Trajectory Tracking of an Omni-Directional Wheeled Mobile Robot Using a Model Predictive Control Strategy

Wang, Yuming; Liu, Xiaofeng; Yang, Xianqiang; Hu, Fang; Jiang, Aimin; Yang, Chenguang

doi:10.3390/app8020231

Cited by 123 publications

(74 citation statements)

References 22 publications

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“…The proof follows from (43), from (32) of Lemma 5 and by noting that, for x belonging to the generic hyper-circumference C P,ρ from (28) of Lemma 1 and (42) it is:…”

Section: Resultsmentioning

confidence: 99%

“…To control the system (A17) with the MPC technique (e.g., [37,43]), consider the following system as the nominal model in order to predict its evolution:…”

Section: Appendix Amentioning

confidence: 99%

“…Finally, it is included an appendix in which six easy examples are provided. The first five ones clearly show how numerous control techniques available in the literature (e.g., [10,14,15,20,[23][24][25]29,31,33,[41][42][43] and the references therein) for significant classes of linear and nonlinear systems can produce unstable control system or can significantly reduce the performance of the control system, under the following realistic hypotheses: parametric uncertainties, real actuators, measurement noise, finite online computation time of the control signal.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Unified Approach to Design Robust Controllers for Nonlinear Uncertain Engineering Systems

Celentano¹

2018

Applied Sciences

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Featured Application: Design and realization of robust, simple and effective controllers, mainly for the transportation and manufacturing systems.Abstract: This paper presents new theorems, which allow to design in a unified way robust proportional-derivative (PD)-type control laws without chattering for a broad class of uncertain nonlinear multi-input multi-output (MIMO) systems, subject to bounded disturbances and noises, of great theoretical and engineering relevance. These controllers are used to track a reference signal with bounded second derivative with the tracking error norm smaller than a prescribed value. The proposed control laws are simple to design and implement, above all for robotic systems, both in the case of a trajectory assigned in the joint space and in the workspace. The obtained theoretical results can have numerous applications. In this paper four significant applications are provided. The first one concerns the solution of a nonlinear equations system or the determination of an equilibrium point of a nonlinear system. The second case study deals with the inversion of a nonlinear vectorial function or the kinematic inversion of a robot. The third application concerns: (A) the tracking control of a robot with parametric uncertainties, with and without measurement noise on velocity, both in the joint space and the workspace; (B) the impedance control of a robot interacting with a human operator. The fourth case study addresses the tracking control of an uncertain nonlinear system that does not belong to the class of mechanical systems. Finally, an appendix is included, providing six easy examples, which show how the results proposed in the paper can eliminate and/or reduce serious disadvantages existing in the robust control literature for significant classes of linear and nonlinear uncertain systems.Keywords: general robust tracking control method; design of robust proportional-derivative-type controller; practical robust stability; robust control of mechanical uncertain systems; impedance control of a robot

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“…The proof follows from (43), from (32) of Lemma 5 and by noting that, for x belonging to the generic hyper-circumference C P,ρ from (28) of Lemma 1 and (42) it is:…”

Section: Resultsmentioning

confidence: 99%

“…To control the system (A17) with the MPC technique (e.g., [37,43]), consider the following system as the nominal model in order to predict its evolution:…”

Section: Appendix Amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Unified Approach to Design Robust Controllers for Nonlinear Uncertain Engineering Systems

Celentano¹

2018

Applied Sciences

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“…Lakatos et al dealt with the velocity control and planning of the bang-bang control parameters of the hopping robot [16]. Besides trajectory planning of jumping robots, many other scientists studied trajectory planning for the robotic manipulator and vehicle [17][18][19][20][21][22]. Constantinescu and Croft proposed an autonomous obstacle-avoidance function to plan trajectory and enhance the intelligence of a robotic manipulator [18].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning of an Intermittent Jumping Quadruped Robot with Variable Redundant and Underactuated Joints

et al. 2018

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The jumping robot has been a hot research field due to its prominent obstacle-climbing ability and excellent capacity in terrain adaptation and autonomous movement. However, huge impact between the robot and the ground when landing may cause structure damage, unbalanced movement, and even system crash. Therefore, trajectory planning of the jumping process has been a great challenge in robotic research, especially for the robot with varying underactuated and redundant joints. An intermittent jumping quadruped robot driven by pneumatic muscle actuators (PMAs) and owning variable redundant and underactuated joints designed in a previous study is taken as the study object. This paper divides the problem of trajectory planning into trajectory planning in the centroid space and joint space. Trajectory planning of different jumping phases in the centroid space adopts the scheme of minimizing the peak reaction force from the ground, then trajectory planning of the joint space is performed obeying the principle of minimizing consumed active torques. A jumping experiment is performed and validates the effectiveness of the proposed trajectory algorithm.

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“…Robotics in one of the most prolific research fields (WANG et al, 2018). Throughout its main topic, the most fascinating one is autonomous navigation (ÖZAS-LAN et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

The Use of a Statistical Filter and Metaheuristics to Model and Control The DC Motor of the Mobile Robot Used on NXP Cup

Moreira¹,

Fernandes

Silva

et al. 2018

jme

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Over the past decades, Robotics is one of the research fields with more advances. From methodologies of low-level control, used on actuators, to high-level control, used with artificial intelligence approaches. One of the most interesting problem that a mobile robot faces is autonomous navigation. For the robot be able to navigate on the environment autonomously, it have to make use of sensory input from one or more sensors that are used to perceive the robot surroundings as well as sensors that measure internal states of the robot. One of the most used control theory methodology is the proportional-integrative-derivative (PID) controller, where its parameters are estimated through a variety of ways, from raw mathematical modeling to the application of hybrid approaches that uses both a mathematical model and metaheuristics such as genetic algorithms. This paper aims to estimate the parameters of the direct current motor through a Kalman filter and use those to estimate the PID parameters to control the DC motor by the usage of a genetic algorithm. Results shows that the derived PID controller is quite efficient on the control of the DC motor used, thus validating the methodology.

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Trajectory Tracking of an Omni-Directional Wheeled Mobile Robot Using a Model Predictive Control Strategy

Cited by 123 publications

References 22 publications

A Unified Approach to Design Robust Controllers for Nonlinear Uncertain Engineering Systems

A Unified Approach to Design Robust Controllers for Nonlinear Uncertain Engineering Systems

Trajectory Planning of an Intermittent Jumping Quadruped Robot with Variable Redundant and Underactuated Joints

The Use of a Statistical Filter and Metaheuristics to Model and Control The DC Motor of the Mobile Robot Used on NXP Cup

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