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The purpose of this paper is to quantify the impact of the constraints of the power take-off system (PTO) on the power extraction of a point absorber wave energy converter (WEC). Such constraints include power, torque and maximum stroke limitations. Two different concepts, unidirectional and bidirectional point absorbers, are analysed, which both are relevant for practical applications in the wave energy industry.

The two different cases of unidirectional and bidirectional point absorbers are analysed and directly compared. Moreover, a simplified control strategy is considered for the point absorber, which is based on a constant torque reference. The WEC performance is first evaluated in selected sea states and then the analysis is extended to assess the impact of the different solutions on the expected yearly wave energy production of the point absorber, when deployed at a specific location. The European Marine Energy Center (EMEC) is selected as the target site for the analysis.

The analysis was performed in selected sea states and then it was extended to all the sea conditions occurring at the EMEC test site. The comparison between unidirectional and bidirectional operated devices suggested a clear superiority of the latter, ensuring similar power extraction at the expense of a halved required torque by the PTO. Moreover, a selective control strategy was implemented, and the results showed an increase in yearly energy production for the bidirectional device.

The study proved the importance of including the actual PTO constraints in the preliminary power assessment in order to avoid unrealistic overestimation of the expected power performance.

The paper quantifies the power performance obtained with the application of such control strategy considering both unidirectional and bidirectional point absorbers. This analysis and comparison is extremely relevant since both unidirectional and bidirectional devices are reaching the market.

The purpose of this paper is to analyze the impact of the torque, power, jerk and energy consumed constraints on the generation of minimum time collision‐free trajectories for industrial robots in a complex environment.

An algorithm is presented in which the trajectory is generated under real working constraints (specifically torque, power, jerk and energy consumed). It also takes into account the presence of obstacles (to avoid collisions) and the dynamics of the robotic system. The method solves an optimization problem to find the minimum time trajectory to perform the tasks the robot should do.

Important conclusions have been reached when solving the trajectory planning problem related to the value of the torque, power, jerk and energy consumed and the relationship between them, therefore enabling the user to choose the most efficient way of working depending on which parameter he is most interested in optimizing. From the examples solved the authors have found the relationship between the maximum and minimum values of the parameters studied.

This new approach tries to model the real behaviour of the actuators in order to be able to upgrade the trajectory quality, so a lot of work has to be done in this field.

The algorithm solves the trajectory planning problem for any industrial robot and the real characteristics of the actuators are taken into account, which is essential to improve the performance of it.

This new tool enables the performance of the robot to be improved by combining adequately the values of the mentioned parameters (torque, power, jerk and consumed energy).

WE define as an open tube a thin‐walled structure, the cross‐section of which does not include any closed circuit. This property is common, for example, to the curved channel, the interspar wing cut‐out and the panel stiffened with Z‐sections, illustrated in FIG. 1 (a, b, c). But the interspar cut‐out with nose cell (FIG. 1d) is not an open tube in the present definition. All structures discussed in this paper are assumed to be cylindrical and to have a constant cross‐section. It is relatively simple to extend the results to conical taper and longitudinally varying thickness, but this would be beyond the scope and space of the present analysis (see, however, ref. 5).

The purpose of this paper is to present a dual-mode online optimization method (OOM) for trajectory tracking of the redundant manipulators. This method could be used to resolve the problem of the kinematics redundancy effectively when the manipulator moves in a limited space or its movements go through a singular point.

In the proposed method, the physical limits of the manipulator in the torque level is considered as inequality constraints for the optimal scheme. Besides, a dual-mode optimal scheme is developed to yield a feasible input in each control period during the path tracking task of the manipulator, especially when it moves under the limited space or around the singular point. Then, the scheme is formulated as a quadratic programming; the computationally efficient quadratic programming solver based on interior method is formulated to solve the kinematic redundancy problem.

The traditional pseudo inverse method (PIM) for the kinematic resolution to the redundant manipulator has some limitations, such as slow computation speed, unable to take joint physical limits into consideration, etc. Relatively, the OOM could be used to conquer the deficits of the PIM method. Combining with the dual-mode optimal scheme and considering the physical constraints in the torque level, the online method proposed in this paper is more robust and efficient than the existing method.

In this paper, dual-mode OOM is first proposed for the resolution of the kinematics redundancy problem. Specific design of its model and the discussion of its performance are also presented in this paper.

The purpose of this paper is to propose a precise time-optimal path tracking approach for robots under kinematic and dynamic constraints to improve the work efficiency of robots and guarantee tracking accuracy.

In the proposed approach, the robot path is expressed by a scalar path coordinate and discretized into N points. The motion between two neighbouring points is assumed to be uniformly accelerated motion, so the time-optimal trajectory that satisfies constraints is obtained by using equations of uniformly accelerated motion instead of numerical integration. To improve dynamic model accuracy, the Coulomb and viscous friction are taken into account (while most publications neglect these effects). Furthermore, an iterative learning algorithm is designed to correct model-plant mismatch by adding an iterative compensation item into the dynamic model at each discrete point before trajectory planning.

An experiment shows that compared with the sequential convex log barrier method, the proposed numerical integration-like (NI-like) approach has less computation time and a smoother planning trajectory. Compared with the experimental results before iteration, the torque deviation, tracking error and trajectory execution time are reduced after 10 iterations.

As the proposed approach not only yields a time-optimal solution but also improves tracking performance, this approach can be used for any repetitive robot tasks that require more rapidity and less tracking error, such as assembly.

In this work, a method to design a slotless permanent magnet machine (SPMM) based on the joint use of an analytical model and deterministic global optimization algorithms is addressed. The purpose of this study is to propose to include torque ripples as an extra constraint in the optimization phase involving de facto the study of a semi-infinite optimization problem.

