Performance indices for robotic manipulators: a review of the state of the art

The performance indices are important tools for motion planning and design of robot manipulators. In this paper we present a collection of some of the performance indices that have generated interest in the robotics community. These indices are four different types: kinetostatic performance indices, dynamic performance indices, indices of joint limits, and finally global performance indices. In addition, we review the strategies that have been proposed to solve the problems that occur when the units of the Jacobian matrix elements are not homogeneous. At the end of this paper, we propose a set of global performance indices that can be useful in the design of robot manipulators.

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

Frequency control support of a wind-solar isolated system by a hydropower plant with long tail-race tunnel

Pumped storage hydro plants (PSHP) can provide adequate energy storage and frequency regulation capacities in isolated power systems having significant renewable energy resources. Due to its high wind and solar potential, several plans have been developed for La Palma Island in the Canary archipelago, aimed at increasing the penetration of these energy sources. In this paper, the performance of the frequency control of La Palma power system is assessed, when the demand is supplied by the available wind and solar generation with the support of a PSHP which has been predesigned for this purpose. The frequency regulation is provided exclusively by the PSHP. Due to topographic and environmental constraints, this plant has a long tail-race tunnel without a surge tank. In this configuration, the effects of pressure waves cannot be neglected and, therefore, usual recommendations for PID governor tuning provide poor performance. A PI governor tuning criterion is proposed for the hydro plant and compared with other criteria according to several performance indices. Several scenarios considering solar and wind energy penetration have been simulated to check the plant response using the proposed criterion. This tuning of the PI governor maintains La Palma system frequency within grid code requirements.