This article focuses on identifying and fully utilizing the dynamic capabilities of a nanopositioning system to optimally trace a given trajectory. This work develops a framework for abstracting the capabilities of the piezo-actuated nanopositioning systems and a methodology for using these capabilities to generate an optimal trajectory for a particular tool path on a given nanopositioning system while satisfying all the process-related requirements. Several dynamic capabilities of a typical nanopositioning system are identified and modeled as the constraints to drive the optimization problem. First, the velocity and acceleration capabilities of each individual axes are constrained by developing a simplified dynamic model of the performance envelope, which couple velocity and acceleration capabilities of each axis, as a function of displacement. Second, input command bandwidth constraints are introduced to mitigate frequency-related tracking difficulties encountered when traversing sharp geometric features at high velocity. Finally, the accuracy requirement is satisfied by developing a dynamic model of the instantaneous following error to estimate the contour error as a function of the velocity and acceleration at each moment. The above constraints are incorporated into a computationally efficient two-pass algorithm to generate a minimum time feedrate profile for a particular positioning system for any given trajectory. Linear zigzag and cubic spline airfoil trajectories are used to demonstrate the significant improvements in time and contouring accuracy realized through such an approach.

The generation of a time-optimal feedrate trajectory under various machine and process-related constraints has received significant attention in CNC machining and robotics applications. While most of the existing feedrate planning algorithms take velocity and acceleration into the consideration as capability constraints, the introduction of higher order dynamic states, such as jerk and/or jounce, makes the feedrate planning and optimization extremely challenging, as the dimension of the planning problem is increased accordingly. This paper proposes a heuristic trajectory planning algorithm that can provide a near-optimal minimum time trajectory for problems with higher order dynamic states. The algorithm starts with a non-timeoptimal but feasible velocity trajectory, which is interpolated from a number of knot points by piecewise spline interpolation with high-order continuity. Then, the trajectory is improved by scanning and increasing the velocity at each knot points while maintaining the feasibility of the resulting trajectory. A near-optimal trajectory is achieved when the improvement in travel time from the last scan iteration is smaller than a given value. The algorithm supports the incorporation of higher order dynamic states (up to the fifth derivative of displacement) in constraints for optimization without sacrificing the computational efficiency. Examples including linear and curved toolpath are presented to illustrate the effectiveness of this algorithm for high-speed contouring.

No abstract

The Internet of Things (IoT) seems to developed in the real-world scenario due to increased utilization of sensor driven technologies. There are various research works has been proposed earlier for the network coding to ensure the reliable data transmission. However, existing research techniques doesn’t focus on the reliable route path selection which might affect the rate of data transmission. These issues are focused in the proposed research method by introducing the method namely Multi-Objective concerned Network Coding Technique (MO-NCT). In this work initially multicast tree construction is performed using Particle Swarm Optimization method. The main goal of this research work is ensuring the reliable and successful data transmission. Here the optimal network nodes will be chosen for constructing the multi cast tree. The multiple objectives considered in this work for the selection of the nodes are residual energy, remaining bandwidth level and throughput of nodes. To ensure the reliable data transmission even with the presence of larger coverage area, this work attempted to select the backup forwarder nodes which will act as intermediate hop relay nodes. The overall analysis of the research work is done in the NS2 simulation environment from which it is proved that the proposed method MO-MRP tends to achieve the optimal data transmission rate.