scholarly journals Predictor-Based Motion Tracking Control for Cloud Robotic Systems with Delayed Measurements

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 398 ◽  
Author(s):  
Shaobo Shen ◽  
Aiguo Song ◽  
Tao Li
Keyword(s):  
Tracking Control ◽  
Motion Tracking ◽  
Robot Manipulator ◽  
Sufficient Conditions ◽  
Robotic Systems ◽  
Model Uncertainties ◽  
Tracking Controllers ◽  
Velocity Prediction ◽  
Novel Method ◽  
Real Time Information

This paper addresses the problem of motion prediction and tracking control for cloud robotic systems with time-varying delays in measurements. A novel method using an observer-based structure for position and velocity prediction is developed to estimate the real-time information of robot manipulator. The prediction error can converge to zero even if model uncertainties exist in the robot manipulator. Based on the predicted positions and velocities, some sufficient conditions are derived to design suitable tracking controllers such that semi-globally uniformly ultimately bounded tracking performance of the predictor–controller couple can be guaranteed. Finally, the effectiveness and robustness to model uncertainties of the proposed method are verified by a two degree-of-freedom (DOF) robot system.

Experimental and Analytical Decentralized Adaptive Control of a 7-DOF Robot Manipulator

2020 ◽  
Author(s):  
Alexander Bertino ◽  
Peiman Naseradinmousavi ◽  
Atul Kelkar
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Computational Efficiency ◽  
Tracking Control ◽  
Robot Manipulator ◽  
Problem Formulation ◽  
Experimental Results ◽  
Model Free ◽  
Trajectory Simulation ◽  
Adaptive Control Strategy

Abstract In this paper, we study the analytical and experimental control of a 7-DOF robot manipulator. A model-free decentralized adaptive control strategy is presented for the tracking control of the manipulator. The problem formulation and experimental results demonstrate the computational efficiency and simplicity of the proposed method. The results presented here are one of the first known experiments on a redundant 7-DOF robot. The efficacy of the adaptive decentralized controller is demonstrated experimentally by using the Baxter robot to track a desired trajectory. Simulation and experimental results clearly demonstrate the versatility, tracking performance, and computational efficiency of this method.

scholarly journals Online Optimal Control of Robotic Systems with Single Critic NN-Based Reinforcement Learning

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Xiaoyi Long ◽  
Zheng He ◽  
Zhongyuan Wang
Keyword(s):  
Optimal Control ◽  
Reinforcement Learning ◽  
Tracking Control ◽  
Learning Algorithm ◽  
Tracking Error ◽  
Adaptive Dynamic Programming ◽  
Robotic Systems ◽  
Control Synthesis ◽  
Optimal Tracking ◽  
Optimal Tracking Control

This paper suggests an online solution for the optimal tracking control of robotic systems based on a single critic neural network (NN)-based reinforcement learning (RL) method. To this end, we rewrite the robotic system model as a state-space form, which will facilitate the realization of optimal tracking control synthesis. To maintain the tracking response, a steady-state control is designed, and then an adaptive optimal tracking control is used to ensure that the tracking error can achieve convergence in an optimal sense. To solve the obtained optimal control via the framework of adaptive dynamic programming (ADP), the command trajectory to be tracked and the modified tracking Hamilton-Jacobi-Bellman (HJB) are all formulated. An online RL algorithm is the developed to address the HJB equation using a critic NN with online learning algorithm. Simulation results are given to verify the effectiveness of the proposed method.

scholarly journals Interacting with Maps in Virtual and Augmented Reality

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Bernhard Jenny ◽  
Kadek Ananta Satriadi ◽  
Yalong Yang ◽  
Christopher R. Austin ◽  
Simond Lee ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Motion Tracking ◽  
Three Dimensional ◽  
Geospatial Data ◽  
Leap Motion ◽  
Flow Maps ◽  
Points Of Interest ◽  
Tracking Controllers ◽  
Game Engines ◽  
Virtual And Augmented Reality

