Robust Optimal Motion Cueing Algorithm Based on the Linear Quadratic Regulator Method and a Genetic Algorithm

Asadi, Houshyar; Mohamed, Shady; Lim, Chee Peng; Nahavandi, Saeid

doi:10.1109/tsmc.2016.2523906

Cited by 73 publications

(41 citation statements)

References 43 publications

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“…where P is the positive definite solution of the Riccati Equation (15). Substituting (23) and (24) into (27) yields…”

Section: Ga-based Optimal Design Of Eps Fault-tolerantmentioning

confidence: 99%

“…To overcome the limitations of selecting weighting matrices by empirical rules, genetic algorithm (GA) approach is adopted to determine the gain matrix of LQR controller [14][15][16][17]. Moreover, to our best knowledge, there only exist few studies on the design of LQR-based faulttolerant controller for the EPS system, which provides the aspiration and motivates this study.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Design of Fault‐Tolerant Controller for an Electric Power Steering System with Sensor Failures Using Genetic Algorithm

Pang

Shang

et al. 2018

Shock and Vibration

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This paper focuses on the fault-tolerant control (FTC) problem for an electric power steering (EPS) system subjected to stochastic sensor failures, and a novel fault-tolerant controller is proposed based on the genetic algorithm (GA). A mathematical model of the EPS system with sensor failures is first established, and the state feedback control law is solved by using linear quadratic regulator techniques to stabilize the closed-loop control system. Then, the dynamic response errors of the EPS system with and without sensor faults are chosen as the optimization objective function. Furthermore, the appropriate weighting matrices are evaluated to obtain the optimal fault control law by using GA. Finally, simulation results are presented to illustrate the effectiveness of the proposed control strategy.

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“…where P is the positive definite solution of the Riccati Equation (15). Substituting (23) and (24) into (27) yields…”

Section: Ga-based Optimal Design Of Eps Fault-tolerantmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Design of Fault‐Tolerant Controller for an Electric Power Steering System with Sensor Failures Using Genetic Algorithm

Pang

Shang

et al. 2018

Shock and Vibration

View full text Add to dashboard Cite

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“…The SBMPs can be used to study the driver behaviour, transportation, reliability of the autonomous vehicle, etc. [1,2]. Unfortunately, the motion signal cannot be imported to the SBMP because of the boundaries of the SBMP [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…Asadi et al [22] proposed a hybrid MCA with combination of classical and optimal MCAs to regenerate the compensation motion signal based the human motion sensation between real vehicle and SBMP user. Asadi et al [2] employed the genetic algorithm along with the linear quadratic regulator to extract the robust optimal MCA while considering the system nonlinearities. The idea of the optimal MCA by considering of the SBMP limitations is also introduced by Dagdelen et al [23] known as MCA based on model predictive control (MPC).…”

Section: Introductionmentioning

confidence: 99%

A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario

Qazani

Asadi

Nahavandi

2021

IEEE Systems Journal

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The motion cueing algorithm (MCA) is in charge of the real vehicle motion feeling regeneration for the driver of the simulation-based motion platform (SBMP) with respect to its limitations. The model predictive control (MPC) has newly employed in developing MCAs to calculate the optimal input signals for delivering the best motion feeling to the SBMP's drivers while respecting the boundaries of the platform. The stability of the MCA based on MPC has become one of the main issues for some scenarios such as urban driving scenario which involves sudden decelerations/accelerations (stop and start moving), sharp and large turn, slalom movement. The urban driving scenario destabilises the current MCA based on MPC and leads undesired motion fluctuations which creates unpleasant motion artefact for the SBMP drivers. Therefore, the displacement of the SBMP should be penalised conservatively to respect the workspace boundaries for all driving scenarios. This will make the motion conservative and can cause some motion feeling error. In this paper, the concept of terminal conditions (weights and states) are employed for the first time to design and develop a new generation of MCA based on MPC to enhance the performance of the model for different scenarios such as the heavy-traffic scenario in urban areas. Also, the stability of the MPC by considering of the terminal conditions is investigated in MCA domain. Then, the MCA based on MPC by considering of terminal conditions is developed using MATLAB software with presentation of urban motion scenario. The outcomes demonstrate the effectiveness of the designed model with common MCA based on MPC without consideration of the terminal conditions.

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“…Statistical approaches such as RSM can be employed to maximize the production of a special substance by optimization of operational factors. In contrast to conventional methods, the interaction among process variables can be determined by statistical techniques [2].…”

Section: Introductionmentioning

confidence: 99%

Two Combined Alphabetic Optimality Criteria for Second Order Rotatable Designs Constructed Using Balanced Incomplete Block Design in Four Dimensions

Mwan¹

2018

IJDSA

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The theory of optimal experimental designs is concerned with the construction of designs that are optimum with respect to some statistical criteria. Some of these criteria include the alphabetic optimality criteria such as; D-, A-, E-, T-, Gand C-criterion. Compound optimality criteria are those that combine two or more alphabetic optimality criteria. Design that require optimality criteria have specific desired properties that do very well in one design and at the same time perform poorly in another design. Thus, a compound optimality criterion gives a balance to the desirability of any two or more alphabetic optimality criteria. The present paper aims to introduce CD-and DT-criteria which are compound optimality criteria for second order rotatable designs constructed using Balanced Incomplete Block Designs (BIBDs) in four dimensions.

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Robust Optimal Motion Cueing Algorithm Based on the Linear Quadratic Regulator Method and a Genetic Algorithm

Cited by 73 publications

References 43 publications

Optimal Design of Fault‐Tolerant Controller for an Electric Power Steering System with Sensor Failures Using Genetic Algorithm

Optimal Design of Fault‐Tolerant Controller for an Electric Power Steering System with Sensor Failures Using Genetic Algorithm

A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario

Two Combined Alphabetic Optimality Criteria for Second Order Rotatable Designs Constructed Using Balanced Incomplete Block Design in Four Dimensions

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