Optimization-based model reference adaptive control for dynamic positioning of a fully actuated underwater vehicle

Gao, Jian; Wu, Puguo; Li, Tianrui; Proctor, Alison A.

doi:10.1007/s11071-016-3214-2

Cited by 34 publications

(11 citation statements)

References 29 publications

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“…The MPC approach has important advantages: It offers good control quality and takes into account all existing constraints imposed on process variables. As a result, MPC algorithms have been applied to numerous technological processes, mainly in industrial process control [44], e.g., chemical reactors [45], but also for control: computer networks [46], unmanned vehicles [28], antilock brake systems in automobiles [47], unmanned helicopters [27], tractortrailer vehicles [48], overhead cranes [49], underwater vehicles [50], active steering systems in cars [29] and even chaotic systems [51].…”

Section: Mpc Problem Formulationmentioning

confidence: 99%

Wiener structures for modeling and nonlinear predictive control of proton exchange membrane fuel cell

Ławryńczuk

Söffker

2018

Nonlinear Dyn

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The proton exchange membrane (PEM) fuel cell is a nonlinear dynamic system which cannot be precisely described and controlled using a linear model. This work has two objectives: (a) it discusses model selection for the PEM and (b) it develops two nonlinear computationally efficient model predictive control (MPC) algorithms for the PEM. Three Wiener model types of different orders of dynamics and complexity of the nonlinear steady-state block are compared. The model consisting of three dynamic blocks and a neural network with five hidden nodes is chosen. To obtain simple MPC quadratic optimization problems, a linear approximation of the model or a linear approximation of the predicted trajectory is repeatedly found. The first MPC scheme gives very good control accuracy, whereas the second MPC scheme leads to the same trajectories as those possible in the "ideal" MPC scheme with full online nonlinear optimization. Financial support received by the first author from the German Academic Exchange Service (DAAD) is acknowledged.

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Section: Mpc Problem Formulationmentioning

confidence: 99%

Wiener structures for modeling and nonlinear predictive control of proton exchange membrane fuel cell

Ławryńczuk

Söffker

2018

Nonlinear Dyn

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“…They decrease the computational cost of robust MPCs by constructing an ancillary loop together with the MPC loop. There are also some other custom‐designed TL‐MPC Schemes 20‐24 that employ an inner control loop to deal with the uncertainty and/or nonlinearity of the system and utilize an MPC loop to satisfy the constraints.…”

Section: Introductionmentioning

confidence: 99%

An improved two‐loop model predictive control design for nonlinear robust reference tracking with practical advantages

Farajzadeh-D

Sani

2020

Optim Control Appl Methods

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Summary In this paper, the nonlinear robust reference tracking problem is considered and an Improved Two‐Loop Nonlinear Model Predictive Control (ITL‐NMPC) design is proposed for a pre‐controlled system with bounded uncertainties subject to input and state constraints. In the industry, this scheme leads the lower design cost and fewer implementation risks since (i) it allows the existing controller to remain unchanged without any manipulation, (ii) it does not need the open‐loop model of the pre‐controlled system, and (iii) it does not require the terminal cost and constraint definition. For the proposed ITL‐NMPC, a practical parameter tuning algorithm is introduced and its robust exponential stability, as well as recursive feasibility, are guaranteed. Simulation results are used to better illustrate the effectiveness of the proposed approach and show that the proposed method not only improves the control performance of the pre‐controlled system but also reduces the design cost while satisfying the constraints.

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“…In addition, the MPC path tracking control method is also widely used in other auto-control fields, such as navigation and aerospace. 12–15…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the MPC path tracking control method is also widely used in other auto-control fields, such as navigation and aerospace. [12][13][14][15] The AV path tracking control method-based MPC aforementioned always sets a fixed prediction horizon, the length of which is very important because it significantly influences the AV performance during path tracking. And for different purposes, few scholars have studied the MPC method with variable prediction horizon.…”

Section: Introductionmentioning

confidence: 99%

An adaptive-prediction-horizon model prediction control for path tracking in a four-wheel independent control electric vehicle

Zhang

Zong

Chen

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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An adaptive-prediction-horizon model prediction control-based path tracking controller for a four-wheel independent control electric vehicle is designed. Unlike traditional model prediction control with fixed prediction horizon, this paper devotes to satisfy the varied path tracking demand by adjusting online the prediction horizon of model prediction control according to its effect on vehicle dynamic characteristics. Vehicle dynamic stability quantized with the vehicle sideslip-feature phase plane is preferentially considered in the prediction horizon adjustment. For stability during switching prediction horizon and for robustness during path tracking, the numerical problem inherent in the adaptive-prediction-horizon model prediction control is analysed and solved by introducing exponentially decreasing weight. Subsequently, the desired motion for path tracking with the four-wheel independent control electric vehicle is realized with a hierarchical control structure. Simulation results finally illustrate the effectiveness of the proposed method.

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Optimization-based model reference adaptive control for dynamic positioning of a fully actuated underwater vehicle

Cited by 34 publications

References 29 publications

Wiener structures for modeling and nonlinear predictive control of proton exchange membrane fuel cell

Wiener structures for modeling and nonlinear predictive control of proton exchange membrane fuel cell

An improved two‐loop model predictive control design for nonlinear robust reference tracking with practical advantages

An adaptive-prediction-horizon model prediction control for path tracking in a four-wheel independent control electric vehicle

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