Attainable Moment Set Research Articles

Four-Dimensional Generalized AMS Optimization Considering Critical Engine Inoperative for an eVTOL

In this paper, we present a method to optimize the attainable moment set (AMS) to increase the control authority for electrical vertical take-off and landing vehicles (eVTOLs). As opposed to 3D AMSs for conventional airplanes, the hover control of eVTOLs requires vertical thrust produced by the powered lift system in addition to three moments. The limits of the moments and vertical thrust are coupled due to input saturation, and, as a result, the concept of the traditional AMS is extended to the 4D generalized moment set to account for this coupling effect. Given a required moment set (RMS) derived from system requirements, the optimization is formulated as a 4D convex polytope coverage problem, i.e., the AMS coverage over the RMS, such that the system’s available control authority is maximized to fulfill the prescribed requirements. The optimization accounts for not only nominal flight, but also for one critical engine inoperative situation. To test the method, it is applied to an eVTOL with eight rotors to optimize for the rotors’ orientation with respect to the body axis. The results indicate highly improved coverage of the RMS for both failure-free and one-engine-inoperative situations. Closed-loop simulation tests are performed for both optimal and non-optimal configurations to further validate the results.

Design of Pseudo-Command Restricted Controller for Tailless Unmanned Aerial Vehicles Based on Attainable Moment Set

This work investigates the pseudo-command restricted problem for tailless unmanned aerial vehicles with snake-shaped maneuver flight missions. The main challenge of designing such a pseudo-command restricted controller lies in the fact that the necessity of control allocation means it will be difficult to provide a precise envelope of pseudo-command to the flight controller; designing a compensation system to deal with insufficient capabilities beyond this envelope is another challenge. The envelope of pseudo-command can be expressed by attainable moment sets, which leave some open problems, such as how to obtain the attainable moment sets online and how to reduce the computational complexity of the algorithm, as well as how to ensure independent control allocation and the convexity of attainable moments sets. In this article, an innovative algorithm is proposed for the calculation of attainable moment sets, which can be implemented by fitting wind tunnel data into a function to solve the problems presented above. Furthermore, the algorithm is independent of control allocation and can be obtained online. Moreover, based on the above attainable moment sets algorithm, a flight performance assurance system is designed, which not only guarantees that the command is constrained within the envelope so that its behavior is more predictable, but also supports adaptive compensation for the pseudo-command restricted controller. Finally, the effectiveness of the AMS algorithm and the advantages of the pseudo-command restricted control system are validated through two sets of independent simulations.

Multirotor Unmanned Aerial Vehicle Configuration Optimization Approach for Development of Actuator Fault-Tolerant Structure

Presently, multirotor unmanned aerial vehicles (UAV) are utilized in numerous applications. Their design governs the system’s controllability and operation performance by influencing the achievable forces and moments produced. However, unexpected causalities, such as actuator failure, adversely affect their controllability, which raises safety concerns about their service. On the other hand, their design flexibility allows further design optimization for various performance requirements, including actuator failure tolerance. Thus, this study proposed an optimization framework that can be employed to design a novel actuator fault-tolerant multirotor UAV configuration. The approach used an attainable moment set (AMS) to evaluate the achievable moment from a multirotor configuration; similarly, standard deviation geometries (SDG) were employed to define performance requirements. Therefore, given a UAV configuration, actuator fault situation, and SDG derived from the designed mission requirement, the suggested optimization framework maximizes the scaling factor of SDG and fits it into the AMS by adjusting the design parameters up to a sufficient margin. The framework is implemented to optimize selected parameters of the Hexacopter-type of parcel delivery multirotor UAV developed by the PNU drone, and a simulation was conducted. The result showed that the optimized configuration of the UAV achieved actuator fault tolerance and operation-performing capability in the presence of a failed actuator.

A trim problem formulation for maximum control authority using the Attainable Moment Set geometry

This paper presents a generic trim problem formulation, in the form of a constrained optimization problem, which employs forces and moments due to the aircraft control surfaces as decision variables. The geometry of the Attainable Moment Set (AMS), i.e. the set of all control forces and moments attainable by the control surfaces, is used to define linear equality and inequality constraints for the control forces decision variables. Trim control forces and moments are mapped to control surface deflections at every solver iteration through a linear programming formulation of the direct Control Allocation algorithm. The methodology is applied to an innovative box-wing aircraft configuration with redundant control surfaces, which can partially decouple lift and pitch control, and allow direct lift control. Novel trim applications are presented to maximize control authority about the lift and pitch axes, and a “balanced” control authority. The latter can be intended as equivalent to the classic concept of minimum control effort. Control authority is defined on the basis of control forces and moments, and interpreted geometrically as a distance within the AMS. Results show that the method is able to capitalize on the angle of attack or the throttle setting to obtain the control surfaces deflections which maximize control authority in the assigned direction. More conventional trim applications for minimum total drag and for assigned angle of elevation are also explored.

Attainable Moment Set Optimization to Support Configuration Design: A Required Moment Set Based Approach

In this paper, we discuss an attainable moment set (AMS) optimization methodology considering a system’s required moment set (RMS). The AMS describes the achievable moments from a system, given its input limits. An RMS, like an AMS, is a convex set in the moment space, describing the required moments for a system to meet the designed mission profile and disturbance rejection requirements. Given the configuration of a system, its mission requirements, and the derived RMS, the proposed optimization maximizes coverage of the AMS onto the RMS, thus ensuring the system possesses the guaranteed controllability to fulfill its required missions from a design level. To achieve this goal, the variables to optimize are chosen as effector settings, such as the installation position and angle of propellers and control surfaces, which effectively change the AMS without a vast impact on major design parameters, such as mass and moment of inertia. Since the optimization includes massive geometry operations of rays intersecting polyhedron, an efficient intersection solver is proposed to speed up the optimization process. The described method is applied to an electric-vertical-take-of-landing vehicle (eVTOL) with eight hover propellers, which delivers a highly improved coverage of the RMS compared to its initial design.

