Nowadays, electric vehicles are one of the main topics in the new industrial revolution, called Industry 4.0. The transport and logistic solutions based on E-mobility, such as handling machines, are increasing in factories. Thus, electric forklifts are mostly used because no greenhouse gas is emitted when operating. However, they are usually equipped with lead-acid batteries which present bad performances and long charging time. Therefore, combining high-energy density lithium-ion batteries and high-power density supercapacitors as a hybrid energy storage system results in almost optimal performances and improves battery lifespan. The suggested solution is well suited for forklifts which continuously start, stop, lift up and lower down heavy loads. This paper presents the sizing of a lithium-ion battery/supercapacitor hybrid energy storage system for a forklift vehicle, using the normalized Verein Deutscher Ingenieure (VDI) drive cycle. To evaluate the performance of the lithium-ion battery/supercapacitor hybrid energy storage system, different sizing simulations are carried out. The suggested solution allows us to successfully optimize the system in terms of efficiency, volume and mass, in regard to the battery, supercapacitors technology and the energy management strategy chosen.

Aerial manipulators may replace industrial manipulators for specific tasks involving large workspaces and high dynamics. However, these robots suffer from a lack of accuracy, autonomy, payload capability and a complex regulatory environment. To overcome some of these limitations, we introduce a novel aerial manipulator suspended by a spring to a robotic carrier. A computed torque controller with exteroceptive feedback is used to control the robot, using singular perturbation theory to prove the stability. We carried out various experiments to assess the workspace, accuracy and dynamics of the manipulator.

This article presents the design and implementation of an event-triggered control approach, applied to the leader-following consensus and formation of a group of autonomous micro-aircraft with capabilities of vertical take-off and landing (VTOL-UAVs). The control strategy is based on an inner–outer loop control approach. The inner control law stabilizes the attitude and position of one agent, whereas the outer control follows a virtual leader to achieve position consensus cooperatively through an event-triggered policy. The communication topology uses undirected and connected graphs. With such an event-triggered control, the closed-loop trajectories converge to a compact sphere, centered in the origin of the error space. Furthermore, the minimal inter-sampling time is proven to be below bounded avoiding the Zeno behavior. The formation problem addresses the group of agents to fly in a given shape configuration. The simulation and experimental results highlight the performance of the proposed control strategy.

This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS) based on low-cost MEMS (Micro-Electro-Mechanical Systems) Inertial Measure Unit (IMU) and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance.

In this article, a macro–mini aerial manipulator with elastic suspension is introduced. The mini is an omnidirectional aerial manipulator suspended from the macro by a spring. The macro is a Cartesian robot that moves the anchoring point of the spring. This design combines the advantages of the large workspace of the macrorobot with the high dynamics of aerial vehicles, while reducing energy consumption thanks to gravity compensation. A partitioned control scheme is first implemented to regulate the aerial manipulator and its carrier separately. The redundancy resolution strategy positions the macrorobot to minimize the energy consumption of the aerial manipulator at steady state. Then, a nonlinear model predictive controller replaces the partitioned controller to improve further the efficiency of the combined system, notably by anticipating the slow dynamics of the macrorobot. A sufficient condition for offset-free tracking has been investigated theoretically. Experiments with a cable-driven parallel robot as macro are carried out to assess the added value of the carrier. Both controllers are validated and compared experimentally.