Additive Manufacturing using UV Polymerization of Complex Surfaces Generated by Two Main B-Splines

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CONTROLADOR MULTIEJE DE POSICIONAMIENTO DE SERVOMOTORES BLDC IMPLEMENTADO EN FPGA

ResumenEn los últimos años el aumento de la presencia de motores eléctricos empleados en la automatización de sistemas mecánicos complejos, ha motivado el desarrollo de motores y controladores con mejores prestaciones que permitan cumplir con los requerimientos de cada aplicación, en donde una de las necesidades recurrentes es el accionamiento paralelo de motores y el control de su posición. El presente trabajo propone el diseño e implementación de un controlador de posicionamiento multieje de servomotores BLDC haciendo uso de la tecnología embebida FPGA, el cual permite el accionamiento y control de posición de múltiples motores de forma independiente, pero que pueden ser accionados simultáneamente y sin retardo acumulativo, para ello se incluyen módulos independientes para la conmutación electrónica de cada motor, así como módulos para el control de su posición.Palabra(s) Clave: BLDC, Control automático, FPGA, Multieje, Perfil de trayectoria,  Posición. MULTI-AXIS POSITIONING CONTROLLER FOR BLDC SERVOMOTORS IMPLEMENTED IN FPGA AbstractIn recent years the increase in the presence of electric motors used in the automation of complex mechanical systems has motivated the development of motors and controllers with better performance that allow to meet the requirements of each application, where one of the recurring needs is the parallel drive of motors and the control of their position. The present work proposes the design and implementation of a multi-axis positioning controller for BLDC servo motors using embedded FPGA technology, which allows the drive and position control of multiple motors independently, but which can be operated simultaneously and without delay cumulative, for this are included independent modules for the electronic switching of each motor, as well as modules to control their position.Keywords: Automatic control, BLDC, FPGA, multi-axis, Position, Trajectory profile

Time-Optimal Feedrate Planning for Freeform Toolpaths for Manufacturing Applications

Optimality and computational efficiency are two desired yet competing attributes of time-optimal feedrate planning. A well-designed algorithm can vastly increase machining productivity, by reducing tool positioning time subject to limits of the machine tool and process kinematics. In the optimization, it is crucial to not overload the machining operation, saturate the actuators’ limits, or cause unwanted vibrations and contour errors. This presents a nonlinear optimization problem for achieving highest possible feedrates along a toolpath, while keeping the actuator level velocity, acceleration and jerk profiles limited. Methods proposed in literature either use highly elaborate nonlinear optimization solvers like Sequential Quadratic Programming (SQP), employ iterative heuristics which extends the computational time, or make conservative assumptions that reduces calculation time but lead to slower tool motion. This thesis proposes a new feedrate optimization algorithm, which combines recasting of the original problem into a Linear Programming (LP) form, and the development of a new windowing scheme to handle very long toolpaths. All constraint equations are linearized by applying B-spline discretization on the kinematic profiles, and approximating the nonlinear jerk equation with a linearized upper bound (so-called ‘pseudo-jerk’). The developed windowing algorithm first solves adjacent portions of the feed profile with zero boundary conditions at overlap points. Afterwards, using the Principle of Optimality, connection boundary conditions are identified that guarantee a feasible initial guess for blending the pre-solved adjacent feed profiles into one another, through a consecutive pass of LP. Experiments conducted at the sponsoring company of this research, Pratt & Whitney Canada (P&WC), show that the proposed algorithm is able to reliably reduce cycle time by up to 56% and 38% in two different contouring operations, without sacrificing dynamic positioning accuracy. Benchmarks carried out with respect to two earlier proposed feedrate optimization algorithms, validate both the time optimality and also drastic (nearly 60 times) reduction in the computational load, achieved with the new method. Part quality, robustness and feed drive positioning accuracy have also been validated in 3-axis surface machining of a part with 1030 waypoints and 10,000 constraint checkpoints