Maarouf Saad

Sliding-Mode Robot Control With Exponential Reaching Law

In this paper, sliding-mode control is applied on multi-input/multi-output (MIMO) nonlinear systems. A novel approach is proposed, which allows chattering reduction on control input while keeping high tracking performance of the controller in steady-state regime. This approach consists of designing a nonlinear reaching law by using an exponential function that dynamically adapts to the variations of the controlled system. Experimental study was focused on a MIMO modular robot arm. Experimental results are presented to show the effectiveness of the proposed approach, regarding particularly the chattering reduction on control input in steady-state regime.

Identification and Real-Time Control of an Electrohydraulic Servo System Based on Nonlinear Backstepping

This paper studies the identification and the real-time control of an electrohydraulic servo system. The control strategy is based on the nonlinear backstepping approach. Emphasis is essentially on the tuning parameters effect and on how it influences the dynamic behavior of the errors. While the backstepping control ensures the global asymptotic stability of the system, the tuning parameters of the controller, nonetheless, do greatly affect the saturation and chattering in the control signal, and consequently, the dynamic errors. In fact, electrohydraulic systems are known to be highly nonlinear and non-differentiable due to many factors, such as leakage, friction, and especially, the fluid flow expression through the servo valve. These nonlinear terms appear in the closed loop dynamic errors. Their values are so large that in the presence of a poor design, they can easily overwhelm the effect of the controller parameters. Backstepping is used here because it is a powerful and robust nonlinear strategy. The experimental results are compared to those obtained with a real-time proportional-integral-derivative (PID) controller, to prove that classic linear controllers fail to achieve a good tracking of the desired output, especially, when the hydraulic actuator operates at the maximum load. Before going through the controller design, the system parameters are identified. Despite the nonlinearity of the system, identification is based on the recursive least squares method. This is done by rewriting the mathematical model of the system in a linear in parameters (LP) form. Finally, the experimental results will show the effectiveness of the proposed approach in terms of guaranteed stability and zero tracking error

A higher level path tracking controller for a four-wheel differentially steered mobile robot

A variety of approaches for path tracking control of wheeled mobile robots have been implemented. While most of these are based on controlling the robot dynamics, they are not applicable if the robot dynamics are inaccessible. In this paper, a fuzzy logic controller (FLC) for the path tracking of a wheeled mobile robot based on controlling the robot at a higher level is presented. The controller is highly robust and flexible and automatically follows a sequence of discrete waypoints, and no interpolation of the waypoints is needed to generate a continuous reference trajectory. The speeds are varied depending on the variations in the path and on the posture of the robot. The heuristic rules of the FLC are based on an analogy with a human driving a car and the optimization of the controller is based on experimentation. The implementation on a P3-AT mobile robot shows the effectiveness of the proposed approach.

Learning disaggregation technique for the operation of long‐term hydroelectric power systems

This paper describes a nonlinear disaggregation technique for the operation of multireservoir systems. The disaggregation is done by training a neural network to give, for an aggregated storage level, the storage level of each reservoir of the system. The training set is obtained by solving the deterministic operating problem of a large number of equally likely flow sequences. The training is achieved using the back propagation method, and the minimization of the quadratic error is computed by a variable step gradient method. The aggregated storage level can be determined by stochastic dynamic programming in which all hydroelectric installations are aggregated to form one equivalent reservoir. The results of applying the learning disaggregation technique to Quebecs La Grande river are reported, and a comparison with the principal component analysis disaggregation technique is given.

Indirect Adaptive Control of an Electrohydraulic Servo System Based on Nonlinear Backstepping

This paper studies the real-time position control of an electrohydraulic system using indirect adaptive backstepping. Electrohydraulic systems are known to be highly nonlinear and nondifferentiable. Backstepping is used for being a powerful, nonlinear control strategy and for its ability to ensure an asymptotic stability of the controlled system without canceling useful nonlinearities. On the other hand, hydraulic parameters are prone to variations; it is, therefore, useful to employ an adaptive control strategy in order to update the controller with the parameters variation. In such a case, indirect adaptive control is highly recommended, among other adaptive controller types, as it has the benefit of identifying the real system parameters value. Since not much literature is available for the indirect method as applied to the hydraulic systems, because of its implementation complexity, this paper shows how efficiently this method can handle the parameter estimates.

