Rodolfo Haber-Haber

An optimal fuzzy control system in a network environment based on simulated annealing. An application to a drilling process

This paper shows a strategy for the optimal tuning of a fuzzy controller in a networked control system using an offline simulated annealing approach. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) performance index. The goal is to obtain the optimal tuning parameters for the input scaling factors where the ITAE performance index is minimized. In this study, a step change in the force reference signal is considered a disturbance, and the goal is to assess how well the system follows set-point changes using the ITAE criterion. In order to improve the efficiency of high-performance drilling processes while preserving tool life, the current study focuses on the design and implementation of an optimal fuzzy-control system for drilling force. Simulation results demonstrate good convergence properties of the proposed strategy. Experimental tests of the drilling of two materials (GGG40 and 17-4 PH) corroborate the excellent transient response and the minimum overshoot predicted by the simulation results. Thus, the optimal fuzzy control system reduces the influence of the increase in cutting force that occurs at larger drill depths, eliminating the risk of rapid drill wear and catastrophic drill breakage.

Lyapunov Stable Control of Robot Manipulators: A Fuzzy Self-Tuning Procedure

In this paper we present a fuzzy adaptation scheme for PD control with gravity compensation of robot manipulators. We demonstrate, by taking into account the full nonlinear and multivariable nature...

System Identification of the High Performance Drilling Process for Network-Based Control

A simple, fast, network-based experimental procedure for identifying the dynamics of the high-performance drilling (HPD) process is proposed and successfully applied. This identification technique utilizes a single-input (feed rate), single-output (resultant force) system with a dual step input function. The model contains the delays of both the network architecture (a PROFIBUS type network) and the dead time related with the plant dynamic itself. Classical identification techniques are used to obtain first order, second order, and third order models on the basis of the recorded input/output data. The developed models relate the dynamic behavior of resultant force versus commanded feed rate in HPD. Model validation is performed through error-based performance indices and correlation analyses. Experimental verification is performed using two different work piece materials. The models match perfectly with real-time force behavior in drilling operations and are easily integrated with many control strategies. Furthermore, these results demonstrate that the HPD process is somewhat non-linear with a remarkable difference in gain due to work piece material; however, the dynamic behavior does not change significantly.Copyright

Fuzzy Control of Spindle Torque in High-Speed Milling Processes

This paper presents the design and implementation of a two-input/ two-output fuzzy logic-based torque control system embedded in an open architecture computer numerical control (CNC) for optimizing the material removal rate in high-speed milling processes. The control system adjusts the feed rate and spindle speed simultaneously as needed to regulate the cutting torque using the CNCs own resources. The control system consists of a two-input (i.e., torque error and change of error), two-output (i.e., feed rate and spindle speed increment) fuzzy controller, which is embedded within the kernel of a standard open control. Two approaches are tested, and their performance is assessed using several performance measurements. These approaches are a two-input/two-output fuzzy controller and a single-output (i.e., feed rate modification only) fuzzy controller. The results demonstrate that the proposed control strategy provides better accuracy and machining cycle time than other strategies, thus increasing the metal removal rate.

Using simulated annealing for optimal tuning of a PID controller for time-delay systems: an application to a high-performance drilling process

This paper shows a strategy based on simulated annealing for the optimal tuning of a PID controller to deal with time-varying delay. The main goal is to minimize the integral time absolute error (ITAE) performance index and the overshoot for a drilling-force control system. The proposed strategy is compared with other classic tuning rules (the Ziegler-Nichols and Cohen-Coon tuning formulas). Other tuning laws derived from genetic algorithms and the Simplex search algorithm for unconstrained optimization are also included in the comparative study. The results demonstrate that simulated annealing provides an optimal tuning of the PID controller, which means better transient response (less overshoot) and less ITAE than with other methods.

Fuzzy Logic Based Drilling Force Control in a Network-Based Application

In order to improve efficiency of high-performance drilling processes while preserving tool life, the current study focuses on the design and implementation of an optimal fuzzy-control system for drilling force. The main topic of this study is the design and implementation of a networked fuzzy controller. The control algorithm is connected to the process through a multipoint interface (MPI) bus, a proprietary programming and communication interface for peer-to-peer networking that resembles the PROFIBUS protocol. The output (i.e., feed-rate) signal is transmitted through the MPI; therefore, network-induced delay is unavoidable. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) criterion. In this study, a step in the force reference signal is considered a disturbance, and the goal is to assess how well the system follows set-point changes using the ITAE criterion. The main advantage of the approach presented herein is the design of an optimal fuzzy controller using a known maximum allowable delay to deal with uncertainties and nonlinearities in the drilling process and delays in the network-based application. In order to suppress the cutting-force increase, the feed rate is decreased gradually as the drilling depth increases, and the cutting force is quite well regulated at the given setpoint. The good transient response is verified by improvements in the integral time absolute error (11.77), integral time square error (2.912) and integral of absolute error (12.81) performance indices. Moreover, the experimental results without oscillations and overshoot corroborate that increases and fluctuations in force drilling can be suppressed despite an increase in drilling depth. Thus, the drilling process can be stabilized and the risk of drill failure can be greatly reduced through a fuzzy-control system.Copyright

Networked Fuzzy Control System for a High-Performance Drilling Process

In order to improve drilling efficiency while preserving tool life, the current study focuses on the design and implementation of a simple, optimal fuzzy-control system for drilling force. The main topic of this study is the design and implementation of a networked fuzzy controller. The control system consists of a two-input (force error and change of error), single-output (feed-rate increment) fuzzy controller. The control algorithm is connected to the process through a multipoint interface (MPI) bus. The output (i.e., feed-rate) signal is transmitted through the MPI; therefore, network-induced delay is unavoidable. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) criterion. The main advantage of the approach presented herein is the design of a simple fuzzy controller using a known maximum allowable delay to deal with uncertainties and nonlinearities in the drilling process and delays in the network-based application. The results demonstrate that the proposed control strategy provides an excellent transient response without overshoot and a slightly higher drilling time than the CNC working alone (uncontrolled). Therefore, the fuzzy-control system reduces the influence of the increase in cutting force and torque that occurs as the drill depth increases, thus eliminating the risk of rapid drill wear and catastrophic drill breakage.Copyright