In agricultural field mapping missions, a collision risk occurs when the UAVs deviate from their planned trajectories due to the wind or uncertainties in the model, but also in case of intersecting paths of the UAVs, e.g. when the battery level is not sufficient and a UAV needs to change its initially planned path and return to the base unexpectedly.In this paper, three nonlinear model predictive control (NMPC) trajectory tracking strategies for collision avoidance are compared for multi-UAV mapping of an agricultural field: incorporating collision avoidance as a nonlinear constraint, applying it as a penalty cost, and employing a safe flight corridor approach. All the presented strategies consider passing priority allocation of the UAVs involved in the mission, where only a UAV with a lower-level priority handles collision avoidance. Control strategies are compared regarding robustness to external disturbances, such as wind, and model uncertainties through Monte Carlo simulations. The performance is evaluated with respect to the resulting tracking errors, the ability to avoid collision, and the computational time needed to solve the optimal control problem. The objective is to determine, among these three approaches, the one that exhibits the best trade-off between performance and computational burden.

This paper presents a novel approach for UAV battery management of the energy-aware mapping mission planning. The optimization strategy aims to reduce overall flight time by considering necessary battery replacements. Energy constraints are imposed as the capacities of available batteries are limited. The resulting mission plan reduces the unnecessary long flight distances from and to the base station. This strategy also considers the choice of the base location. Potential base locations are fixed and placed at the vertices of the mapping area for easy access. Iterative optimization results in choosing the location with the minimal total mission flight distance. The optimal solution of the proposed approach is compared to its initial solution, where the mapping area is decomposed proportionally to the capacities of batteries planned to be used in the mission. Simulation results for the realistic test case mapping area of the vineyard and olive orchard show that fewer battery replacements are needed and both total flight time and total flight distance are reduced when implementing the proposed optimization strategy. Moreover, mission safety is increased as the number of take-offs and landings, which pose high risk, are reduced.

This paper considers the control of spacecraft's vibration testing system. This test system is used for the qualification of the dynamic behavior of spacecraft under severe launch environment. The vibration testing system shall cover the launcher's vibration frequency band with respect to the spacecraft limitations (notching around the eigen frequencies). Several control strategies were already studied, leading however to inaccurate tracking performance and important oscillations due to the excitation of the vibrational modes of the spacecraft. An additional difficulty results from the large spectral interval tracking problem, generally beginning at 5 Hz, and continuing up to 150 Hz. In this paper, a switching control strategy is developed based on several robust controllers, where the switch between controllers depends on the reference frequency. The performance of this strategy is assessed by means of a model in- the-loop (MIL) architecture introduced for the virtual shaker testing campaign up to 40 Hz, including Monte-Carlo simulations. Moreover, the campaign's security is assured through guaranteed stability margins of the closed-loop system, limiting the testing campaign to a single run vibration testing instead of the current four-stage one, reducing the testing cost.

In this study, a control strategy for lactic acid production process from wheat flour is proposed. First, the process model to be used in the control strategy is chosen after performing an observability analysis of the system. Then, the optimal setpoint that maximizes the lactic acid productivity is determined based on this simplified model. Finally, the regulation of lactic acid concentration to its optimal value is considered. The designed control law uses a state-feedback linearizing controller in an inner loop together with a proportional integral (PI) regulator in an outer loop. An anti-windup mechanism is added in order to improve the control law performances. The efficiency of the proposed control strategy is illustrated and assessed by means of simulation results.

This paper presents a nonlinear predictive control (NMPC) strategy applied to the continuous microalgae cultivation process in a closed photobioreactor. The photo-bioreactor system is programmed to operate in a constant biomass density mode, in order to maintain the culture at the optimal population density and sustain high biomass production levels. This objective is achieved by regulating the biomass density while tracking a reference culture medium feeding profile determined off-line. The proposed NMPC approach is validated in simulation, and performances and benefits for the cell cultivations are compared to those obtained when applying a generic model control (GMC) law.

This paper proposes an off-line procedure which enables the robustification of an initial stabilizing controller for multivariable systems using the convex optimization of a Youla parameter. This robustification must provide stability robustness towards unstructured uncertainties for the nominal system, while guaranteeing stability properties over a specified polytopic domain of uncertainties. Solving this problem leads to verify a Bilinear Matrix Inequality (BMI) for each vertex of the polytopic domain. To overcome the problem faced with BMIs, an alternative tractable sub-optimal solution is proposed, based on the minimization of the complementary sensitivity function permitting to enlarge the stability domain. To illustrate the potential of the developed method, an application to a simplified model of a stirred tank reactor is further examined.