A Time-Varying Weight MPC-Based Motion Cueing Algorithm for Motion Simulation Platform

Qazani, Mohammad Reza Chalak; Asadi, Houshyar; Mohamed, Shady; Lim, Chee Peng; Nahavandi, Saeid

doi:10.1109/tits.2021.3106970

Cited by 16 publications

(4 citation statements)

References 51 publications

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“…This paper categorized these robotic machines based on their working principles and the number of DoF that they provide to facilitate smooth translational and rotational positioning in the 3d space. Furthermore, the Adaptive washout lter [6], [18][21] Optimal washout lter [22] OpDA algorithm [23] Sliding mode-based cueing [24][26], [31] Model predictive control [27] [29] Time-varying model predictive control [30], [32] Nonlinear model predictive control [33] Neural network [34] Fuzzy control system…”

Section: Discussionmentioning

confidence: 99%

A Review of Dynamic Vehicular Motion Simulators: Systems and Algorithms

et al. 2023

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Vehicular motion simulators have evolved to become an important contributor to major industries, including defense, aerospace, and vehicle manufacturing. During the past few decades, many eorts have been made towards developing robust, adaptive motion simulators with the highest level of delity and realism. Thus, it is important to recollect, in order to evaluate the current state of complex robotic systems, encouraging careful planning of further improvements in the future. This article focuses on the current motion simulators' structural designs and working principles alongside the currently developed motion control algorithms to achieve the highest delity. Furthermore, within the era of industry 4.0 and the fast-paced merging of technologies into key industries, some suggestions are made for future works which it is believed are worth investigating to provide robustness and adaptivity to the control of simulation systems, improving their delity and realism alongside reducing motion sickness experienced by the simulator operator.

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Section: Discussionmentioning

confidence: 99%

A Review of Dynamic Vehicular Motion Simulators: Systems and Algorithms

et al. 2023

Self Cite

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“…Additionally, the optimal cost function weights are crucial to the outcomes, with many scholars exploring weight optimisation. Qazani et al [35] proposed an MPC-based motion cueing algorithm to calculate suitable MPC weights with fuzzy logic units and provide more efficient utilisation of the motion simulation platform. Nevertheless, its compensator unit and the application of intelligent algorithms may affect the timeliness of the response.…”

Section: Information About Agvsmentioning

confidence: 99%

Path Planning and Trajectory Tracking for Autonomous Obstacle Avoidance in Automated Guided Vehicles at Automated Terminals

Feng,

Yang,

Zhang

et al. 2023

Axioms

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During the operation of automated guided vehicles (AGVs) at automated terminals, the occurrence of conflicts and deadlocks will undoubtedly increase the ineffective waiting time of AGVs, so there is an urgent need for path planning and tracking control schemes for autonomous obstacle avoidance in AGVs. An innovative AGV autonomous obstacle avoidance path planning and trajectory tracking control scheme is proposed, effectively considering static and dynamic obstacles. This involves establishing three potential fields that reflect the influences of obstacles, lane lines, and velocities. These potential fields are incorporated into an optimized model predictive control (MPC) cost function, leveraging artificial potential fields to ensure effective obstacle avoidance. To enhance this system’s capability, a fuzzy logic system is designed to dynamically adjust the weight coefficients of the hybrid artificial potential field model predictive controller, strengthening the autonomous obstacle avoidance capabilities of the AGVs. The tracking control scheme includes a fuzzy linear quadratic regulator based on a fuzzy logic system, a dynamics model as a lateral controller, and a PI controller as a longitudinal tracker to track the pre-set trajectory and speed autonomously. Multi-scenario simulation tests demonstrate the effectiveness and rationality of our autonomous obstacle-avoidance control scheme.

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“…In the context of parameter optimization and adjustment, numerous intelligent algorithms, such as fuzzy logic and genetic algorithms, prove to be valuable tools. These methods are frequently employed in optimizing controller parameters, showcasing robust performance, and contributing significantly to achieving superior control values in motion simulation platforms, aero-engine, and so on [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

Li,

Lu,

Cheng

et al. 2024

J Bionic Eng

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This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot (BCR) for the maintenance of the China Fusion Engineering Test Reactor (CFETR). Initially, a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach. The nonlinear components of the model are compensated through nonlinear feedback linearization. Subsequently, a fuzzy-based regulator is employed to enhance the receding horizon optimization process for achieving optimal results. A Deep Neural Network (DNN) is trained to address disturbances. Consequently, a novel hybrid controller incorporating Nonlinear Model Predictive Control (NMPC), the Fuzzy Regulator (FR), and Deep Neural Network Feedforward (DNNF), named NMPC-FRDNNF is developed. Finally, the efficacy of the control system is validated through simulations and experiments. The results indicate that the Root Mean Square Error (RMSE) of the controller with FR and DNNF decreases by 33.2 and 48.9%, respectively, compared to the controller without these enhancements. This research provides a theoretical foundation and practical insights for ensuring the future highly stable, safe, and efficient maintenance of blankets.

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A Time-Varying Weight MPC-Based Motion Cueing Algorithm for Motion Simulation Platform

Cited by 16 publications

References 51 publications

A Review of Dynamic Vehicular Motion Simulators: Systems and Algorithms

A Review of Dynamic Vehicular Motion Simulators: Systems and Algorithms

Path Planning and Trajectory Tracking for Autonomous Obstacle Avoidance in Automated Guided Vehicles at Automated Terminals

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

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