carsim-matlab co-simulation framework (MathWorks Inc)
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carsim-matlab co-simulation framework
Carsim Matlab Co Simulation Framework, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/co-simulation+framework/pm38160078-204-4-4
Average 90 stars, based on 1 article reviews
Carsim Matlab Co Simulation Framework, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/co-simulation+framework/pm38160078-204-4-4
Average 90 stars, based on 1 article reviews
carsim-matlab co-simulation framework - by Bioz Stars,
2026-10
90/100 stars
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Comparison:Article Title: Electric shovel trajectory tracking with inversion sliding mode based on Lyapunov functions Article Snippet: The harsh actual working environment and heavy weight of the electric shovel pose a great challenge to its trajectory tracking performance.. Taking into account the strong robustness and anti-interference performance of the sliding mode control method and the global stability of the inversion control method, a Lyapunov-based inversion sliding mode trajectory tracking method is proposed in this paper, and its effectiveness is verified through numerical simulation based on the electromechanical coupling dynamic model of the electric shovel and the actual electric shovel tracking experiment.. The results show that the trajectory tracking method can effectively realize the trajectory tracking of the electric shovel accompanied by tracking deviation within 0.3 m. The existence of the track slip phenomenon makes the electric shovel shake when steering, which also makes the actual operating velocity of the electric shovel fluctuate greatly. Article Title: Preview-Based Path-tracking Stability Control with Vehicle Dynamic Uncertainty via Robust Weighted LPV/H ∞ Technique. Article Snippet: This article proposes a preview-based robust path-tracking control technique for maintaining lateral stability and tracking performance of autonomous vehicles, particularly in the presence of external disturbances and modeling uncertainties.. First, a vehicle-road dynamic model with tire norm-bounded uncertainty is developed, which includes time-varying velocities and preview distances.. The lateral and yaw dynamic characteristics are also analyzed in the frequency domain. Article Title: Coordinated control method for electric vehicles having independent four-wheel driving and steering Article Snippet: . . , n) is updated to the current particle position, and if not, the position of Pb,i(i 1, . . . , n) remains unchanged, wherein after the calculation of all the particle convergence values is completed, the best point Pb,g of the particle swarm is updated to the position of the smallest particle in all the current particle convergence values, and the worst point Pw,g of the particle swarm is updated to the position of the largest particle in all the current particle convergence values, wherein the number of current iterations is increased by one, namely, Ic=Ic+1; (4) Termination of Condition Determination To ensure the solving effect of the algorithm while prevent the algorithm from falling into an infinite loop, two termination conditions are set as follows: λ ( P w , g ) > λ ( P b , g ) + ε and I c < I max ( 30 ) I c < I min wherein λ(Pb,g) and λ(Pw,g) respectively represent a final convergence value obtained according to the iteration shown in FIG. 5 when the best point and the worst point are used as Lagrange multiplier initial values, wherein after step (3) is completed, two conditions are judged, and if one of the conditions is satisfied, it indicates that the search process is not completed, and then returns to step (2) to continue the iteration, wherein if none of the above two conditions is satisfied, it indicates that the search process is completed, and meanwhile, the best point Pb,g of the current particle swarm is output as the optimal Lagrange multiplier initial value; 8) Simulation for Verification and Comparison In this embodiment, the validity of the coordinated control method of the present invention is verified by using the Article Title: Speed-Varying Path Tracking Based on Model Predictive Control for Autonomous Vehicles Article Snippet: In order to improve autonomous vehicles path-tracking accuracy and stability, a lateral–longitudinal coordination pathtracking control method is proposed.. The proposed coordination control consists of path-tracking control and speed tracking control.. First, the desired safety speed is planned according to the known road curvature and adhesion coefficient in order to prevent the tire force saturation. Article Title: Nonsingleton Gaussian type-3 fuzzy system with fractional order NTSMC for path tracking of autonomous cars. Article Snippet: Please cite this article as: Hamid Taghavifar et al., ISA Transactions , https:/ Available online 28 December 2023 0019-0578/© 2023 ISA.. Published by Elsevier Ltd. All rights reserved. https://doi.org/10.1016/j.isatra.2023.12.037 Received 7 July 2023; Received in revised form 17 November 2023; Accepted 25 D /doi.org/10.1016/j.isatra.2023.12.037 ecember 2023 