<p><strong>Abstract.</strong> Augmented reality (AR) and virtual reality (VR) technology are increasingly used for the analysis and visualisation of geospatial data. It has become simple to create an immersive three-dimensional AR or VR map with a combination of game engines (e.g., Unity), software development kits for streaming and rendering geospatial data (e.g., Mapbox), and affordable hardware (e.g., HTC Vive). However, it is not clear how to best interact with geospatial visualisations in AR and VR. For example, there are no established standards to efficiently zoom and pan, select map features, or place markers on AR and VR maps. In this paper, we explore interaction with AR and VR maps using gestures and handheld controllers.</p><p>As for gesture-controlled interaction, we present the results of recent research projects exploring how body gestures can control basic AR and VR map operations. We use motion-tracking controllers (e.g., Leap Motion) to capture and interpret gestures. We conducted a set of user studies to identify, explore and compare various gestures for controlling map-related operations. This includes, for example, mid-air hand gestures for zooming and panning (Satriadi et al. 2019), selecting points of interest, adjusting the orientation of maps, or placing markers on maps. Additionally, we present novel VR interfaces and interaction methods for controlling the content of maps with gestures.</p><p>As for handheld controllers, we discuss interaction with exocentric globes, egocentric globes (where the user stands inside a large virtual globe), flat maps, and curved maps in VR. We demonstrate controller-based interaction for adjusting the centre of world maps displayed on these four types of projection surfaces (Yang et al. 2018), and illustrate the utility of interactively movable VR maps by the example of three-dimensional origin-destination flow maps (Yang et al. 2019).</p>

scholarly journals Observer-Based H ∞ Fuzzy Synchronization and Output Tracking Control of Time-Varying Delayed Chaotic Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Kuan-Yi Lin ◽  
Tung-Sheng Chiang ◽  
Chian-Song Chiu ◽  
Wen-Fong Hu ◽  
Peter Liu
Keyword(s):  
Continuous Time ◽  
Tracking Control ◽  
Chaotic Systems ◽  
Sufficient Conditions ◽  
Control Design ◽  
Practical Consideration ◽  
Time Varying ◽  
Fuzzy Observer ◽  
Output Tracking ◽  
Output Tracking Control

Tracking control for the output using an observer-based H ∞ fuzzy synchronization of time-varying delayed discrete- and continuous-time chaotic systems is proposed in this paper. First, from a practical point of view, the chaotic systems here consider the influence of time-varying delays, disturbances, and immeasurable states. Then, to facilitate a uniform control design approach for both discrete- and continuous-time chaotic systems, the dynamic models along with time-varying delays and disturbances are reformulated using the T-S (Takagi–Sugeno) fuzzy representation. For control design considering immeasurable states, a fuzzy observer achieves master-slave synchronization. Third, combining both a fuzzy observer for state estimation and a controller (solved from generalized kinematic constraints) output tracking can be achieved. To make the design more practical, we also consider differences of antecedent variables between the plant, observer, and controller. Finally, using Lyapunov’s stability approach, the results are sufficient conditions represented as LMIs (linear matrix inequalities). The contributions of the method proposed are threefold: (i) systemic and unified problem formulation of master-slave synchronization and tracking control for both discrete and continuous chaotic systems; (ii) practical consideration of time-varying delay, immeasurable state, different antecedent variables (of plant, observer, and controller), and disturbance in the control problem; and (iii) sufficient conditions from Lyapunov’s stability analysis represented as LMIs which are numerically solvable observer and controller gains from LMIs. We carry out numerical simulations on a chaotic three-dimensional discrete-time system and continuous-time Chua’s circuit. Satisfactory numerical results further show the validity of the theoretical derivations.

Neural network adaptive robust tracking control for uncertain robotic systems with delays

2008 ◽  
Vol 41 (2) ◽  
pp. 11702-11707 ◽  
Author(s):  
Yaonan Wang ◽  
Yi Zuo ◽  
Lihong Huang ◽  
Chunsheng Li
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Robotic Systems ◽  
Robust Tracking ◽  
Robust Tracking Control

Adaptive PID Switched Tracking Control of Robot Manipulator

2021 ◽  
Author(s):  
Juan Wang ◽  
Qiang Wei ◽  
Quanze Zhao ◽  
Zhi-E Lou
Keyword(s):  
Tracking Control ◽  
Robot Manipulator
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