joint Robot with Nonlinear Friction Characteristics

A robust controller method for flexible joint robot considering the effect caused by nonlinear friction was presented.The nonlinear friction was denoted as inverse additive output uncertainty relative to the nominal model in our work,based on which the describing function was analyzed in frequency domain,and the weighting function of nonlinear friction was further calculated as well. By combining the friction uncertainty,the mixed sensitivity H∞optimization was proposed as the benchmark for controller design, which also leaded to good performance of robustness. Furthermore,unstructured perturbation to the system was analyzed so that the stability was guaranteed. Simulation results show that the proposed controller can provide excellent tracking and regulation performance.

Singular perturbation composite control of a free-floating flexible dual-arm space robot

The Free-floating Flexible Dual-arm Space Robot is a highly nonlinear and coupled dynamics system. In this paper, the dynamic model is derived of a Free-floating Flexible Dual-arm Space Robot holding a rigid payload. Furthermore, according to the singular perturbation method, the system is separated into a slow subsystem representing rigid body motion of the robot and a fast subsystem representing the flexible link dynamics. For the slow subsystem, based on the second method of Lyapunov, using simple quantitative bounds on the model uncertainties, a robust tracking controller design is used during the trajectory tracking phase. The optimal control method is designed in the fast subsystem to guarantee the exponential stability. With the combination of the two above, the system can track the expected trajectory accurately, even though with uncertainty in model parameters, and its flexible vibration gets suppressed, too. Finally, some simulation tests have been conducted to verify the effectiveness of the proposed methods.

Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion

Robotic manipulators are widely used in applications that require fast and precise motion.Such devices,however,are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part.To address these issues,the Linear Matrix Inequalities(LMIs)and Parallel Distributed Compensation(PDC)approaches are implemented in the Takagy–Sugeno Fuzzy Model(T-SFM).We propose the following methodology;initially,the state space equations of the nonlinear manipulator model are derived.Next,a Takagy–Sugeno Fuzzy Model(T-SFM)technique is used for linearizing the state space equations of the nonlinear manipulator.The T-SFM controller is developed using the Parallel Distributed Compensation(PDC)method.The prime concept of the designed controller is to compensate for all the fuzzy rules.Furthermore,the Linear Matrix Inequalities(LMIs)are applied to generate adequate cases to ensure stability and control.Convex programming methods are applied to solve the developed LMIs problems.Simulations developed for the proposed model show that the proposed controller stabilized the system with zero tracking error in less than 1.5 s.

Robust dynamic surface control of flexible joint robots using recurrent neural networks

A robust neuro-adaptive controller for uncertain flexible joint robots is presented. This control scheme integrates H^infinity disturbance attenuation design and recurrent neural network adaptive control technique into the dy- namic surface control framework. Two recurrent neural networks are used to adaptively learn the uncertain functions in a flexible joint robot. Then, the effects of approximation error and filter error on the tracking performance are attenuated to a prescribed level by the embedded H-infinity controller, so that the desired H-infinity tracking performance can be achieved. Finally. simulation results verifv the effectiveness of the nronosed control scheme.

A New Adaptive Tracking Control Approach for Uncertain Flexible Joint Robot System

The adaptive tracking problem for uncertain flexible joint robot system is studied in this paper. By utilizing the adaptive backstepping method, an adaptive controller is constructed at the beginning. By utilizing the modified adaptive dynamic surface control technique, a new adaptive controller is presented afterwards to avoid the overparametrization problem and the explosion of complexity problem existing in the adaptive backstepping method. All the signals of the closed-loop system are rendered globally/semi-globally uniformly ultimately bounded, and the tracking error can be made arbitrarily small by tuning the designed parameters. A simulation example is given to show the validity of the control algorithm.

Off-line Programming Technology Based on RPC Communication Method and its Application

This paper puts forward a communication programming method between robot and external computer based on RPC (Remote Produce Call) communication method, which realizes robot distributed controlling network system model. And a new Robot off line programming method is built based on this communication method and network model. Further more, as an example, robot auto marking and auto cutting of shipbuilding profile system is developed, which proves the ideas of author’s off line programming and development methods of robot flexible automation system. As a result, this paper presents a new method for developing robot flexible automation system.

A Design Concept and Kinematic Model for a Soft Aquatic Robot with Complex Bio-mimicking Motion

Fish mortality assessments for turbine passages are currently performed by live-animal testing with up to a hundred thousand fish per year in Germany.A propelled sensor device could act as a fish surrogate.In this context,the study presented here investigates the state of the art via a thorough literature review on propulsion systems for aquatic robots.An evaluation of propulsion performance,weight,size and complexity of the motion achievable allows for the selection of an optimal concept for such a fish mimicking device carrying the sensors.In the second step,the design of a bioinspired soft robotic fish driven by an unconventional drive system is described.It is based on piezoceramic actuators,which allow for motion with five degrees of freedom(DOF)and the creation of complex bio-mimicking body motions.A kinematic model for the motion’s characteristics is developed,to achieve accurate position feedback with the use of strain gauges.Optical measurements validate the complex deformation of the body and deliver the basis for the calibration of the kinematic model.Finally,it can be shown,that the calibrated model presented allows the tracking of the deformation of the entire body with an accuracy of 0.1 mm.

Motion Control and Optimal Design of a Biomimetic Manipulator Based on Snake Coiling and Stretching

The traditionally articulated manipulator had a single control method,and the limited motion trajectory space was unsuitable for working in an unstructured environment.This paper introduces a control method and optimization for a multijoint manipulator Inspired by snakes'curling and stretching motions.First,we analyze the manipulator’s connection mode and motion planning and propose a new motion method.In addition,we calculated the relevant positions and angles and subdivided the motion of some joints based on the principle of the meta-heuristic algorithm.Ultimately,the manipulator in this mode has a larger workspace and more flexible motion trajectories.The experimental results are consistent with the theoretical analysis,which further proves the feasibility and scalability of the scheme.