Safety and reliability of modern automobiles can be enhanced by Antilock braking system (ABS), traction control system etc. The wheel slip is generally kept within a certain predefined range for an antilock braking system by using an on-off control strategy. In case of single wheel or bicycle model only constant normal loading on the wheels is considered, whereas, for a four wheel vehicle model dynamic normal loading on the wheels and correct lateral forces are considered for the reliable design of braking system. So the controller design needs integration with the different subsystems of the vehicle dynamics model. The vehicle braking system dynamics and its control for a four wheel vehicle is illustrated here. The evaluation of performance of the ABS system under various operating conditions is done through bond graph modeling.

Combined regenerative and antilock braking in electric/hybrid-electric vehicles provides higher safety in addition to energy storing capability. Development of control law for this type of braking system is a challenging task. A sliding mode controller (SMC) for ABS is developed to maintain the optimal slip value. The braking of the vehicle, performed by using both regenerative and antilock braking, is based on an algorithm which decides on how to distribute the braking force between the regenerative braking and the antilock braking in emergency/panic braking situations as well as in normal city driving conditions. The passenger comfort is improved when a sliding mode ABS controller is used in place of standard ABS controller for the mechanical braking part.

Myoelectric signals are weak signals (order of micro-volts) generated by the muscular activity. The contraction of muscles can generate microvolt level electrical signals within the muscles. These signals can be realized on the surface of skin above the muscles or within the muscles using a needle. Based on this phenomenon, it was thought of implementing a myoelectric control to prosthetic hands which would use a surface electrode to receive myoelectric signals from disabled persons’ residual limb. A prothetic hand is a customized limb that can be fitted on a disabled persons’ residual limb to assist them in manipulation, which can be only performed by hands. This chapter demonstrates the principle of controlling the prosthetic hand by Surface EMG signals on a wooden prototype. The developed prosthetic hand also uses force sensor and proximity sensor to aid the EMG sensor for hybrid control. The chapter describes the various steps for development of low cost surface EMG controlled prosthetic hand.

The work presented in this chapter is twofold. Firstly, the robust adaptive position control of a 6 degree of freedom (6dof) parallel robot called C5 is addressed. Coupling of the sliding modes and Multi-Layer Perceptron (MLP) neural networks form the basis of the proposed approach. This means that for the derivation of the control law, there is no requirement for the inverse dynamic model. The MLP neural network is integrated into the control scheme for the estimation of both gravity and friction forces alongside the dynamic effects, which do not constitute part of the model. The non-linearity problem present in neural networks is resolved using Taylor series expansion. The proposed approach permits the adjustment of the neural network parameters and sliding mode control terms by considering a reference model and the closed-loop stability, in the Lyapunov sense. Secondly, the force control of a C5 parallel robot is also addressed. It is based on the multi-layer perceptron (MLP), without any ex-ante knowledge of the dynamic model of the robot. Otherwise, the control type that we propose to apply is a black box one. The neural network corrective is used adaptively in the goal to ensure the system stability in the Lyapunov sense. We implemented the proposed approaches on a C5 parallel robot and carried tests of robustness against external influences in order to check the originality of our work.

This chapter discusses the necessary conditions for the successful design of a driving simulator. This success is assessed, among other factors, by the quality of the rendered motions, when driving the simulator.

We discuss throughout this chapter, the philosophy of driving simulation to better explain the challenges of these applications. Particular attention will be paid to the interaction between the various entities, making up a simulation system operational. This interaction is intended to highlight the importance of mechatronics in the successful design of such a simulator.

This chapter deals with robust fault detection and isolation using the bond graph (BG) approach and linear filters. The bond graph tool is used to model the dynamic system and the uncertainties on the sensors and actuators. The same model is used to generate systematically the analytical redundancy relations and the thresholds. A specific form of digital linear filter is used to evaluate the residuals and to ameliorate the robustness and the detectability of the faults. the developed procedure is applied to experimental data of an electromechanical system which is a subsystem of a mobile robot named Robotino.

In this chapter, a methodology for plant fault detection and isolation using Bond Graph modeling tool is presented, the motivation using bond graph is that the dynamic model of the system and fault detection and isolation are performed using the same tool. Based on bond graph properties, the conditions of diagnosability are carried out structurally on the graph representing the system. The considered plant fault is a break of the transmission axle on an electromechanical system representing a quarter of an autonomous vehicle, named Robucar. Co-simulation using a vehicle simulator CALLAS/Simulink is given to show the efficiency of the proposed methodology.

