Neural Approximation-based Model Predictive Tracking Control of Non-holonomic Wheel-legged Robots
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ISSN:1598-6446 eISSN:2005-4092 http://www.springer.com/12555
Neural Approximation-based Model Predictive Tracking Control of Nonholonomic Wheel-legged Robots Jiehao Li, Junzheng Wang, Shoukun Wang, Wen Qi, Longbin Zhang, Yingbai Hu, and Hang Su* Abstract: This paper proposes a neural approximation based model predictive control approach for tracking control of a nonholonomic wheel-legged robot in complex environments, which features mechanical model uncertainty and unknown disturbances. In order to guarantee the tracking performance of wheel-legged robots in an uncertain environment, effective approaches for reliable tracking control should be investigated with the consideration of the disturbances, including internal-robot friction and external physical interactions in the robot’s dynamical system. In this paper, a radial basis function neural network (RBFNN) approximation based model predictive controller (NMPC) is designed and employed to improve the tracking performance for nonholonomic wheel-legged robots. Some demonstrations using a BIT-NAZA robot are performed to illustrate the performance of the proposed hybrid control strategy. The results indicate that the proposed methodology can achieve promising tracking performance in terms of accuracy and stability. Keywords: Model predictive control, neural approximation, nonholonomic system, tracking control, wheel-legged robot.
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INTRODUCTION
In the past few years, wheel-legged robots [1–3] have become widespread among applications that can operate in various uncertain or unreachable terrains, such as narrow space in damaged buildings after disasters, radiation environments, and complex working field. In the development and control of the wheel-legged robots, research interests have been attracted, and promising results have been achieved. For instance, the developed quadruped robot AZ-IMUT in [4] was capable of switching the control modes between legs and wheel tracking. A deformable wheeled robot based on origami structure was introduced in [5], and the robot can move quickly with large wheels and small gaps. A mechanically decoupled wheel-legged hybrid transformable robot, namely HyTRo-I in [6], was able to achieve the transformation between wheeled and legged configuration with improved shifting stability and a small number of transition steps. However, most of these wheel-legged robots are created with series mechanism, which is small in size and weak in payload and cannot meet the practical requirements in ex-
treme situations such as disaster relief, combat platforms, and resource exploration. In order to meet the various terrains requirements, such as movement efficiency, velocity, stability, obstacle-negotiation, and improved payload capacity [7, 8], a new mobility structure that can transform between wheel and leg is proposed in this paper. However, its tracking control accuracy is affected due to its mechanical model uncertainty and unknown disturbances in complex environments under heavy loads. Few works have solved these challenges. Hence, this
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