A Modified Direct Allocation Algorithm with Application to Redundant Actuators

Control allocation considers the problem of controlling instruction distribution for control systems with multiple and redundant actuators. This paper focuses on the direct allocation method, making the time requirement of the algorithm analogous compared with modified pseudoinverse redistribution methods, linear programming methods solved by simplex method, and sub-gradient optimization method. To reduce off-line computations of constructing the attainable moment set of actuators, a new approach based on the null space of the control effectiveness matrix is proposed, which is superior when the number of actuators is less than 10 compared with traditional method. To decrease on-line computations, an improvement method of searching the facet that is aligned with the desired moment is presented, shortening the search time by checking only the facets that lie around the desired moment. To find such facets, the vertices of the attainable moment set are normalized and saved during off-line computations. Simulation results show that at least 32.22% of off-line computation time would be saved using null space-based construction when the number of actuators is less than 10. In on-line computations, the modified method performs superiorly compared with the three aforementioned methods. Furthermore, it may solve the problem of control allocation efficiently when a remarkable large number of redundant actuators are configured.

Control allocation for a V/STOL aircraft based on robust fuzzy control

This study addresses the design of an output-feedback H-infinity and fuzzy mixed controller for an advanced vertical and/or short take-off and landing aircraft that exhibits satisfactory global stability criteria. A fuzzy logic based optimization approach is employed to solve autonomously the constrained control allocation problem by suitably adjusting the components of the output vector and finding a proper vector in the attainable moment set. Simulations show that the designed fuzzy controller is better suited to resist external disturbances, and is robust against parameter perturbations.

Aeroservoelastic model based active control for large civil aircraft

A modeling and control approach for an advanced configured large civil aircraft with aeroservoelasticity via the LQG method and control allocation is presented. Mathematical models and implementation issues for the multi-input/multi-output (MIMO) aeroservoelastic system simulation developed for a flexible wing with multi control surfaces are described. A fuzzy logic based optimization approach is employed to solve the constrained control allocation problem via intelligently adjusting the components of output vector and find a proper vector in the attainable moment set (AMS) autonomously. The basic idea is to minimize the L2 norm of error between the desired moment and achievable moment using the designing freedom provided by redundantly allocated actuators and control surfaces. Considering the constraints of control surfaces, in order to obtain acceptable performance of aircraft such as stability and maneuverability, the fuzzy weights are updated by the learning algorithm, which makes the closed-loop system self-adaptation. Finally, an application example of flight control designing for the advanced civil aircraft is discussed as a demonstration. The studies we have performed showed that the advanced configured large civil aircraft has good performance with the proper designed control law designed via the proposed approach. The gust alleviation and flutter suppression are applied with the synergetic effects of elevator, ailerons, equivalent rudders and flaps. The results show good closed loop performance and meet the requirement of constraint of control surfaces.

Method for Determination of Nonlinear Attainable Moment Sets

A method for generating attainable moment sets for left-right pairs of nonlinear control effectors on aircraft is presented. It is shown that the determination of the attainable moment set boundary can be posed as a constrained, nonlinear optimization problem. The first-order necessary conditions for a point to be on the boundary are simply the Kuhn-Tucker first-order necessary conditions. An algorithm is given where the Kuhn-Tucker points for a given point in the pitch-roll plane are constructed for each control effector configuration that forms a candidate boundary. The Kuhn-Tucker points are then checked for feasibility, and the points on the boundary are those that produce extremal values of the objective function. The nonlinear attainable moment set boundary is used to determine feasibility of moment commands generated by the flight control system. Infeasible commands are clipped to the boundary of the attainable moment set. If a commanded moment is feasible, a constrained optimization problem is solved for the control surface deflections.

Fast Implementation of Direct Allocation with Extension to Coplanar Controls

The direct allocation method is considered for the control allocation problem. The original method assumed that every three columns of the controls effectiveness matrix were linearly independent. Here, the condition is relaxed, so that systems with coplanar controls can be considered. For fast online execution, an approach using spherical coordinates is also presented, and results of the implementation demonstrate improved performance over a sequential search. Linearized state-space models of a C-17 aircraft and of a tailless aircraft are used in the evaluation. Oincreasethe reliability ofaircraft,cone gurations with a large numberofactuatorsandcontrolsurfacesareadvantageous.Recone gurable control laws may be used to exploit all of the available control power despite failures and damages. 1;2 Control allocation is the problem of distributing the control requirements among multiple actuators to satisfy the desired objectives while accounting for the limited range of the actuators. Although solutions exist for the control allocation problem, an issue of current interest is that of the feasibilityoftheirimplementationonexistingcomputersforaircraft with a large number of actuators. 3 The direct allocation approach 4i6 is based on the concept of the attainable moment set (AMS), which is the set of all of the moment vectors that are achievable within the control constraints. The methodofdirectallocation allowsoneto achieve100%oftheAMS, whereas some other approaches such as daisy chaining, pseudoinverse,and generalized inversesolutionshavebeen shown to achieve