scholarly journals Model predictive control–based steering control algorithm for steering efficiency of a human driver in all-terrain cranes

2019 ◽  
Vol 11 (6) ◽  
pp. 168781401985978
Author(s):  
Ja-Ho Seo ◽  
Kwang-Seok Oh ◽  
Hong-Jun Noh
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Steering System ◽  
Driver Model ◽  
Control Technique ◽  
Change Scenario ◽  
Steering Control ◽  
Human Driver ◽  
Steering Effort

All-terrain cranes with multi-axles have large inertia and long distances between the axles that lead to a slower dynamic response than normal vehicles. This has a significant effect on the dynamic behavior and steering performance of the crane. Therefore, the purpose of this study is to develop an optimal steering control algorithm with a reduced driver steering effort for an all-terrain crane and to evaluate the performance of the algorithm. For this, a model predictive control technique was applied to an all-terrain crane, and a steering control algorithm for the crane was proposed that could reduce the driver’s steering effort. The steering performances of the existing steering system and the steering system applied with the newly developed algorithm were compared using MATLAB/Simulink and ADAMS with a human driver model for reasonable performance evaluation. The simulation was performed with both a double lane change scenario and a curved-path scenario that are expected to happen in road-steering mode.

An Experiment on Electric Power Steering (EPS) System of a CAR

2011 ◽  
Vol 110-116 ◽  
pp. 4941-4950
Author(s):  
M. Akhtaruzzaman ◽  
Norrul’ Aine Binti Mohd Razali ◽  
Mohd. Mahbubur Rashid ◽  
Amir Akramin Shafie
Keyword(s):  
Electric Power ◽  
Control Strategies ◽  
Electronic System ◽  
Steering System ◽  
Control Technique ◽  
Steering Wheel ◽  
Steering Control ◽  
Electric Power Steering ◽  
Power Steering ◽  
Steering Effort

This paper describes an experiment on Electric Power Steering (EPS) system of a car. Nowadays EPS system can be considered as a Mechatronics system that reduces the amount of steering effort by directly applying the output of an electric motor to the steering system. In this paper, the constitutions, operational mechanism and control strategies of EPS system are introduced. A potentiometer measures driver input to the steering wheel, both direction and rate of turn. This information is fed into a microcontroller that determines the desired control signals to the motor to produce the necessary torque needed to assist. Although an electro hydraulic power assisted steering system can be used to reduce the fuel consumption, but the maximum benefit can be obtained if electronic system is applied instead of the hydraulic mechanism. The paper shows that a good power steering control technique is achieved by designing a Mechatronics system. The experimental results for the designed EPS system are also analyzed in this paper.

Wide-area Power System Oscillation Damping using Model Predictive Control Technique

2011 ◽  
Vol 131 (7) ◽  
pp. 536-541 ◽  
Author(s):  
Tarek Hassan Mohamed ◽  
Abdel-Moamen Mohammed Abdel-Rahim ◽  
Ahmed Abd-Eltawwab Hassan ◽  
Takashi Hiyama
Keyword(s):  
Model Predictive Control ◽  
Power System ◽  
Predictive Control ◽  
Wide Area ◽  
Control Technique ◽  
Oscillation Damping

scholarly journals Passive Model Predictive Control on a Two-Body Self-Referenced Point Absorber Wave Energy Converter

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1731
Author(s):  
Dan Montoya ◽  
Elisabetta Tedeschi ◽  
Luca Castellini ◽  
Tiago Martins
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Power Flow ◽  
Linear Constraints ◽  
Wave Energy Converter ◽  
Control Technique ◽  
Computational Time ◽  
Energy Converter ◽  
Point Absorber

Wave energy is nowadays one of the most promising renewable energy sources; however, wave energy technology has not reached the fully-commercial stage, yet. One key aspect to achieve this goal is to identify an effective control strategy for each selected Wave Energy Converter (WEC), in order to extract the maximum energy from the waves, while respecting the physical constraints of the device. Model Predictive Control (MPC) can inherently satisfy these requirements. Generally, MPC is formulated as a quadratic programming problem with linear constraints (e.g., on position, speed and Power Take-Off (PTO) force). Since, in the most general case, this control technique requires bidirectional power flow between the PTO system and the grid, it has similar characteristics as reactive control. This means that, under some operating conditions, the energy losses may be equivalent, or even larger, than the energy yielded. As many WECs are designed to only allow unidirectional power flow, it is necessary to set nonlinear constraints. This makes the optimization problem significantly more expensive in terms of computational time. This work proposes two MPC control strategies applied to a two-body point absorber that address this issue from two different perspectives: (a) adapting the MPC formulation to passive loading strategy; and (b) adapting linear constraints in the MPC in order to only allow an unidirectional power flow. The results show that the two alternative proposals have similar performance in terms of computational time compared to the regular MPC and obtain considerably more power than the linear passive control, thus proving to be a good option for unidirectional PTO systems.

scholarly journals Reference Tracking using a Non-Cooperative Distributed Model Predictive Control Algorithm

2016 ◽  
Vol 49 (7) ◽  
pp. 1079-1084 ◽  
Author(s):  
Anca Maxim ◽  
Clara M. Ionescu ◽  
Constantin F. Caruntu ◽  
Corneliu Lazar ◽  
Robin De Keyser
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Distributed Model ◽  
Reference Tracking ◽  
Distributed Model Predictive Control ◽  
Model Predictive Control Algorithm

An Economic Model Predictive Control Approach for Wind Power Smoothing and Tower Load Mitigation

2018 ◽  
Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Model Predictive Control ◽  
Wind Power ◽  
Predictive Control ◽  
Economic Model ◽  
Control Algorithm ◽  
Fatigue Load ◽  
Economic Model Predictive Control ◽  
Control Framework

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.

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