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.

Soft Robotics:Morphology and Morphology-inspired Motion Strategy

Robotics has aroused huge attention since the 1950s.Irrespective of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental adaption.Accordingly,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured environments.For decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing applicability.The presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific morphologies.This paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

ANALYTICAL MODEL ALGORITHM FOR DYNAMICS OF ROBOTIC MANIPULATORS

A simple analytical model method for dynamics of robotic manipulators is proposed.Problem of deriving model matrix elements is transformed into problem of solving for driving forceand driving torque under specified condition by recursive dynamic equations. Expressions of reaction force in arbitrary joint in numeric-symbolic form are also derived. The properties of modelmatrices are given. Corresponding software which can recognize and manipulate symbols is developed and can be used to generate model and real-time code of robotic dynamics.

Hybrid force control of astronaut rehabilitative training robot under active loading mode

In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.

PATH FOLLOWING GPS-BASED CONTROL OF SMALL-SIZE ROBOTIC UNMANNED BLIMP

Robotic unmanned blimps own an enormous potential for applications in low-speed and low-altitude exploration, surveillance, and monitoring, as well as telecommunication relay platforms. To make lighter-than-air platform a robotic blimp with significant levels of autonomy, the decoupled longitude and latitude dynamic model is developed, and the hardware and software of the flight control system are designed and detailed. Flight control and navigation strategy and algorithms for waypoint flight problem are discussed. A result of flight experiment is also presented, which validates that the flight control system is applicable and initial machine intelligence of robotic blimp is achieved.

N-PD cross-coupling synchronization control based on adjacent coupling error analysis

In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on adjacent coupling error analysis is presented. The mathematical models of the robot, including kinematic model, dynamic model and spline trajectory planing, are established and verified. Since it is difficult to describe the real-time contour error of the robot for complex trajectory, the adjacent coupling error is analyzed to solve the problem. Combined with nonlinear control and coupling performance of the robot, N-PD cross-coupling synchronization controller is designed and validated by simulation analysis. A servo control experimental system which mainly consists of laser tracking system, the robot mechanical system and EtherCAT based servo control system is constructed. The synchronization error is significantly decreased and the maximum trajectory error is reduced from 0.33 mm to 0.1 mm. The effectiveness of the control algorithm is validated by the experimental results, thus the control strategy can improve the robot＇s trajectory tracking precision significantly.

DISTRIBUTION OF REACHABLE WORKSPACE AREAS IN PHYSICAL MODEL OF THE SOLUTION SPACE OF 2-DOF PARALLEL PLANAR MANIPULATORS

The expressions for calculating the values of the workspace areas of 2-DOF parallel planar manipulators (PPM) is derived. By the aid of computer, the values are calculated and plotted on the physical model of the solution space of the 2-DOF PPMs,so the workspaee-area-property atlas is obtained. The atlas delineates the relationship between the workspace areas and the link lengths of the 2-DOF PPMs all-sidedly. It is very useful for designers overalI to understand and know welI the relationship.

MODELLING OF TWO-FLEXIBLE-ARM MECHANISM WITH ELASTIC JOINTS

The dynamic model of two-flexible-arm mechanism with elastic joints is studied.The transmission problem of the joint which connects two flexible links is successfully solved. The mechanical model is proposed for the joint, and a practical vibration analysis method of lumped parameter transfer matrix modal analysis is developed for two flexible arms with an elastic joint.

Longitudinal and lateral slip control of autonomous wheeled mobile robot for trajectory tracking

This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme lies in its methodology that considers both longitudinal and lateral slip components. Based on the derived slip model, the controller for longitudinal motion slip has been synthesized. Various control parameters have been studied to investigate their effects on the performance of the controller resulting in selection of their optimum values. The designed controller for lateral slip or skid is based on the proposed side friction model and skid check condition. Considering a car-like WMR, simulation results demonstrate the effectiveness of the proposed control scheme. The robot successfully followed the desired circular trajectory in the presence of wheel slippage and skid. This research finds its potential in various applications involving WMR navigation and control.

Emotion Modelling for Social Robotics Applications： A Review

Robots of today are eager to leave constrained industrial environments and embrace unexplored and unstructured areas, for extensive applications in the real world as service and social robots. Hence, in addition to these new physical frontiers, they must face human ones, too. This implies the need to consider a human-robot interaction from the beginning oft_he design; the possibility for a robot to recognize users＇ emotions and, in a certain way, to properly react and ＂behave＂. This could play a fundamental role in their integration in society. However, this capability is still far from being achieved. Over the past decade, several attempts to implement automata for different applications, outside of the industry, have been pursued. But very few applications have tried to consider the emotional state of users in the behavioural model of the robot, since it raises questions such as： how should human emotions be modelled for a correct representation of their state of mind？ Which sensing modalities and which classification methods could be the most feasible to obtain this desired knowl- edge？ Furthermore, which applications are the most suitable for the robot to have such sensitivity？ In this context, this paper aims to provide a general overview of recent attempts to enable robots to recognize human emotions and interact properly.

Identification of robot dynamic model and joint frictions using a baseplate force sensor

Dynamic models play an important role in robot control and applications.The accurate identification of dynamic models has become crucial to meeting increasing performance requirements.Owing to the inertial forces and the joint frictions coupling,the identification first requires a parametrized friction model.However,the joint frictions are strongly nonlinear and vary with many factors including posture,velocity and temperature.Hence,all friction models have some deviation from the real values,which reduces the identification accuracy.This paper proposes an identification approach using a baseplate force sensor.It identifies the inertial parameters first and then computes the joint friction values by subtracting the inertial torques from the joint torques.This method has the advantage that it does not require a priori friction model.It can choose or construct a proper model to fit the real values and is thus expected to achieve high performance.Experiments on a 6-DoF robot were conducted to verify the proposed method.

Characteristic model-based consensus of networked heterogeneous robotic manipulators with dynamic uncertainties

In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.

Towards Efficient Robotic Software Development by Reusing Behavior Tree Structures for Task Planning Paradigms

interaction pipelines while maintaining interfaces for task-specific customization.The Structural-BT framework supports the modular design of structure functionalities and allows easy extensibility of the inner planning flows between BT components.With the Structural-BT framework,software engineers can develop robotic software by flexibly composing BT structures to formulate the skeleton software architecture and implement task-specific algorithms when necessary.In the experiment,this paper develops robotic software for diverse task scenarios and selects the baseline approaches of Robot Operating System(ROS)and classical BT development frameworks for comparison.By quantitatively measuring the reuse frequencies and ratios of BT structures,the Structural-BT framework has been shown to be more efficient than the baseline approaches for robotic software development.

Radial basis function‐based exoskeleton robot controller development

The realisation of a model‐based controller for a robot with a higher degree of freedom requires a substantial amount of computational power.A high‐speed CPU is required to maintain a higher sampling rate.Multicore processors cannot boost the performance or reduce the execution time as the programs are sequentially structured.The neural network is a great tool to convert a sequentially structured program to an equivalent parallel architecture program.In this study,a radial basis function(RBF)neural network is developed for controlling 7 degrees of freedom of the human lower extremity exoskel-eton robot.A realistic friction model is used for modelling joint friction.High trajectory tracking accuracies have been obtained.Evidence of computational efficiency has been observed.The stability analysis of the developed controller is presented.Analysis of variance is used to assess the controller's resilience to parameter variation.To show the effectiveness of the developed controller,a comparative study was performe between the developed RBF network‐based controller and Sliding Mode Controller,Computed Tor-que Controller,Adaptive controller,Linear Quadratic Regulator and Model Reference Computed Torque Controller.