Based on the use of a well-known analytical model describing the electromagnetic behavior of an SPMM, this analytical model has been supplemented by the calculus of the dynamic torque and its ripples to carry out a more accurate optimized sizing method of such an electromechanical converter. As a consequence, the calculated torque depends on a continuous variable, namely, the rotor angular position, resulting in the definition of a semi-infinite optimization problem. The way to solve this kind of semi-infinite problem by discretizing the rotor angular position by using a deterministic global optimization solver, that is to say COUENNE, via the AMPL modeling language is addressed.

In this study, the proposed approach is validated on some numerical tests based on the minimization of the magnet volume. Efficient global optimal solutions with torque ripples about 5% (instead of 30%) can be so obtained.

The analytical model does not use results from the solution of two-dimensional field equations. A strong assumption is put forward to approximate the distribution of the magnetic flux density in the air gap of the SPMM.

The problem to design an SPMM can be efficiently formulated as a semi-infinite global optimization problem. This kind of optimization problems are hard to solve because they involve an infinity of constraints (coming from a constraint on the torque ripple). The authors show in this paper that by using analytical models, a discretization method and a deterministic global optimization code COUENNE, this problem is efficiently tackled. Some numerical results show that the deterministic global solution of the design can be reached even if the step of discretization is small.

The purpose of this paper is to apply an Ant colony optimization approach for the solution of the topological design of interior permanent magnet (IPM) machines.

The IPM motor design domain is discretized into a suitable equivalent graph representation and an Ant System (AS) algorithm is employed to achieve an efficient distribution of materials into this graph.

The single-objective problems associated with the maximization of the torque and with the maximization of the shape smoothness of the IPM are investigated. The rotor of the device is discretized into a 9×18 grid in both cases, and three different materials are considered: air, iron and permanent magnet.

The graph representation used enables the solution of topological design problems with an arbitrary number of materials, which is relevant for 2 and 3D problems.

From the numerical experiments, the AS algorithm was able to achieve reasonable shapes and torque values for both design problems. The results show the relevance of the mechanism for multi-domain topology optimization of electromagnetic devices.

This paper aims to study using a mobile manipulator with a collaborative robotic arm component to manipulate objects beyond the robot’s maximum payload.

This paper proposes a single-short probabilistic roadmap-based method to plan and optimize manipulation motion with environment support. The method uses an expanded object mesh model to examine contact and randomly explores object motion while keeping contact and securing affordable grasping force. It generates robotic motion trajectories after obtaining object motion using an optimization-based algorithm. With the proposed method’s help, the authors plan contact-rich manipulation without particularly analyzing an object’s contact modes and their transitions. The planner and optimizer determine them automatically.

The authors conducted experiments and analyses using simulations and real-world executions to examine the method’s performance. The method successfully found manipulation motion that met contact, force and kinematic constraints. It allowed a mobile manipulator to move heavy objects while leveraging supporting forces from environmental obstacles.

This paper presents an automatic approach for solving contact-rich heavy object manipulation problems. Unlike previous methods, the new approach does not need to explicitly analyze contact states and build contact transition graphs, thus providing a new view for robotic grasp-less manipulation, nonprehensile manipulation, manipulation with contact, etc.

In this paper the problem of the dynamic optimal time‐energy Off‐Line programming of an autonomous mobile robot in a crowded environment is considered. First, kinematic model and planning are presented. Then a dynamic model based on Euler‐Lagrange formalism is developed and a mobility estimation function of the robot is considered. This dynamic estimation of the robot mobility takes into account of the velocity and the orientation of the robot. Then the scene structuration and a path finder algorithm are developed. After, the optimal dynamic off‐line programming is formulated as a nonlinear programming problem under nonlinear equality and inequality constraints. The Discrete Augmented Lagrangian (DAL) is used to obtain the optimal trajectograhy. We develop an extended DAL to DALAP, DALAdaptive Penalty. RoboSim 1.0 simulator is developed to perform kinematic and DALAP based algorithms on a large class of mobile robots optimal time‐energy off‐line programming. A comparative study with kinematic planning is considered. It is shown that the performance of the dynamic optimal time‐energy control and off‐line programming is much better than kinematic and heuristic based schemes. This strategy of trajectory planning was implemented on the case study of the SARA mobile robot model.

Responsible for lift generation, the helicopter rotor is an essential component to protect against ice accretion. As rotorcraft present a smaller wing cross-section and a lower available onboard power compared to aircraft, electro-thermal heating pads are favored as they conform to the blades’ slender profile and limited volume. Their optimization is carried out here taking into account, for the first time, the highly three-dimensional (3D) nature of the flow and ice accretion, in contrast to the current state-of-the-art that is limited to two-dimensional (2D) airfoils.

Conjugate heat transfer simulation results are provided by the truly 3D finite element Navier–Stokes analysis package-ICE code, embedded in a proprietary rotorcraft simulation toolkit, with reduced-order modeling providing a time-efficient evaluation of the objective and constraint functions at every iteration. The proposed methodology optimizes heating pads extent and power usage and is versatile enough to address in a computationally efficient manner a wide variety of optimization formulations.

Low-error reduced-order modeling strategies are introduced to make the tackling of complex 3D geometries feasible in todays’ computers, with the developed framework applied to four problem formulations, demonstrating marked reductions to power consumption along with improved aerodynamics.

The present paper proposes a 3D framework for the optimization of electro-thermal rotorcraft ice protection systems, in hover and forward flight. The current state-of-the-art is limited to 2D airfoils.