scholarly journals Switched Linear Multi-Robot Navigation Using Hierarchical Model Predictive Control

2017 ◽  
Author(s):  
Chao Huang ◽  
Xin Chen ◽  
Yifan Zhang ◽  
Shengchao Qin ◽  
Yifeng Zeng ◽  
...  
Keyword(s):  
Predictive Control ◽  
Robot Navigation ◽  
Reference Trajectory ◽  
Control Parameters ◽  
Multiple Robots ◽  
High Complexity ◽  
Navigation Problem ◽  
A New Technique ◽  
Theoretical Results ◽  
Multi Robot

Multi-robot navigation control in the absence of reference trajectory is rather challenging as it is expected to ensure stability and feasibility while still offer fast computation on control decisions. The intrinsic high complexity of switched linear dynamical robots makes the problem even more challenging. In this paper, we propose a novel HMPC based method to address the navigation problem of multiple robots with switched linear dynamics. We develop a new technique to compute the reachable sets of switched linear systems and use them to enable the parallel computation of control parameters. We present theoretical results on stability, feasibility and complexity of the proposed approach, and demonstrate its empirical advance in performance against other approaches.

Game-Theoretic Strategic Coordination and Navigation of Multiple Wheeled Robots

2021 ◽  
Vol 21 (4) ◽  
pp. 1-15
Author(s):  
Buddhadeb Pradhan ◽  
Nirmal Baran Hui ◽  
Diptendu Sinha Roy ◽  
Gautam Srivastava ◽  
Jerry Chun-Wei Lin
Keyword(s):  
Robot Navigation ◽  
Heuristic Method ◽  
Performance Comparison ◽  
Multiple Robots ◽  
Coordination Strategy ◽  
Strategic Coordination ◽  
Comparison Results ◽  
Game Theoretic ◽  
Multi Robot

Multiple robots negotiating in a dynamic workspace may lead to collisions. To avoid such issues, multi-robot navigation and coordination becomes necessary but is computationally very challenging, particularly when there are many robots. This article addresses the problem of multi-robot navigation where individual robots require coordination. Although a few such attempts for modeling multi-robot coordination and navigation have been studied, this work proposes a game-theoretic coordination strategy, also referred to as strategic coordination. We make use of a genetic algorithm tuned fuzzy logic–based motion planner. The proposed strategic coordination strategy has been pitted against a basic potential field-based motion planner, also referred to as the heuristic method, for performance comparison. Results are compared through computer simulation with 8 to 17 robots at different rounds. From the obtained results, it was observed that the proposed coordination scheme’s efficacy is strong for a larger number of robots. In addition, the proposed strategic coordination scheme with the genetic-fuzzy-based motion planner was found to outperform other combinations as far as the quality of solutions and time to reach the goal positions. The computational complexity of different methods has also been compared and presented.

A novel recursive formulation for dynamic modeling and trajectory tracking control of multi-rigid-link robotic manipulators mounted on a mobile platform

2020 ◽  
pp. 095965182097390
Author(s):  
AM Shafei ◽  
H Mirzaeinejad
Keyword(s):  
Dynamic Modeling ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Robotic System ◽  
Mobile Platform ◽  
Reference Trajectory ◽  
Trajectory Tracking Control ◽  
Recursive Formulation ◽  
Mobile Base

This article establishes an innovative and general approach for the dynamic modeling and trajectory tracking control of a serial robotic manipulator with n-rigid links connected by revolute joints and mounted on an autonomous wheeled mobile platform. To this end, first the Gibbs–Appell formulation is applied to derive the motion equations of the mentioned robotic system in closed form. In fact, by using this dynamic method, one can eliminate the disadvantage of dealing with the Lagrange Multipliers that arise from nonholonomic system constraints. Then, based on a predictive control approach, a general recursive formulation is used to analytically obtain the kinematic control laws. This multivariable kinematic controller determines the desired values of linear and angular velocities for the mobile base and manipulator arms by minimizing a point-wise quadratic cost function for the predicted tracking errors between the current position and the reference trajectory of the system. Again, by relying on predictive control, the dynamic model of the system in state space form and the desired velocities obtained from the kinematic controller are exploited to find proper input control torques for the robotic mechanism in the presence of model uncertainties. Finally, a computer simulation is performed to demonstrate that the proposed algorithm can dynamically model and simultaneously control the trajectories of the mobile base and the end-effector of such a complicated and high-degree-of-freedom robotic system.

