There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Once limited to the military domain, unmanned aerial vehicles are now poised to gain widespread adoption in the commercial sector. One such application is to deploy these aircraft, also known as drones, for last-mile delivery in logistics operations. While significant research efforts are underway to improve the technology required to enable delivery by drone, less attention has been focused on the operational challenges associated with leveraging this technology. This paper provides two mathematical programming models aimed at optimal routing and scheduling of unmanned aircraft, and delivery trucks, in this new paradigm of parcel delivery. In particular, a unique variant of the classical vehicle routing problem is introduced, motivated by a scenario in which an unmanned aerial vehicle works in collaboration with a traditional delivery truck to distribute parcels. We present mixed integer linear programming formulations for two delivery-by-drone problems, along with two simple, yet effective, heuristic solution approaches to solve problems of practical size. Solutions to these problems will facilitate the adoption of unmanned aircraft for last-mile delivery. Such a delivery system is expected to provide faster receipt of customer orders at less cost to the distributor and with reduced environmental impacts. A numerical analysis demonstrates the effectiveness of the heuristics and investigates the tradeoffs between using drones with faster flight speeds versus longer endurance.

The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery

With the rise of soft robotics technology and applications, there have been increasing interests in the development of controllers appropriate for their particular design. Being fundamentally different from traditional rigid robots, there is still not a unified framework for the design, analysis, and control of these high-dimensional robots. This review article attempts to provide an insight into various controllers developed for continuum/soft robots as a guideline for future applications in the soft robotics field. A comprehensive assessment of various control strategies and an insight into the future areas of research in this field are presented.

Control Strategies for Soft Robotic Manipulators: A Survey.

In this paper we are concerned with global optimization, which can be defined as the problem of finding points on a bounded subset of Rn in which some real valued functionf assumes its optimal (i.e. maximal or minimal) value. We present a stochastic approach which is based on the simulated annealing algorithm. The approach closely follows the formulation of the simulated annealing algorithm as originally given for discrete optimization problems. The mathematic formulation is extended to continuous optimization problems and we prove asymptotic convergence to the set of global optima. Furthermore, we discuss an implementation of the algorithm and compare its performance with other well known algorithms. The performance evaluation is carried out for a standard set of test functions from the literature. Keywords: global optimization, continuous variables, simulated annealing.

Global optimization and simulated annealing

Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges

In this paper, autonomous control problem of a class of bionic continuum robots named “Compact Bionic Handling Arm” (CBHA) is addressed. These robots can reproduce biological behaviors of trunks, tentacles, or snakes. The modeling problem associated with continuum robots includes nonlinearities, structured and unstructured uncertainties, and the hyperredundancy. In addition to these problems, the CBHA comprises the hysteresis behavior of its actuators and a memory phenomenon related to its structure made of polyamide materials. These undesirable effects make it difficult to design a control system based on quantitative models of the CBHA. Thus, two subcontrollers are proposed in this paper. One, encapsulated in the other, and both implemented in real time allow controlling of the CBHA's end-effector position. The first subcontroller controls the CBHA's kinematics based on a distal supervised learning scheme. The second subcontroller controls the CBHA's kinetics based on an adaptive neural control. These subcontrollers allow a better assessment of the stability of the control architecture while ensuring the convergence of Cartesian errors. The obtained experimental results using a CBHA robot show an accurate tracking of the CBHA's end-effector position.

Adaptive Neural Network Control of a Compact Bionic Handling Arm

Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes: An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control Dedicated chapters for advanced topics such as multibody dynamics and micro-electromechanical systems, vehicle mechatronic systems, robot kinematics and dynamics, space robotics and intelligent transportation systems Detailed discussion of cooperative environments and reconfigurable systems Intelligent Mechatronic Systems provides control, electrical and mechanical engineers and researchers in industrial automation with a means to design practical, functional and safe intelligent systems.

Intelligent Mechatronic Systems: Modeling, Control and Diagnosis

This paper deals with the generation of fault indicators and residual thresholds in the presence of parameter uncertainties by using a bond graph representation in linear fractional transformation (LFT) form. The residuals' sensitivity analysis, which is based on the fault detectability indexes, is used for residuals evaluation. The developed algorithms are applied on an electromechanical test bench system for on-line fault detection and isolation. Simulation and experimental tests show the influence of dead zone magnitude and variations of system parameters on the residuals.

Robust Fault Diagnosis by Using Bond Graph Approach

This article presents a modeling methodology and experimental validation for soft manipulators to obtain forward kinematic model (FKM) and inverse kinematic model (IKM) under quasi-static conditions (in the literature, these manipulators are usually classified as continuum robots. However, their main characteristic of interest in this article is that they create motion by deformation, as opposed to the classical use of articulations). It offers a way to obtain the kinematic characteristics of this type of soft robots that is suitable for offline path planning and position control. The modeling methodology presented relies on continuum mechanics, which does not provide analytic solutions in the general case. Our approach proposes a real-time numerical integration strategy based on finite element method with a numerical optimization based on Lagrange multipliers to obtain FKM and IKM. To reduce the dimension of the problem, at each step, a projection of the model to the constraint space (gathering actuators, sensors, and end-effector) is performed to obtain the smallest number possible of mathematical equations to be solved. This methodology is applied to obtain the kinematics of two different manipulators with complex structural geometry. An experimental comparison is also performed in one of the robots, between two other geometric approaches and the approach that is showcased in this article. A closed-loop controller based on a state estimator is proposed. The controller is experimentally validated and its robustness is evaluated using Lypunov stability method.

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Rochdi Merzouki

Papers

Adaptive Neural Network Control of a Compact Bionic Handling Arm

Intelligent Mechatronic Systems: Modeling, Control and Diagnosis

Robust Fault Diagnosis by Using Bond Graph Approach

Finite Element Method-Based Kinematics and Closed-Loop Control of Soft, Continuum Manipulators.

Backlash phenomenon observation and identification in electromechanical system