Guaranteed Cost Attitude Tracking Control for Uncertain Quadrotor Unmanned Aerial Vehicle Under Safety Constraints

In this paper,guaranteed cost attitude tracking con-trol for uncertain quadrotor unmanned aerial vehicle(QUAV)under safety constraints is studied.First,an augmented system is constructed by the tracking error system and reference system.This transformation aims to convert the tracking control prob-lem into a stabilization control problem.Then,control barrier function and disturbance attenuation function are designed to characterize the violations of safety constraints and tolerance of uncertain disturbances,and they are incorporated into the reward function as penalty items.Based on the modified reward function,the problem is simplified as the optimal regulation problem of the nominal augmented system,and a new Hamilton-Jacobi-Bellman equation is developed.Finally,critic-only rein-forcement learning algorithm with a concurrent learning tech-nique is employed to solve the Hamilton-Jacobi-Bellman equa-tion and obtain the optimal controller.The proposed algorithm can not only ensure the reward function within an upper bound in the presence of uncertain disturbances,but also enforce safety constraints.The performance of the algorithm is evaluated by the numerical simulation.

UAVs cooperative task assignment and trajectory optimization with safety and time constraints

This paper proposes new methods and strategies for Multi-UAVs cooperative attacks with safety and time constraints in a complex environment.Delaunay triangle is designed to construct a map of the complex flight environment for aerial vehicles.Delaunay-Map,Safe Flight Corridor(SFC),and Relative Safe Flight Corridor(RSFC)are applied to ensure each UAV flight trajectory's safety.By using such techniques,it is possible to avoid the collision with obstacles and collision between UAVs.Bezier-curve is further developed to ensure that multi-UAVs can simultaneously reach the target at the specified time,and the trajectory is within the flight corridor.The trajectory tracking controller is also designed based on model predictive control to track the planned trajectory accurately.The simulation and experiment results are presented to verifying developed strategies of Multi-UAV cooperative attacks.

Robust Assignment of Airport Gates with Operational Safety Constraints

This paper reviews existing approaches to the airport gate assignment problem （AGAP） and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize the dispersion of gate idle time periods （to get robust optimization） while ensuring appropriate matching between the size of each aircraft and its assigned gate type and avoiding the potential hazard caused by gate apron operational conflict. Genetic algorithm is adopted to solve the problem, An illustrative example is given to show the effectiveness and efficiency of the algorithm. The algorithm performance is further demonstrated using data of a terminal from Beijing Capital International Airport （PEK）.

Intelligent Power Grid Load Transferring Based on Safe Action-Correction Reinforcement Learning

When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changingthe states of tie-switches and load demands. Computation speed is one of the major performance indicators inpower grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault powergrids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient.The tedious training process of the reinforcement learning model can be conducted offline, so the model showssatisfactory performance in real-time operation, indicating that it is suitable for fast load transfer. Consideringthat the reinforcement learning model performs poorly in satisfying safety constraints, a safe action-correctionframework is proposed to modify the learning model. In the framework, the action of load shedding is correctedaccording to sensitivity analysis results under a small discrete increment so as to match the constraints of line flowlimits. The results of case studies indicate that the proposed method is practical for fast and safe power grid loadtransfer.

Optimal‑Control‑Based Eco‑Driving Solution for Connected Battery Electric Vehicle on a Signalized Route

Speed advisory systems have been used for connected vehicles to optimize energy consumption.However,for their practical utilization,presence of preceding vehicles and signals must be taken into account.Moreover,for Battery Electric Vehicles(BEVs),factors that deteriorate battery’s life cycle and discharging time must also be considered.This paper proposes an eco-driving control for connected BEV with traffic signals and other safety constraints.Traffic signals are considered as interior point constraints,while inter-vehicle distance with preceding vehicles,vehicle speed and battery charging/discharging limits,are considered as state safety constraints.Backward-forward simulator based Speed Guidance Model is applied to follow the optimized velocity under powertrain safety limitations.Effectiveness of the proposed methodology is tested on a 5.3-km route in Islamabad,Pakistan.Real traffic data using Simulation of Urban Mobility under different driving scenarios is considered.Using the proposed method,around 21% energy can be saved compared to the preceding vehicles that followed their random velocities under the same traffic and route conditions.This means the EV controlled by the proposed method can have longer driving range.Furthermore,the host BEV has crossed signals during their green time without collision with preceding vehicles.Low charging rates and terminal Depth of Discharge indicate less number of charging cycles,thus proving the usefulness of the proposed solution as battery’s lifesaving strategy.

Towards automated validation of charted soundings:Existing tests and limitations

The nautical chart is one of the fundamental tools in navigation used by mariners to plan and safely execute voyages.Its compilation follows strict cartographic constraints with the most prominent being that of the safety.Thereby,the cartographer is called to make the selection of the bathymetric information for portrayal on charts in a way that,at any location,the expected water depth is not deeper than the source information.To validate the shoal-biased pattern of selection two standard tests are used,i.e.the triangle and edge tests.To date,some efforts have been made towards the automation of the triangle test,but the edge test has been largely ignored.In the context of research on a fully automated solution for the compilation of charts at different scales from the source information,this paper presents an algorithmic implementation of the two tests for the validation of selected soundings.Through a case study with real-world data,it presents the improved performance of the implementation near and within depth curves and coastlines and points out the importance of the edge test in the validation process.It also presents the,by definition,intrinsic limitation of the two tests as part of a fully automated solution and discusses the need for a new test that will complement or supersede the existing ones.