Francisco Javier Carrillo

Experimental Study on the Mechanical Effects of the Vibration-Assisted Ball-Burnishing Process

Burnishing processes are effective methods for treating pieces to increase their durability and roughness. Studies reveal that traditional burnishing can be strongly improved with the assistance of external energy sources. A vibrating module was attached to a classical burnishing tool and was tested on aluminum specimens to find the optimal vibration-assisted burnishing parameters. Vibration caused roughness improvements of the specimens and decreased the processing time by fivefold compared to traditional burnishing. At the tested frequency, no significant consequences were found on hardness and residual stresses.

Output Error Identification Algorithms for Continuous-Time Systems Operating in Closed-Loop

Abstract This paper presents off-line and recursive output error identification algorithms for linear continuous-time systems operating in closed-loop from sampled data. The resulting algorithm can be considered as the continuous-time version of the Filtered Closed Loop Output Error (F-CLOE) identification method for discrete-time systems proposed by Landau. Simulations results and the application of the proposed strategy to an experimental liquid level control system are also presented.

Study of a ball-burnishing vibration-assisted process:

This study refers to the study of the ball-burnishing process assisted by vibration. This study begins by considering that this vibration helps to make the development of this finishing process easier because it helps to deform the workpiece material more easily. Because a similar tool is not available in the market, a tool that can perform the study needed to be designed, characterised and manufactured to conduct the study by considering the critical components that are involved in the design and the physical model that characterises the operation. For these criteria, the tool operation is also characterised by evaluating the surface roughness that remains after the process occurs. Workpieces of aluminium and steel were used for the experimental validation. These results were compared to those obtained using the same tool without vibration. The roughness results obtained using the ball-burnishing vibration-assisted process improve compared to those obtained using the process without assistance for both materials tested.

Time domain identification of continuous-time systems with time delay using output error method from sampled data

Abstract This paper presents an off-line time domain output error identification algorithm for linear continuous-time systems with time delay from sampled data. The proposed method use a NonLinear Programming algorithm and needs an initialization step that is also proposed from a modification of the Yang algorithms. Simulations, as illustrated by Monte-Carlo runs, show that the obtained parameters are unbiased and very accurate.

Robust control reconfiguration of a thermal process with multiple operating modes

This paper proposes a robust control reconfiguration method applied to a thermal process with multiple operating modes. For this process, several discrete-time models may be identified with respect to non-measurable exogenous events. The parameters of the identified models change according to operating conditions. In this case, it is convenient to design a reconfiguration strategy which switches online the right controller to achieve the same performances for a given objective. An additional detection-accommodation loop is proposed to the robust control feedback. The switching performances of the plant and the stability of the corresponding switched discrete-time linear systems are discussed. The reconfiguration strategy is validated on a real thermal process.

Monitored robust force control of a milling process

Abstract This paper focuses on the important problems of tool wear or flexion that induce defects in the part. The contributions of the main control strategies are discussed. A monitored robust force control strategy is specified by a hybrid automaton. The force controller is designed from an identified plant model by a robust pole placement method based on iterative shaping of the input–output sensitivity functions. Two estimates of the cutting mean force based on the l 1 and l ∞ norms are proposed to take the great variations of the measured forces issued from the multiple teeth engaged in the part into account. The monitored robust force control strategy was implemented in a platform of experiments to evaluate two scenarios of experiments showing a good way to get more efficient performances for the monitored control strategy.

Delta approach robust controller for constant turning force regulation

The adaptive implementation of a robust controller for the constant turning force regulation problem under varying cutting conditions is presented. The discrete control structure is based on a state variable feedback regulator obtained using the delta approach optimal control theory. The controller scheme is robust in the presence of cutting process nonlinearities and disturbances. The proposed adaptive scheme uses an estimation and controller algorithm including prior knowledge of the system. Simulations and experimental results obtained with an industrial lathe show the robustness of the proposed solution.

Least squares and output error identification algorithms for continuous time systems with unknown time delay operating in open or closed loop

Abstract This paper presents two off-line output error identification algorithms for linear continuous-time systems with unknown time delay from sampled data. The proposed methods (for open and closed loop systems) use a Nonlinear Programming algorithm and need an initialization step that is also proposed from a modification of the Yang algorithm. Simulations, as illustrated by Monte-Carlo runs, show that the obtained parameters are unbiased and very accurate.

A Supervised Robust Predictive Multi-Controller for Large Operating Conditions of an Open-Channel System

Abstract In this paper, a method for designing and for choosing parameters of a supervised robust predictive multi-controller strategy (SRPMC) is proposed. The SRPMC strategy is based on a multi-model representation taking into account the large operating conditions of the real process. In this application to an open-channel system, multiple discrete models were identified for representing the overall range of discharge. The number of models is given by an algorithm initialized by the choice of only one parameter. The SRPMC strategy is compared with a PID control strategy showing its effectiveness and better performances.

An instrumental variable method for robot identification based on time variable parameter estimation

This paper considers the data-based identification of industrial robots using an instrumental variable method that uses off-line estimation of the joint velocities and acceleration signals based only on the measurement of the joint positions. The usual approach to this problem relies on a ‘tailor-made’ prefiltering procedure for estimating the derivatives that depends on good prior knowledge of the system’s bandwidth. The paper describes an alternative Integrated Random Walk SMoothing (IRWSM) method that is more robust to deficiencies in such a priori knowledge and exploits an optimal recursive algorithm based on a simple integrated random walk model and a Kalman filter with associated fixed interval smoothing. The resultant IDIM-IV instrumental variable method, using this approach to signal generation, is evaluated by its application to an industrial robot arm and comparison with previously proposed methods.