A passivity based control methodology for flexible joint robots with application to a simplified shuttle RMS arm

The main goal is to develop a general theory for the control of flexible robots, including flexible joint robots, flexible link robots, rigid bodies with flexible appendages, etc. As part of the validation, the theory is applied to the control law development for a test example which consists of a three-link arm modeled after the shoulder yaw joint of the space shuttle remote manipulator system (RMS). The performance of the closed loop control system is then compared with the performance of the existing RMS controller to demonstrate the effectiveness of the proposed approach. The theoretical foundation of this new approach to the control of flexible robots is presented and its efficacy is demonstrated through simulation results on the three-link test arm

Passivity/Lyapunov based controller design for trajectory tracking of flexible joint manipulators

A passivity and Lyapunov based approach for the control design for the trajectory tracking problem of flexible joint robots is presented. The basic structure of the proposed controller is the sum of a model-based feedforward and a model-independent feedback. Feedforward selection and solution is analyzed for a general model for flexible joints, and for more specific and practical model structures. Passivity theory is used to design a motor state-based controller in order to input-output stabilize the error system formed by the feedforward. Observability conditions for asymptotic stability are stated and verified. In order to accommodate for modeling uncertainties and to allow for the implementation of a simplified feedforward compensation, the stability of the system is analyzed in presence of approximations in the feedforward by using a Lyapunov based robustness analysis. It is shown that under certain conditions, e.g., the desired trajectory is varying slowly enough, stability is maintained for various approximations of a canonical feedforward

Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Induction Machine Control

In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations.

Model-free control of dc/dc converters

International audienceA new "model-free" control methodology is applied for the first time to power converters, and in particular to a buck converter, and to a Cuk converter. We evaluate its performances regarding load and supply variations. Our approach, which utilizes "intelligent" PI controllers, does not require any converter identification while ensuring the stability and the robustness of the control synthesis. Simulation and experimental results show that, with a simple control structure, insensitivity to power supply fluctuations and to large load variations is ensured

Two wheel speed robust sliding mode control for electric vehicle drive

Nowadays the uses of electrical power resources are integrated in the modern vehicle motion traction chain so new technologies allow the development of electric vehicles (EV) by means of static converters-related electric motors. All mechanical transmission devices are eliminated and vehicle wheel motion can be controlled by means of power electronics. The proposed propulsing system consists of two induction motors (IM) that ensure the drive of the two back driving wheels. The proposed control structure-called independent machines- for speed control permit the achievement of an electronic differential. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling independently, every driving wheel to turn at different speeds in any curve. This paper presents the study and the sliding mode control strategy of the electric vehicle driving wheels

Toward the design of functional foods and biobased products by 3D printing: A review

Toward the design of functional foods and biobased products by 3D printing: A revie

New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm

[EN] In this paper, an optimal gain tuning method for PID controllers is proposed using a novel combination of a simplified Ant Colony Optimization algorithm and Nelder¿Mead method (ACO-NM) including a new procedure to constrain NM. To address Proportional-Integral-Derivative (PID) controller tuning for the Automatic Voltage Regulator (AVR) system, this paper presents a meta-analysis of the literature on PID parameter sets solving the AVR problem. The investigation confirms that the proposed ACO-NM obtains better or equivalent PID solutions and exhibits higher computational efficiency than previously published methods. The proposed ACO-NM application is extended to realistic conditions by considering robustness to AVR process parameters, control signal saturation and noisy measurements as well as tuning a two-degree-of-freedom PID controller (2DOF-PID). For this type of PID, a new objective function is also proposed to manage control signal constraints. Finally, real time control experiments confirm the performance of the proposed 2DOF-PIDs in quasi-real conditions. Furthermore, the efficiency of the algorithm is confirmed by comparing its results to other optimization algorithms and NM combinations using benchmark functions.This work was supported by the Vanier Canada Graduate Scholarship, the Michael Smith Foreign Study Supplements Program from the Natural Sciences and Engineering Research Council of Canada and by the Ministerio de Economia y Competitividad (Spain), project DPI2015-71443-R. It was also supported by the Bourse Mobilite Etudiante from Ministere de l'Education du Quebec, the CEMF Claudette MacKay-Lassonde Graduate Engineering Ambassador Award and the SWAAC Bourseau merite pour etudiantes de cycles superieurs.Blondin, MJ.; Sanchís Saez, J.; Sicard, P.; Herrero Durá, JM. (2018). New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Applied Soft Computing. 62:216-229. https://doi.org/10.1016/j.asoc.2017.10.007S2162296

Characterisation of the electric drive of EV: on-road versus off-road method

For system design, analysis of global performance and energy management of electric vehicles (EVs), it is common to use the efficiency map of electric traction drive. The characterisation of the efficiency map with high accuracy is then an important issue. In this study, an on-road method and an off-road method are compared experimentally to determine the efficiency map of electric drive of EVs. The off-road method requires a dedicated experimental test bed, which is expensive and time consuming. The on-road method is achieved directly in-vehicle. Experimental data, recorded during an on-road driving cycle, are used to determine the efficiency map using non-intrusive measurements from global positioning system antenna, voltage and current sensors. A versatile experimental setup is used to compare both methods on the same platform. A maximal efficiency difference of 6% is achieved in most of the torque–speed plane. It is shown that, in an energetic point of view, both methods yield similar results. © The Institution of Engineering and Technology 201