An-Najah Staff

The dynamic characteristics of automobile demand are critical for national economic and revenue predictions. Automobile demand and ownership level forecasts are also the basis for travel demand models, land use-transport interaction models, and transport policies and regulations. This article develops a dynamic automobile demand simulation model using a simultaneous-equation system. The system considers the interaction between supply and demand and the resulting equilibrium. The model includes the current and lagged automobile quantity and price variables; economic, financial and operating cost variables; and income and government policy variables. The capabilities of the model are demonstrated through performing a number of simulation experiments considering various growth-development scenarios, changes in operating costs, government policies towards automobile imports, and demographic/employment shifts.

The issue of identification of dynamic parameters in open-chain industrial manipulators is addressed with emphasis on the physical feasibility of the identified set of parameters. The dynamic model on which the identification procedure is based considers rigid-link robots including a complete actuator dynamics modeling and is obtained starting from the Gibbs–Appell equations. Friction at the joints is also considered. The dynamic equations of the model are written linearly with respect to the dynamic parameters to be identified. The matrix form linear system is solved through a quadratic optimization procedure with non-linear constraints in order to ensure the physical feasibility of the identified parameters. The procedure is tested using a PUMA 560 industrial robot. A comparison between control actions and torques obtained from the Inverse Dynamic Problem considering identified parameters is performed in order to establish the validity of the proposed procedure. The set of physically feasible dynamic parameters is used in an integration of the equations of motion of the robot and the results of the simulation are compared with the robot actual movement.

Dynamic simulation in robotic systems can be considered as a useful tool not only for the design of both mechanical and control systems, but also for planning the tasks of robotic systems. Usually, the dynamic model suffers from discontinuities in some parts of it, such as the use of Coulomb friction model and the contact problem. These discontinuities could lead to stiff differential equations in the simulation process. In this paper, we present an algorithm that solves the discontinuity problem of the Coulomb friction model without applying any normalization. It consists of the application of an external switch that divides the integration interval into subintervals, the calculation of the friction force in the stick phase, and further improvements that enhance its stability. This algorithm can be implemented directly in the available commercial integration routines with event-detecting capability. Results are shown by a simulation process of a simple 1-DoF oscillator and a 3-DoF parallel robot prototype considering Coulomb friction in its joints. Both simulations show that the stiffness problem has been solved. This algorithm is presented in the form of a flowchart that can be extended to solve other types of discontinuity.