Predictive Control and Simulation for Variable-Pitch Wind Turbines

2012 ◽  
Vol 562-564 ◽  
pp. 1012-1015
Author(s):  
S.X. Wang ◽  
Z.X. Li ◽  
D.X. Sun ◽  
X.X. Xie
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Small World ◽  
Modeling Method ◽  
Reference Trajectory ◽  
System Delay ◽  
Variable Pitch ◽  
Electricity Grid ◽  
System Output ◽  
The Impact

In order to avoid the limitations of traditional mechanism modeling method, a neural network (NN) model of variable - pitch wind turbine is built by the NN modeling method based on field data. Then considering that from wind turbine’s startup to grid integration, the generator speed must be controlled to rise to the synchronous speed smoothly and precisely, a neural network model predictive control (NNMPC) strategy based on the small-world optimization algorithm (SWOA) is proposed. Simulation results show that the strategy can forecast the change of generator rotational speed based on the wind speed disturbance, making the controller act ahead to eliminate the impact of system delay. Furthermore, the system output can track the reference trajectory well, making sure that the system can connect the electricity grid steadily.

scholarly journals A model reference adaptive variable impedance control method for robot

2021 ◽  
Vol 336 ◽  
pp. 03005
Author(s):  
Xinchao Sun ◽  
Lianyu Zhao ◽  
Zhenzhong Liu
Keyword(s):  
Real Time ◽  
Tracking Control ◽  
Control Method ◽  
Impedance Control ◽  
Tracking Error ◽  
Reference Trajectory ◽  
Control Parameters ◽  
Model Reference ◽  
Force Tracking ◽  
Model Reference Adaptive

As a simple and effective force tracking control method, impedance control is widely used in robot contact operations. The internal control parameters of traditional impedance control are constant and cannot be corrected in real time, which will lead to instability of control system or large force tracking error. Therefore, it is difficult to be applied to the occasions requiring higher force accuracy, such as robotic medical surgery, robotic space operation and so on. To solve this problem, this paper proposes a model reference adaptive variable impedance control method, which can realize force tracking control by adjusting internal impedance control parameters in real time and generating a reference trajectory at the same time. The simulation experiment proves that compared with the traditional impedance control method, this method has faster force tracking speed and smaller force tracking error. It is a better force tracking control method.

Practical Tracking Control of a Class of Uncertain Surface Vessels Under Weak Assumptions on Uncertainties and Reference Trajectories

2021 ◽  
Author(s):  
Jian Li ◽  
Wenqing Xu ◽  
Zhaojing Wu ◽  
Yungang Liu
Keyword(s):  
Tracking Control ◽  
Broad Class ◽  
Tracking Error ◽  
Reference Trajectory ◽  
Unknown Parameters ◽  
Related Literature ◽  
Surface Vessels ◽  
Control Scheme ◽  
Reference Trajectories ◽  
Theoretical Results

Abstract This paper is devoted to the tracking control of a class of uncertain surface vessels. The main contributions focus on the considerable relaxation of the severe restrictions on system uncertainties and reference trajectory in the related literature. Specifically, all the system parameters are unknown and the disturbance is not necessarily to be differentiable in the paper, but either unknown parameters or disturbance is considered but the other one is excluded in the related literature, or both of them are considered but the disturbance must be continuously differentiable. Moreover, the reference trajectories in the related literature must be at least twice continuously differentiable and themselves as well as their time derivatives must be known for feedback, which are generalized to a more broad class ones that are unknown and only one time continuously differentiable in the paper. To solve the control problem, a novel practical tracking control scheme is presented by using backstepping scheme and adaptive technique, and in turn to derive an adaptive state-feedback controller which guarantees that all the states of the resulting closed-loop system are bounded while the tracking error arrives at and then stay within an arbitrary neighborhood of the origin. Finally, simulation is provided to validate the effectiveness of the proposed theoretical results.

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