This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations within a closed-loop reverse logistics network with machines subject to random failures and repairs. While consumers traditionally dispose of products at the end of their life cycle, recovery of the used products may be economically more attractive than disposal, while remanufacturing of the products also pursues sustainable development goals. Three types of inventories are involved in this network. The manufactured and remanufactured items are stored in the first and second inventories. The returned products are collected in the third inventory and then remanufactured or disposed of. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the sum of the holding and backlog costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The optimality conditions are developed using the optimal control theory based on stochastic dynamic programming. A computational algorithm, based on numerical methods, is used for solving the optimal control problem. Finally, a numerical example and a sensitivity analysis are presented to illustrate the usefulness of the proposed approach. The structure of the optimal control policy is discussed depending on the value of costs and parameters and extensions to more complex reverse logistics networks are discussed.

SUMMARY: 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.

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

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.

Electrohydraulic servo systems (EHSS) are used for several engineering applications, and in particular, for efficient handling of heavy loads. proportional-integral-differential (PID) control is used extensively to control EHSS, but the closed-loop performance is limited using this approach, due to the nonlinear dynamics that characterize these systems. Recent studies have shown that feedback linearization is a viable control design technique that addresses the nonlinear dynamics of EHSS; however, it is important to establish the robustness of this method, given that hydraulic system parameters can vary significantly during operation. In this study, we focus on supply pressure variations in a rotational electrohydraulic drive. The supply pressure appears in a square-root term in the system model, and thus, standard adaptive techniques that require uncertain parameters to appear linearly in the system equations, cannot be used. A Lyapunov approach is used to derive an enhanced feedback-linearization-based control law that accounts for supply pressure changes. Simulation results indicate that standard feedback-linearization based control is robust to EHSS parameter variations, providing significant improvement over PID control, and that the performance can be further improved using the proposed control law.