Michael Defoort

A Robust Observer-Based Sensor Fault-Tolerant Control for PMSM in Electric Vehicles

This paper investigates the problem of automatic speed tracking control of an electric vehicle (EV) that is powered by a permanent-magnet synchronous motor (PMSM). A reconfiguration scheme, based on higher order sliding mode (HOSM) observer, is proposed in the event of sensor faults/failures to maintain a good control performance. The corresponding controlled motor output torque drives EVs to track the desired vehicle reference speed for providing uninterrupted vehicle safe operation. The effectiveness of the overall sensor fault-tolerant speed tracking control is highlighted when an EV is subjected to disturbances like aerodynamic load force and road roughness using high-fidelity software package CarSim. Experiments with a 26-W, three-phase PMSM are presented to demonstrate the validity of the proposed fault-detection scheme.

Robust finite time observer design for multicellular converters

In this article, a nonlinear finite time observer is designed for multicellular converters. The aim is to estimate the capacitor voltages by taking into account the hybrid behaviour of the converter. This article extends the validity of the strong Lyapunov function, proposed in Moreno and Osorio (Moreno, J., and Osorio, M. (2008), ‘A Lyapunov Approach to Second Order Sliding Mode Controllers and Observers’, in Proceedings of the IEEE Conference on Decision and Control, New Orleans, USA, pp. 2856–2861), in order to deeply study the reaching time estimation and robustness of the homogeneous finite time observer given in Perruquetti et al. (Perruquetti, W., Floquet, T., and Moulay, E. (2008), ‘Finite Time Observers: Application to Secure Communication’, IEEE Transactions on Automatic Control, 53, 356–360). The proposed approach enables the stabilisation of the observation errors in spite of the presence of perturbations and uncertainties. Some simulations and comparisons with the super-twisting sliding mode observer highlight the efficiency of the proposed strategy.

Motion planning for cooperative unicycle-type mobile robots with limited sensing ranges: A distributed receding horizon approach

This paper presents a decentralized motion planner for a team of nonholonomic mobile robots subject to constraints imposed by sensors and the communication network. The motion planning scheme consists of decentralized receding horizon planners that reside on each vehicle to achieve coordination among flocking agents. The advantage of the proposed algorithm is that each vehicle only requires local knowledge of its neighboring vehicles. The main requirement for designing an optimal conflict-free trajectory in a decentralized way is that each robot does not deviate too far from its presumed trajectory designed without taking the coupling constraints into account. A comparative study between the proposed algorithm and other existing algorithms is provided in order to show the advantages, especially in terms of computing time. Finally, experiments are performed on a team of three mobile robots to demonstrate the validity of the proposed approach.

High-gain observer with sliding mode for nonlinear state estimation and fault reconstruction

Abstract This paper develops a high gain observer with multiple sliding modes for simultaneous state and fault estimations for MIMO nonlinear systems. The novelty lies in the observer design that employs the combination of high-gain observer and sliding mode observer. The proposed observer does not impose the small-Lipschitz-constant condition on the system nonlinearity. By imposing a structural assumption on the nonlinear fault distribution matrix, the observability of the faults/unknown inputs w.r.t. the outputs is safeguarded and sliding modes are utilized for their reconstruction. The reconstruction of the faults from the sliding mode only relies on the output estimation error and thus can be implemented online together with the state estimation. Finally, an application to flexible joint robotic arm is used to illustrate the proposed method.

Output Feedback Active Suspension Control With Higher Order Terminal Sliding Mode

The control of an automotive suspension system using hydraulic actuators is a highly complex nonlinear control task dealing with system nonlinearities, external disturbances, and uncertainties. In this work, an output feedback active suspension control scheme is proposed to achieve a ride comfort while maintaining the road holding for the vehicle. To design the controller, the states of the nonlinear system are first estimated using a highgain observer where the suspension stroke is the only measurable output. The controller is then designed using a recursive derivative nonsingular higher order terminal sliding mode approach that avoids singularity. The practical stability for the closed-loop observer-controller pair is established. Simulation results for the quarter-wheel vehicle over various road conditions demonstrate the effectiveness of the proposed control in improving the suspension performance in both the time and frequency domains.

Adaptive estimation of EEG for subject-specific reactive band identification and improved ERD detection.

The event-related desynchronization (ERD) is a magnitude decrease phenomenon which can be found in electroencephalogram (EEG) mu-rhythm in a certain narrow frequency band (reactive band) during different sensorimotor tasks and stimuli. The success of ERD detection depends on proper identification of subject specific reactive band. An adaptive algorithm band limited multiple Fourier linear combiner (BMFLC) is employed in this paper for identification of subject specific reactive band for real-time ERD detection. With the time-frequency mapping obtained with BMFLC, a procedure is formulated for reactive band identification. Improved classification is obtained by applying this method to a standard BCI data set compared to traditional ERD detection methods. Study conducted with 8 subjects drawn from BCI Competition IV data set show a 22% increase in ERD and 10% improvement in classification with the proposed method compared to standard ERD based classification.

Hybrid sliding mode observer for switched linear systems with unknown inputs

Abstract This paper addresses the state observation and unknown input estimation of a class of switched linear systems with unknown inputs. This class of systems may have modes in which the state is not fully observable. A state transformation allows implementing two suitable reduced-order observers. The first one, based on second order sliding mode techniques, is proposed to reconstruct the discrete state in the presence of unknown inputs. The second one, based on gathering partial information from individual modes of the switched system and on higher order sliding mode techniques, is introduced to estimate the continuous state. Then, the observer injection signal of the first second order sliding mode observer is used to estimate the unknown inputs. Simulation results highlight the efficiency of the proposed method.

Simultaneous Estimation of Road Profile and Tire Road Friction for Automotive Vehicle

The longitudinal motion control of automotive vehicles is heavily reliant on information about the time-varying tire road friction coefficient. In the presence of varying road roughness profiles, the effective vertical load on each wheel varies dynamically, influencing the tire friction. In this paper, we integrated the vertical and longitudinal dynamics of a quarter wheel to form an integrated nonlinear model. In the modeled dynamics, the time-varying random road profile and the tire friction are treated as unknown inputs. To estimate these unknown inputs and states simultaneously, a combination of nonlinear Lipschitz observer and modified super-twisting algorithm (STA) observer is developed. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is established. Simulation results performed with the high-fidelity vehicle simulation software CarSim demonstrate the effectiveness of the proposed scheme in the estimation of states and unknown inputs.

Distributed Constraint Reasoning Applied to Multi-robot Exploration

Exploration of an unknown environment is one of the major applications of Multi-Robot Systems. Many works have proposed multi-robot coordination algorithms to accomplish exploration missions based on multi-agent techniques. Some of these works focus on multi-robot exploration under communication constraints. In this paper, we propose an original way to formalize and solve this issue. Our proposal relies on distributed constraint satisfaction problems (disCSP) which are an extension of classical constraint satisfaction problems (CSP). Compared to other works, our proposal is fully distributed and guaranties the exploration of an unknown environment with maintenance of connectivity between all the members of a robots’ team.

On finite time observer design for multicellular converter

The aim of this paper is to estimate the capacitors voltages by tacking the hybrid behavior of the multicellular converter into account. A nonlinear finite time observer is given in order to solve this problem. The stability and properties of the proposed homogeneous finite time observer are studied using Lyapunov theory. Our approach enables the stabilization of the observation errors in spite of the presence of perturbations. Simulations highlight the efficiency of the proposed strategy.