Dual Quaternion Based Close Proximity Operation for In-Orbit Assembly via Model Predictive Control

This paper studies the problem of guidance and control for autonomous in-orbit assembly. A six-degree-of-freedom (6-DOF) motion control for in-orbit assembly close proximity operation between a service satellite and a target satellite is addressed in detail. The dynamics based on dual quaternion are introduced to dispose the coupling effect between translation and rotation in a succinct frame, in which relevant perturbation and disturbance are involved. With the consideration of economical principle for fuel consume, a generic control system based on model predictive control (MPC) is then designed to generate a suboptimal control sequence for rendezvous trajectory considering actuator output saturation. The stability and robustness issues of the MPC-based control system are analyzed and proved. Numerical simulations are presented to demonstrate the effectiveness and robustness of the proposed control scheme, while additional comparisons for diverse horizons of the MPC are further conducted.

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Dynamic traffic light optimization and Control System using model-predictive control method

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) ◽

10.1109/itsc.2016.7795937 ◽

2016 ◽

Cited By ~ 2

Author(s):

You-Ren Chen ◽

Keng-Pin Chen ◽

Pao-Ann Hsiungy

Keyword(s):

Control System ◽

Model Predictive Control ◽

Predictive Control ◽

Control Method ◽

Dynamic Traffic ◽

Traffic Light ◽

Optimization And Control ◽

And Control

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Desired Terminal State Concept in Model Predictive Control: A Case Study

Journal of Control Science and Engineering ◽

10.1155/2019/5208612 ◽

2019 ◽

Vol 2019 ◽

pp. 1-7

Author(s):

František Dušek ◽

Daniel Honc

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Control Method ◽

Optimization Methods ◽

Terminal State ◽

Online Optimization ◽

Transient Behaviour ◽

The Stability ◽

Transport Problems ◽

And Control

The paper deals with an online optimization control method for dynamical processes called Model Predictive Control (MPC). It is a popular control method in industry and frequently treated in academic areas as well. The standard predictive controllers usually do not guarantee stability especially for the case of short horizons and large control error penalization. Terminal state is one way to ensure stability or at least increase the controller robustness. In the paper, deviation of the predicted terminal state from the desired terminal state is considered as one term of the cost function. Effect of the stability and control quality is demonstrated in the simulated experiments. The application area for online optimization methods is very broad including various logistics and transport problems. If the dynamics of the controlled processes cannot be neglected, the optimization problem must be solved not only for steady state but also for transient behaviour, e.g., by MPC.

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Distributed Model Predictive Control of Steam/Water Loop in Large Scale Ships

Processes ◽

10.3390/pr7070442 ◽

2019 ◽

Vol 7 (7) ◽

pp. 442 ◽

Cited By ~ 4

Author(s):

Shiquan Zhao ◽

Anca Maxim ◽

Sheng Liu ◽

Robin De Keyser ◽

Clara Ionescu

Keyword(s):

Control System ◽

Model Predictive Control ◽

Predictive Control ◽

Power Plants ◽

Large Scale ◽

Distributed Model ◽

Distributed Model Predictive Control ◽

Steam Power Plants ◽

Great Reliability ◽

The Stability

In modern steam power plants, the ever-increasing complexity requires great reliability and flexibility of the control system. Hence, in this paper, the feasibility of a distributed model predictive control (DiMPC) strategy with an extended prediction self-adaptive control (EPSAC) framework is studied, in which the multiple controllers allow each sub-loop to have its own requirement flexibility. Meanwhile, the model predictive control can guarantee a good performance for the system with constraints. The performance is compared against a decentralized model predictive control (DeMPC) and a centralized model predictive control (CMPC). In order to improve the computing speed, a multiple objective model predictive control (MOMPC) is proposed. For the stability of the control system, the convergence of the DiMPC is discussed. Simulation tests are performed on the five different sub-loops of steam/water loop. The results indicate that the DiMPC may achieve similar performance as CMPC while outperforming the DeMPC method.

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