Non-linear model predictive control schemes with application on a 2 link vertical robot manipulator

Wilson, Jacob; Charest, Meaghan; Dubay, Rickey

doi:10.1016/j.rcim.2016.02.003

Cited by 70 publications

(42 citation statements)

References 20 publications

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“…It is observed that by using the MPC control approach, the energy consumption is lower than by using the LQ optimal control. Figure 6a,b depict the robot synthetic controls v 2 and v 1 given by Equation (15). As can be seen, the synthetic controls reach zero when the end-effector of the robot reaches its objective.…”

Section: Simulation Resultsmentioning

confidence: 98%

“…In [15], three nonlinear predictive control approaches for controlling a planar two-link vertical manipulator robot were developed: an adaptive nonlinear model predictive control (nMPC) approach, a proportional-integral-derivative (PID)-based nMPC (PIDnMPC) approach, and a novel simplified nMPC (SnMPC) approach. In [16], a nonlinear model predictive control of a manipulator robot mounted on an unmanned satellite was proposed.…”

Section: Introductionmentioning

confidence: 99%

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MPC Control and LQ Optimal Control of A Two-Link Robot Arm: A Comparative Study

et al. 2018

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This study examined the control of a planar two-link robot arm. The control approach design was based on the dynamic model of the robot. The mathematical model of the system was nonlinear, and thus a feedback linearization control was first proposed to obtain a linear system for which a model predictive control (MPC) was developed. The MPC control parameters were obtained analytically by minimizing a cost function. In addition, a simulation study was done comparing the proposed MPC control approach, the linear quadratic (LQ) control based on the same feedback linearization, and a control approach proposed in the literature for the same problem. The results showed the efficiency of the proposed method.

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Section: Simulation Resultsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

MPC Control and LQ Optimal Control of A Two-Link Robot Arm: A Comparative Study

et al. 2018

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“…For mobile Manipulators, planning issues involve Manipulator planning and platform planning in two parts [12,13]. The combination of the platform and the Manipulator makes the system redundant, the same task can be achieved either by a single motion Manipulator or platform, or by moving a Manipulator and a platform at the same time.…”

Section: Mobile Manipulator Movement Planningmentioning

confidence: 99%

Trajectory Planning and Control of Mobile Manipulator

Luo¹,

Sun²,

Yu³

2017

Proceedings of the 2017 7th International Conference on Social Network, Communication and Education (SNCE 2017)

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Abstract.A manipulator is an automatic operating device that can imitate certain movements of the hand and arm , and it can be used to grab and carry objects or operate tools in a fixed procedure. This paper mainly discusses the concept, the manipulator development history and research trends of the manipulator at home and abroad, it mainly from three aspects of the manipulator motion planning, coordination and control of multiple mobile robots reviews the development in recent years, and introduces the related problems and the corresponding treatment methods. Finally, it explores the development direction and the problem that needs to be solved in this research field.

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“…In recent years, technological advances in computer systems and sensors has lead in the development and application of advanced control theories and robotics. These advances are presented jointly, since the nonlinear models of robots have served as a good study case in order to illustrate the general concepts of analysis and design of advanced control theories (Canudas de Wit, Siciliano, & Bastin, 1996), for example: adaptive control (Tso & Lin, 1996), sliding modes control (Zhao, Sheng, & Liu, 2014), Lyapunov based control (Halalchi, Bara, & Laroche, 2010), nonlinear predictive control (Wilson, Charest, & Dubay, 2016), fuzzy logic control (Chen, Wang, Zhai, & Gao, 2017), among others. The main reason lies in its ability to manipulate materials, parts, tools or specialized devices by programming their movements.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Control for a Three DoF Manipulator Robot

Benitez-Garcia

Villarreal-Cervantes

2018

Enfoque UTE

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In the classical approach of Time-Triggered Control (TTC), the control signal is updated at each sampling time as well as the system states to be controlled, which could imply a redundancy in the computational calculation as well as in the transfer of information in the regulation objective. On the other hand, the Event-Triggered Control (ETC) approach performs the same task in an asynchronous way, i.e,, it only updates the control signal when a performance requirement is violated and the states are updated at each sampling time. This reduces the amount of computational calculation without affecting the performance of the closed loop system. For this reason, in the present work the ETC is developed for the stabilization of a manipulator robot with three Degree of Freedom (DoF) in the joint space where a Lyapunov Control Function (LCF) is proposed to formulate the event function (e¯), which indicates whether or not is required the control signal updating. Simulation results show the reduction of the updates compared with a TTC.

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Non-linear model predictive control schemes with application on a 2 link vertical robot manipulator

Cited by 70 publications

References 20 publications

MPC Control and LQ Optimal Control of A Two-Link Robot Arm: A Comparative Study

MPC Control and LQ Optimal Control of A Two-Link Robot Arm: A Comparative Study

Trajectory Planning and Control of Mobile Manipulator

Event-Triggered Control for a Three DoF Manipulator Robot

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