scholarly journals A modeling system based on dynamic constraints

1988 ◽  
Author(s):  
Ronen Barzel ◽  
Alan H. Barr
Keyword(s):  
Dynamic Constraints

Task-based torque minimization of a 3-PṞR spherical parallel manipulator

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Soheil Zarkandi
Keyword(s):  
Closed Form ◽  
Dynamic Modeling ◽  
Dynamic Equation ◽  
Parallel Manipulator ◽  
Optimization Problem ◽  
Dynamic Constraints ◽  
Part C ◽  
Euler Approach ◽  
Three Degree Of Freedom ◽  
Spherical Parallel Manipulator

Abstract A comprehensive dynamic modeling and actuator torque minimization of a new symmetrical three-degree-of-freedom (3-DOF) 3-PṞR spherical parallel manipulator (SPM) is presented. Three actuating systems, each of which composed of an electromotor, a gearbox and a double Rzeppa-type driveshaft, produce input torques of the manipulator. Kinematics of the 3-PṞR SPM was recently studied by the author (Zarkandi, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 2020, https://doi.org/10.1177%2F0954406220938806). In this paper, a closed-form dynamic equation of the manipulator is derived with the Newton–Euler approach. Then, an optimization problem with kinematic and dynamic constraints is presented to minimize torques of the actuators for implementing a given task. The results are also verified by the SimMechanics model of the manipulator.

Efficient time-optimal feedrate planning under dynamic constraints for a high-order CNC servo system

2013 ◽  
Vol 45 (12) ◽  
pp. 1538-1546 ◽  
Author(s):  
Jian-Xin Guo ◽  
Ke Zhang ◽  
Qiang Zhang ◽  
Xiao-Shan Gao
Keyword(s):  
Servo System ◽  
High Order ◽  
Dynamic Constraints ◽  
Feedrate Planning ◽  
Time Optimal

A New Method of 6-DOF Serial Robot’s Trajectory Planning under Multi-Constraints

2014 ◽  
Vol 602-605 ◽  
pp. 1352-1357 ◽  
Author(s):  
Yong Ting Zhao ◽  
Bin Zheng ◽  
Hong Lin Ma
Keyword(s):  
Coordinate System ◽  
Trajectory Planning ◽  
Angular Displacement ◽  
Joint Space ◽  
New Method ◽  
Position Information ◽  
Physical Constraints ◽  
Dynamic Constraints ◽  
Quaternion Interpolation ◽  
And Performance

This paper proposes a new method of 6-DOF serial robot’s trajectory planning. Ensuring to satisfy the physical constraints of space conditions, the robot’s trajectory is interpolated in the Cartesian coordinate system, and using quaternion interpolation to solve the multiple solution problem in RPY interpolation. Meanwhile, the interpolated position information is transformed into the angular displacement information of the joint coordinate system, and the joint space trajectory planning is achieved using the genetic algorithms integrated velocity, acceleration, jerk and torque and other important kinematic and dynamic constraints. In robot safety and stability, the method is better than the general approach, and it has both the ideal trajectory parameters of the global search ability and performance planning.

Coordinated Control for Novel Full Hybrid Vehicles

2013 ◽  
Vol 860-863 ◽  
pp. 1073-1077 ◽  
Author(s):  
Zhi Guo Kong ◽  
Hong Wei Zhang ◽  
Zi Ning Tang
Keyword(s):  
Control Method ◽  
Dynamic Performance ◽  
Coordinated Control ◽  
Rate Of Change ◽  
Adjustment Process ◽  
Accelerator Pedal ◽  
Dynamic Constraints ◽  
Electric Bus ◽  
The Stability ◽  
Working Point

In order to improve the performance of a new type of full hybrid electric bus, this paper puts forward a set of coordinated control method to adjust the operation of the engine and two motors. In the engine start-stop logic control, comprehensive consideration of SOC, the speed of the bus and the accelerator pedal stroke are performed, while hysteresis control is introduced to improve the stability of the control; In the engine working point adjusting control, not only the engine speed command rate of change was optimized, but also the output torque rate was optimized to match the air injection and exhaust, etc. Further, the method based on dynamic constraints was used to optimize the working point adjustment process. At present, there are hundreds of busses operates in route. Results verify the feasibility and effectiveness of the control method. The vehicle has good fuel economy, and the dynamic performance and driving comfort are also greatly improved.

Trajectory Generation From Paths for Autonomous Ground Vehicles

2020 ◽  
Author(s):  
Letian Lin ◽  
J. Jim Zhu
Keyword(s):  
Phase Plane ◽  
Longitudinal Velocity ◽  
Initial Boundary ◽  
Limit Function ◽  
Ground Vehicles ◽  
Reverse Time ◽  
Dynamic Constraints ◽  
Autonomous Ground Vehicles ◽  
Practical Concern ◽  
Initial Boundary Condition

Abstract Path-to-trajectory conversion problem for car-like autonomous ground vehicles has been studied in various ways. It is challenging to generate a trajectory which is dynamically feasible for the vehicle and comfortable for the passengers. An important practical concern of low computational costs makes the problem even more difficult. In this work, a path-to-trajectory converter is developed using a novel receding-horizon type suboptimal algorithm. By transforming the dynamic constraints to a longitudinal velocity limit function in the velocity-acceleration phase plane, a time-sub-optimal trajectory satisfying the dynamic constraints and the initial boundary condition is generated by computing the maximum constant acceleration in the down-range horizon. The portion of the trajectory approaching the end of the path is generated in reverse time. As illustrated by some simulation results and validation on a full-scale Kia Soul EV, the proposed path-to-trajectory conversion algorithm is able to account for dynamic constraints of the vehicle and guarantees passenger comfort.

scholarly journals Should I stay or should I go? Evidence accumulation drives decision making in human drivers

2020 ◽  
Author(s):  
Arkady Zgonnikov ◽  
David Abbink ◽  
Gustav Markkula
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Cognitive Process ◽  
Response Times ◽  
Process Models ◽  
Cognitive Mechanisms ◽  
Naturalistic Decision Making ◽  
Dynamic Constraints ◽  
Evidence Accumulation ◽  
Out Of Sample

Laboratory studies of abstract, highly controlled tasks point towards noisy evidence accumulation as a key mechanism governing decision making. Yet it is unclear whether the cognitive processes implicated in simple, isolated decisions in the lab are as paramount to decisions that are ingrained in more complex behaviors, such as driving. Here we aim to address the gap between modern cognitive models of decision making and studies of naturalistic decision making in drivers, which so far have provided only limited insight into the underlying cognitive processes. We investigate drivers' decision making during unprotected left turns, and model the cognitive process driving these decisions. Our model builds on the classical drift-diffusion model, and emphasizes, first, the drift rate linked to the relevant perceptual quantities dynamically sampled from the environment, and, second, collapsing decision boundaries reflecting the dynamic constraints imposed on the decision maker’s response by the environment. We show that the model explains the observed decision outcomes and response times, as well as substantial individual differences in those. Through cross-validation, we demonstrate that the model not only explains the data, but also generalizes to out-of-sample conditions, effectively providing a way to predict human drivers’ behavior in real time. Our results reveal the cognitive mechanisms of gap acceptance decisions in human drivers, and exemplify how simple cognitive process models can help us to understand human behavior in complex real-world tasks.

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