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Abstract This paper proposes a novel neural output feedback trajectory tracking controller for robotic exoskeletons. The controller is developed by defining auxiliary dynamics, and utilizing an adaptive feedforward neural network (NN) term to compensate for unknown nonlinear dynamics of the system. The proposed approach only needs position information in both the controller and adaptation rule of the NN weight matrix. In addition, the controller provides an a priori bounded control command. The performance of the controller is validated through simulations and experiments conducted on a lower-limb robotic exoskeleton. It is shown through experiments that the NN term of the controller has assist-as-needed property, such that its contribution in the controller output decreases when the user can follow the desired trajectory in a rehabilitation task. [ABSTRACT FROM AUTHOR]

Highlights • A microgrid model with non-convex combined heat and power systems is considered. • Microgrid variables are optimally scheduled by a simultaneous-distributed algorithm. • The proposed method shows a fast convergence for a test system with 408 variables. • Cost saving is larger than that of a particle swarm optimization approach. Abstract This paper proposes a distributed energy management system-based algorithm to solve the optimal schedule of multiple combined heat and power systems in which exponential efficiencies of fuel cells are considered. To deal with the variation in fuel cell efficiencies, the proposed algorithm utilizes the alternating direction method of multipliers, consensus theory, and quadratic programming to solve the optimization problem with constant efficiencies. Then, the efficiency matching is checked iteratively to verify the obtained result. The optimization algorithm is constructed in a whole-day distributed form, such that all time slot variables can be solved simultaneously in a distributed way. With the help of this simultaneous solution method, operation of hot tanks and combined heat and power systems can be scheduled globally. The proposed algorithm is tested successfully with a test system having 4 combined heat and power systems, showing fast convergence in numerous simulations. [ABSTRACT FROM AUTHOR]

Abstract: In this paper a new control methodology for underactuated mechanical systems is proposed. The basic idea of this method is to combine passive velocity field control with decoupling vector field. In order that the underactuated mechanical systems can be stabilized at the desired position after settling on the desired velocity vector field, novel control strategies are proposed. Proposed control strategies are applied to the underactuated planar three-link manipulator and underactuated planar body. Simulations demonstrate the usefulness and effectiveness of the proposed control methodology. [Copyright &y& Elsevier]

Abstract: In this paper the attitude control problem of planar space robot is addressed and new feedback control scheme is proposed. Since control laws are synthesized via theory of geometric phase, the proposed control laws contain smooth functions of states and time. The usefulness and validity of this control scheme can be demonstrated by hardware experiments. In experiments to simulate the space environment prototype of the planar space robot is floated by air on the horizontal plane. Experimental results show that the proposed smooth time-varying control laws stabilize the attitude of the planar space robot sufficiently. [Copyright &y& Elsevier]

Abstract: In this paper we consider the application of a new formulation of passive velocity field control (PVFC) to the control problem of a class of underactuated mechanical systems (UAMS). In our previous report synthesizing the desired velocity vector fields for PVFC by the decoupling vector fields, we were able to prove that control torques may be successfully obtained and the solvability of the synthesizing problem of PVFC for the UAMS may be guaranteed. We newly develop this control design methodology and propose an explicit feedback solution to the control problems of the UAMS, such as snakeboard, underactuated 3D rigid bodies. Several simulations show the validity of the proposed control methodology. [Copyright &y& Elsevier]

Abstract: This paper presents a new scheduling method for manufacturing system based on the Timed Petri Net model and a reactive fast graph search algorithm. The following two typical problems are addressed in this paper. (1) Minimization of the maximum completion time. (2) Minimization of the total tardiness. As for the problem (1), a new search algorithm which combines the RTA∗ and a rule-based supervisor is proposed. As for problem (2), the original Petri Net model is converted to its reverse model and the algorithm developed for the problem (1) is applied, regarding the due date as the starting time in the reverse model. Some numerical experiments are carried out to demonstrate usefulness of our algorithm. [Copyright &y& Elsevier]

In this paper, we present a control scheme for robotic exoskeletons to gain the desired transparency for a wide range of tasks, which leads to the provision of sufficient support to the wearer in different situations. The main goal of the study was to evaluate the performance of adaptive neural networkbased controllers in gaining transparency for powerassist robots. As these devices experience a large dynamic change during handling different tasks/loads, we studied whether neural networks (NNs) can promptly learn the dynamics and provide sufficiently smooth commands to achieve the desired transparency. Our evaluations were performed through experiments conducted on an upperlimb robotic exoskeleton with unknown dynamics handling external loads. We tested a commonly used structure of NNs with different layers of adjustable weights and numbers of neurons. We also tested the smoothness of the system response and concluded that to gain natural and comfortable feeling the desired transparency needs to be selected in accordance with the task. • An adaptive controller is proposed for power augmentation through assistive robots. • The tracking accuracy has been evaluated for different networks. • The approach does not need the dynamic model of the robot and the weight of the load. • To make users feel comfortable, the smoothness of the control approach is evaluated. [ABSTRACT FROM AUTHOR]