In this chapter the problem of structural reconfigurability analysis is introduced and applied on over-actuated electric vehicle. This task is performed through the use of the bond graph tool, which is an adequate tool for dynamic modeling of complex systems, and for fault detection adn isolation. The latter is performed by exploiting the structural and causal properties of the bond graph model to generate analytical redundancy relations in a systematic manner. Then, the actual system diagnosis information is exploited to study the different possibilities of system structural reconfigurability conditions. Finally, an algorithm is proposed, so that this study can be performed in a systematic way.

Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems and avoiding the execution of an unsafe behaviour. This chapter deals with Robust Decision Making (RDM) for fault detection of electromechanical systems by combining the advantages of Bond Graph (BG) modeling and Fuzzy logic reasoning. A fault diagnosis method implemented in two stages is proposed. In the first stage, the residuals are deduced from the BG model allowing the building of a Fault Signature Matrix (FSM) according to the sensitivity of residuals to different parameters. In the second stage, the result of FSM and the robust residual thresholds are used by the fuzzy reasoning mechanism in order to evaluate a degree of detectability for each set of components. Finally, in order to make robust decision according to the detected fault component, an analysis is done between the output variables of the fuzzy system and components having the same signature in the FSM. The performance of the proposed fault diagnosis methodology is demonstrated through experimental data of an omni directional robot.

This chapter concerns real-times hexapod robot force control. Based on an operational trajectory planner, a computed torque control for each leg of hexapod robot is presented. This approach takes into account the force distribution on the robot legs in real time and the hexapod dynamic model. First, Kinematic and dynamic modeling are presented. Then, a methodology for the optimal force distribution is given. The issue of force distribution is expressed on the basis of nonlinear programming terms that take into consideration both the equality and the inequality of constraints. Subsequently, nonlinear inequalities of friction constraints can be replaced by a combination of linear equalities and inequalities [22]. The original constraining nonlinear programming problem is then transformed to a problem of a quadratic optimization. Therefore, the overall hexapod computed torque control is presented. Finally some simulations are also given in order to show the effectiveness of the proposed approach.

In this chapter, a robotic concept for the prostatic brachytherapy is described. Based on adaptive tracking of mobile targets under ultrasound control using an industrial robot manipulator, the concept integrates two main tasks: mobile target tracking and on-line supervision. The mobile target corresponds to the track at the millimeter scale to the cancerous tissues. This task is done after detection of the prostate contour applied on acquired ultrasound images. The targets are selected safety with manual or automatic approaches, through a virtual environment, where their coordinates are transferred to the robot. The latter is controlled adaptively according to the target position, thus realizing the both brachytherapy motions, related to the needle insertion and the seed injection. The on-line supervision of the robotic concept is performed, based on quantitative approach, it improves the safety during the brachytherapy motions. A fault diagnosis strategy is applied to detect a possible change of the operation modes of the joint actuator. Experimental results are applied on a prostate phantom using one access point, they show the advantage of the described concept in reducing trauma and recovery times for real patients

The hybrid hyper-redundant robots have a very large number of controlled degrees of freedom. This work presents geometric and kinematic modeling using to design an hybrid hyper-redundant robot. The modular structure studied here is considered as a very redundant mechanism that leads to complicated kinematic model. Because the mechanical architecture of the manipulator is simplified, geometric resolution of the problem is made analytically and a specific solution to the case of hybrid hyper-redundant robot formed by the stacking of parallel mechanisms is obtained. It is based on inverse kinematics of each module which the Jacobian matrix (6 x 6) represents the relationship between the speed of the end effectors (linear and angular velocities) and the active joint velocities. Finally, a case study consisting of solving geometric and kinematic analysis of an 18-degrees of freedom (DOF) hyper-redundant manipulator is presented.

Robot grinding/polishing of an unknown surface requires its 3D measurement . An existing method is based on linear variable differential transformer (LVDT) that has limitations such as contact with object and low speed. In this work, a non-contact laser sensor is studied to provide faster and more accurate measurement. Measuring an unknown 3D surface of a turbine vane is challenging because some positions of the turbine vane surface are specular after being polished or grinded. In these situations, little or no measurement data are received and the reconstruction of the 3D surface profile is difficult. Here, we develop a measurement algorithm to process the laser sensor measurement data, and to reconstruct 3D profiles of these surfaces. In particular, the corrupted data due to the specular reflection are processed to obtain a nominal 3D surface profile. Three interpolation algorithms are investigated for restoring corrupted data due to specular reflection. It is found that the linear compensations of control points must be carried out before interpolation. It is necessary to obtain approximately real data of specular reflection edge by linear compensation according to true surface shape. The results of 2D profiles processed by three interpolation algorithms are displayed and compared in the same coordinates. The findings indicate that the piecewise cubic Hermite interpolation of turbine vane surface is the most promising method to restore corrupted data. The results indicate that the measurement system can meet the repairing requirement of turbine vanes .