Direct relaxation of hard-constraint in Model Predictive Control

Zhao, Kejun; Xin, Lü; Zheng, Wenzhou; Huang, Chengbin

doi:10.1109/fskd.2012.6234019

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…For the states, soft constraints are used instead since, in most of the times they cannot be enforced due to the disturbances that are acting on the system. [89,90] Additionally, adding a hard constraint on states may result to an infeasible optimization problem. [91] Moreover, it is noted that in the case where the damping and stiffness uncertainties are set to +10%, the top floor displacement in the case with the passive TMD was slightly increased compared to the uncontrolled scenario.…”

Section: Scenariomentioning

confidence: 99%

Robust structural control of a real high‐rise tower equipped with a hybrid mass damper

Koutsoloukas

Nikitas

Aristidou

2022

Structural Design Tall Build

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In this paper, the robust control of a real high-rise tower is studied, using a newly proposed, in the structural control field, Robust Model Predictive Control scheme (RMPC). Two RMPC controllers were designed considering either displacement mitigation (RMPC 1 ) or power consumption efficiency (RMPC 2 ).The two controllers were compared to the benchmark, robustness-wise, H ∞ control scheme to demonstrate their relative performance. A number of stiffness and damping uncertainty scenarios were designed based on a broad study of the relevant literature, in order to estimate the robustness of each of the three controllers. In all scenarios, variable actuator uncertainty of AE5% was introduced. It was found that all controllers are effective in controlling the tower and demonstrate robustness against parametric and actuator uncertainties with different relative merits over each other. Indicatively, when considering root-mean-square (RMS) and peak displacement and acceleration reduction, the H ∞ had an average performance reduction of 24%, the RMPC 1 31% and the RMPC 2 28% against their uncontrolled equivalent.

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Section: Scenariomentioning

confidence: 99%

Robust structural control of a real high‐rise tower equipped with a hybrid mass damper

Koutsoloukas

Nikitas

Aristidou

2022

Structural Design Tall Build

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“…where W(k) n c * m and f(k) n c * 1 are representing the system constraints parameters according to constraints number n c . The softening constraints method is one of the constraint handling methods and it requires a lower computational burden than other approaches [37,38]. In this method, the violation between the input signal and their constraints is merged into the cost function such as:…”

Section: Mpc Designmentioning

confidence: 99%

Design and Implementation of Model Predictive Control Based PID Controller for Industrial Applications

et al. 2020

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Advanced control approaches are essential for industrial processes to enhance system performance and increase the production rate. Model Predictive Control (MPC) is considered as one of the promising advanced control algorithms. It is suitable for several industrial applications for its ability to handle system constraints. However, it is not widely implemented in the industrial field as most field engineers are not familiar with the advanced techniques conceptual structure, the relation between the parameter settings and control system actions. Conversely, the Proportional Integral Derivative (PID) controller is a common industrial controller known for its simplicity and robustness. Adapting the parameters of the PID considering system constraints is a challenging task. Both controllers, MPC and PID, merged in a hierarchical structure in this work to improve the industrial processes performance considering the operational constraints. The proposed control system is simulated and implemented on a three-tank benchmark system as a Multi-Input Multi-Output (MIMO) system. Since the main industrial goal of the proposed configuration is to be easily implemented using the available automation technology, PID controller is implemented in a PLC (Programable Logic Controller) controller as a lower controller level, while MPC controller and the adaptation mechanism are implemented within a SCADA (Supervisory Control And Data Acquisition) system as a higher controller level.

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A coupled force predictive control of vehicle stability using front/rear torque allocation with experimental verification

Hajiloo

Khajepour

Zengin

et al. 2021

Vehicle System Dynamics

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Direct relaxation of hard-constraint in Model Predictive Control

Cited by 4 publications

References 12 publications

Robust structural control of a real high‐rise tower equipped with a hybrid mass damper

Robust structural control of a real high‐rise tower equipped with a hybrid mass damper

Design and Implementation of Model Predictive Control Based PID Controller for Industrial Applications

A coupled force predictive control of vehicle stability using front/rear torque allocation with experimental verification

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