Ramdane Hedjar

Fuzzy Logic Navigation and Obstacle Avoidance by a Mobile Robot in an Unknown Dynamic Environment

Mobile robot navigation has remained an open problem over the last two decades. Mobile robots are required to navigate in unknown and dynamic environments, and in recent years the use of mobile robots in material handling has considerably increased. Usually workers push carts around warehouses and manually handle orders which is not very cost-effective. To this end, a potential method to control a swarm of mobile robots in a warehouse with static and dynamic obstacles is to use the wireless control approach. Further, to be able to control different types of mobile robots in the warehouse, the fuzzy logic control approach has been chosen. Therefore, in this paper, an on-line navigation technique for a wheeled mobile robot (WMR) in an unknown dynamic environment using fuzzy logic techniques is investigated. In this paper, we aim to use the robot in application in a warehouse. Experimental results show the effectiveness of the proposed algorithm.

Predictive control of periodic-review production inventory systems with deteriorating items

In this paper a predictive control strategy is applied to a periodic-review dynamic inventory system with deteriorating items. Given the current inventory level, we determine the optimal production rates to be implemented at the beginning of each of the following periods over the control horizon. The effectiveness of this approach is the use of future information of the inventory target level and the desired production rate, which are available, along the fixed horizon. The deterioration coefficient may be known or unknown and both cases are considered. In the case where it is unknown, the self-tuning predictive control is applied. The proposed control algorithms are illustrated by simulations.

Cascaded Nonlinear Predictive Control of Induction Motor

Two versions of continuous-time feedback nonlinear predictive control laws with a fixed end point prediction and a finite horizon prediction are presented. They are applied in a cascade structure to induction motor that includes both electrical and mechanical dynamics. Both speed and torque/flux tracking objectives are achieved in matched and mismatched parameters case. The rotor flux is estimated by the Kalman filter. The derived nonlinear predictive laws minimize a quadratic performance index of the predicted tracking error. A key feature of the control law is that its implementation does not need to perform an online optimization and asymptotic tracking of smooth reference signal is guaranteed. Simulations show that the proposed controllers are suitable for high dynamic performance applications. A good robustness with respect to parameters variation and load torque disturbance are achieved.

Two cascaded nonlinear predictive controls of induction motor

Two versions of continuous-time feedback nonlinear predictive control laws with a fixed end point prediction and a finite horizon prediction are presented. They are applied in a cascade structure to induction motor. Both speed and torque/flux tracking objectives are achieved in matched and mismatched parameters case. The rotor flux is estimated by the Kalman filter. The derived nonlinear predictive laws minimize a quadratic performance index of the predicted tracking error. Its implementation does not need to perform an on line optimization and asymptotic tracking of smooth reference signal is guaranteed. Simulations show that the proposed controllers are suitable for high dynamic performance applications.

Cascaded nonlinear predictive control of induction motor

A cascaded nonlinear predictive control design is applied to a nonlinear induction machine with both electrical and mechanical dynamics. With full state measurement assumption, both rotor speed and rotor flux amplitude tracking objectives are satisfied. The proposed control law is able to deal with mismatched parameters and load torque disturbance. Simulation results are performed to illustrate the efficiency of the proposed control law.

A Hierarchical Fuzzy Control Design for Indoor Mobile Robot

This paper presents a motion control for an autonomous robot navigation using fuzzy logic motion control and stereo vision based path-planning module. This requires the capability to maneuver in a complex unknown environment. The mobile robot uses intuitive fuzzy rules and is expected to reach a specific target or follow a prespecified trajectory while moving among unforeseen obstacles. The robots mission depends on the choice of the task. In this paper, behavioral-based control architecture is adopted, and each local navigational task is analyzed in terms of primitive behaviors. Our approach is systematic and original in the sense that some of the fuzzy rules are not triggered in face of critical situations for which the stereo vision camera can intervene to unblock the mobile robot.

Real-Time Obstacle Avoidance for a Swarm of Autonomous Mobile Robots

In this paper, we propose a computational trajectory generation algorithm for swarm mobile robots using local information in a dynamic environment. The algorithm plans a reference path based on constrained convex nonlinear optimization which avoids both static and dynamic obstacles. This algorithm is combined with one-step-ahead predictive control for a swarm of mobile robots to track the generated paths and reach the goals without collision. The numerical simulations and experimental results demonstrate the effectiveness of the proposed free-collision path planning algorithm.

Robot localization using extended kalman filter with infrared sensor

In order to use mobile robot for any application, mobile robot should have an accurate pose information. Most of the localization systems are based on the odometry sensors or the map of the environment, Therefore, localization is a major requirement for a mobile robot. The navigating operation in mobile robot usually uses the odometry sensors to estimate its position. These odometry sensors reckoning the number of revolutions that the wheels make while driving and turning. This reading of the wheel is used to estimating the displacement over the ground to give a make of the location of the robot. This way of localization has many problem, such as wheel slippage, surface roughness, and mechanical tolerances. These papers, propose a mobile robot localization system based on the extended kalman filter and infrared sensor to overcome the problems of localization in mobile robot. The experimental result of this paper illustrates the robust and the accuracy of the proposed system.

Model predictive production planning in a three-stock reverse-logistics system with deteriorating items

A model predictive control approach is applied to a closed-loop supply chain where remanufactured items are as-good-as-old. Three stocks are considered, one for newly produced items, one for returned items, and one for remanufactured items. New and remanufactured items target different market segments, as they are subject to different dynamic demands. Further, new and remanufactured items are subject to different deterioration rates. Returned items that cannot be remanufactured for excessive spoilage are discarded. The goal of the firm is to determine the optimal manufacturing rate, the optimal remanufacturing rate, and the optimal disposal rate, under a quadratic cost structure. Using the Trapezoid formula and Taylor expansion, an optimal solution is obtained explicitly when no constraints are imposed on the state and control variables. A numerical example shows the effect of the constraints on the optimal solution.

End point constraints nonlinear predictive control with integral action for induction motor

In this paper the optimal nonlinear predictive control law is presented with application to induction motors in cascade structure. Both speed and torque/flux tracking objectives are achieved in matched and mismatched case. An integral action is introduced in external loop to improve the robustness with respect to load torque variations. The rotor flux is estimated by the Kalman filter. Simulations show the flux-speed tracking performances and the disturbance rejection capabilities of the proposed controller, which is suitable for high dynamic performance applications.