ISA Transactions xxx (xxxx) xxx H. Taghavifar et al. undesirable understeer or oversteer tendencies by applying steering force to the front axle wheels [11].. However, AFS encounters limitations in path-tracking, particularly in scenarios involving front steering saturation, high-speed maneuvers, and sharp turns [12]. Control:Article Title: Electric shovel trajectory tracking with inversion sliding mode based on Lyapunov functions Article Snippet: The harsh actual working environment and heavy weight of the electric shovel pose a great challenge to its trajectory tracking performance.. Taking into account the strong robustness and anti-interference performance of the sliding mode control method and the global stability of the inversion control method, a Lyapunov-based inversion sliding mode trajectory tracking method is proposed in this paper, and its effectiveness is verified through numerical simulation based on the electromechanical coupling dynamic model of the electric shovel and the actual electric shovel tracking experiment.. The results show that the trajectory tracking method can effectively realize the trajectory tracking of the electric shovel accompanied by tracking deviation within 0.3 m. The existence of the track slip phenomenon makes the electric shovel shake when steering, which also makes the actual operating velocity of the electric shovel fluctuate greatly. Article Title: Preview-Based Path-tracking Stability Control with Vehicle Dynamic Uncertainty via Robust Weighted LPV/H ∞ Technique. Article Snippet: This article proposes a preview-based robust path-tracking control technique for maintaining lateral stability and tracking performance of autonomous vehicles, particularly in the presence of external disturbances and modeling uncertainties.. First, a vehicle-road dynamic model with tire norm-bounded uncertainty is developed, which includes time-varying velocities and preview distances.. The lateral and yaw dynamic characteristics are also analyzed in the frequency domain. Article Title: Coordinated control method for electric vehicles having independent four-wheel driving and steering Article Snippet: . . , n) is updated to the current particle position, and if not, the position of Pb,i(i 1, . . . , n) remains unchanged, wherein after the calculation of all the particle convergence values is completed, the best point Pb,g of the particle swarm is updated to the position of the smallest particle in all the current particle convergence values, and the worst point Pw,g of the particle swarm is updated to the position of the largest particle in all the current particle convergence values, wherein the number of current iterations is increased by one, namely, Ic=Ic+1; (4) Termination of Condition Determination To ensure the solving effect of the algorithm while prevent the algorithm from falling into an infinite loop, two termination conditions are set as follows: λ ( P w , g ) > λ ( P b , g ) + ε and I c < I max ( 30 ) I c < I min wherein λ(Pb,g) and λ(Pw,g) respectively represent a final convergence value obtained according to the iteration shown in FIG. 5 when the best point and the worst point are used as Lagrange multiplier initial values, wherein after step (3) is completed, two conditions are judged, and if one of the conditions is satisfied, it indicates that the search process is not completed, and then returns to step (2) to continue the iteration, wherein if none of the above two conditions is satisfied, it indicates that the search process is completed, and meanwhile, the best point Pb,g of the current particle swarm is output as the optimal Lagrange multiplier initial value; 8) Simulation for Verification and Comparison In this embodiment, the validity of the coordinated control method of the present invention is verified by using the Article Title: Speed-Varying Path Tracking Based on Model Predictive Control for Autonomous Vehicles Article Snippet: In order to improve autonomous vehicles path-tracking accuracy and stability, a lateral–longitudinal coordination pathtracking control method is proposed.. The proposed coordination control consists of path-tracking control and speed tracking control.. First, the desired safety speed is planned according to the known road curvature and adhesion coefficient in order to prevent the tire force saturation. Article Title: Nonsingleton Gaussian type-3 fuzzy system with fractional order NTSMC for path tracking of autonomous cars. Article Snippet: Please cite this article as: Hamid Taghavifar et al., ISA Transactions , https:/ Available online 28 December 2023 0019-0578/© 2023 ISA.. Published by Elsevier Ltd. All rights reserved. https://doi.org/10.1016/j.isatra.2023.12.037 Received 7 July 2023; Received in revised form 17 November 2023; Accepted 25 D /doi.org/10.1016/j.isatra.2023.12.037 ecember 2023 ISA Transactions xxx (xxxx) xxx H. Taghavifar et al. undesirable understeer or oversteer tendencies by applying steering force to the front axle wheels [11].. However, AFS encounters limitations in path-tracking, particularly in scenarios involving front steering saturation, high-speed maneuvers, and sharp turns [12]. |