Development of a whole arm wearable robotic exoskeleton for rehabilitation and to assist upper limb movements

To assist physically disabled people with impaired upper limb function, we have developed a new 7-DOF exoskeleton-type robot named Motion Assistive Robotic-Exoskeleton for Superior Extremity (ETS-MARSE) to ease daily upper limb movements and to provide effective rehabilitation therapy to the superior extremity. The ETS-MARSE comprises a shoulder motion support part, an elbow and forearm motion support part, and a wrist motion support part. It is designed to be worn on the lateral side of the upper limb in order to provide naturalistic movements of the shoulder (vertical and horizontal flexion/extension and internal/external rotation), elbow (flexion/extension), forearm (pronation/supination), and wrist joint (radial/ulnar deviation and flexion/extension). This paper focuses on the modeling, design, development, and control of the ETS-MARSE. Experiments were carried out with healthy male human subjects in whom trajectory tracking in the form of passive rehabilitation exercises (i.e., pre-programmed trajectories recommended by a therapist/clinician) were carried out. Experimental results show that the ETS-MARSE can efficiently perform passive rehabilitation therapy.

Hierarchical Fuzzy Cooperative Control and Path Following for a Team of Mobile Robots

In this paper, an intelligent cooperative control and path-following algorithm is proposed and tested for a group of mobile robots. The core of this algorithm uses a fuzzy model, which mimics human thought to control the robots velocity, movement, and group behavior. The designed fuzzy model employs two behaviors: path following and group cooperation. Hierarchical controllers have also been developed based on fuzzy and proportional integral derivative to instruct the robots to move in a group formation and follow specific paths. As the robots move along individual predetermined paths, the designed algorithm adjusts their velocities so that the group arrives at their target points within the same time duration regardless of the length of each individual path. The fuzzy rules applied to the robots are defined by the kinematics limitation, which is bounded by both linear and angular velocities and the length and curvature of the individual paths. The experimental results of three mobile robots traveling on different paths are presented to show the accuracy of obtaining control and cooperation by using the fuzzy algorithm.

A Decentralized Control of Partitioned Power Networks for Voltage Regulation and Prevention Against Disturbance Propagation

This paper investigates a secondary voltage control based on a graph partitioning method. The method divides the power system into regions to eventually prevent the propagation of disturbances and to minimize the interaction between these regions. The optimized number of regions is found based on the bus voltage sensitivity to disturbances being applied to loads in each region. Then, a number of representative buses are labelled as pilot buses displaying the critical point for voltage control in each region. The control uses decentralized controllers to eliminate voltage violations resulting from load variations and disturbances in the system. The decentralized controllers are implemented by fuzzy logic which is trained via offline simulations; they inject required reactive power into the regions to correct voltage violations. The methodology is applied to the IEEE 118-bus network. The results show the performance and ability of graph partitioning and fuzzy secondary voltage control to regulate the voltage and to avoid propagation of disturbances between regions.

Backstepping-based cooperative and adaptive tracking control design for a group of underactuated AUVs in horizontal plan

In this paper, we investigate new implementable cooperative adaptive backstepping controllers for a group of underactuated autonomous vehicles that are communicating with their local neighbours to track a time-varying virtual leader of which the relative position may only be available to a portion of the team members. At the kinematic cooperative control level of the autonomous underwater vehicle, the virtual cooperative controller is basically designed on a proportional and derivative consensus algorithm presented in Ren (2010), which involves velocity information from local neighbours. In this paper, we propose a new design algorithm based on singular perturbation theory that precludes the use of the neighbours’ velocity information in the cooperative design. At the dynamic cooperative control level, calculation of the partial derivatives of some stabilising functions which in turn will contain velocity information from the local neighbours is required. To facilitate the implementation of the cooperative controllers, we propose a command filter approach technique to avoid analytic differentiation of the virtual cooperative control laws. We show how Lyapunov-based techniques and graph theory can be combined together to yield a robust cooperative controller where the uncertain dynamics of the cooperating vehicles and the constraints on the communication topology which contains a directed spanning tree are explicitly taken into account. Simulation results with a dynamic model of underactuated autonomous underwater vehicles moving on the horizontal plane are presented and discussed.

A Novel Approach for Mobile Robot Navigation with Dynamic Obstacles Avoidance

This paper proposes a new approach for trajectory optimization of a mobile robot in a general dynamic environment. The new method combines the static and dynamic modes of trajectory planning to provide an algorithm that gives fast and optimal solutions for static environments, and generates a new path when an unexpected situation occurs. The particularity of the method is in the representation of the static environment in a judicious way facilitating the path planning and reducing the processing time. Moreover, when an unexpected obstacle blocks the robot trajectory, the method uses the robot sensors to detect the obstacle, finds a best way to circumvent it and then resumes its path toward the desired destination. Experimental results showed the effectiveness of the proposed approach.