Control Allocation System Research Articles

Fault Tolerant Super Twisting Sliding Mode Control of a Quadrotor UAV Using Control Allocation

In this study, a fault-tolerant super-twisting sliding mode controller with a control allocation system for a quadrotor aircraft is proposed. Super twisting sliding mode control is a robust control technique that handles a system with a relative degree equal to one. A super-twisting sliding mode controller is proposed because of its robustness to uncertainties and perturbations. It increases accuracy and reduces chattering. A control allocation algorithm is developed to cope with the actuator fault. Firstly, a nonlinear model of the quadrotor unmanned aerial vehicle (UAV) is presented. Then, the controller design and type of the actuator fault are explained. The control allocation algorithm is used to optimize the trajectory tracking performance of the quadrotor in the presence of an actuator fault. A control allocation algorithm is an effective approach to implementing fault-tolerant control. When actuator faults are identified, they can be modeled as changes in the B matrix of constraints. Various simulations have been made for situations with and without actuator failure. In normal conditions, the quadrotor can accurately track altitude, roll, pitch and yaw references. In faulty conditions, the quadrotor can follow the references with a small error. Simulations prove the effectiveness of the control allocation algorithm, which stabilizes the quadrotor in case of an actuator fault. Overall, this paper presents a novel fault-tolerant controller design for quadrotor aircraft that effectively addresses actuator faults using a super-twisting sliding mode controller and control allocation algorithm.

Performance analysis of control allocation using data‐driven integral quadratic constraints

AbstractA new method is presented for evaluating the performance of a nonlinear control allocation system within a linear control loop. To that end, a worst‐case gain analysis problem is formulated that can be readily solved by means of well‐established methods from robustness analysis using integral quadratic constraints (IQCs). It exploits the fact that control allocation systems are in general memoryless mappings that can be bounded by IQCs. A data‐driven approach is used to find an optimal bound of the input/output mapping of the control allocation. Additionally, an iterative procedure based on local IQCs is introduced to determine meaningful sampling limits for less conservative yet accurate results. The effectiveness of the proposed data‐driven performance analysis is shown at the example of an actively controlled flexible wing in a wind tunnel.

Reconfiguration Control Design of UAV against Actuator Faults Based on Control Allocation Method

The paper concentrates on the problem of fault-tolerant control of UAV against actuator faults from the perspective of flight control system architecture. Using backstepping control method and inverse optimization theory, the design of backstepping optimal control law was constructed. Based on the fault monitoring mechanism of vehicle management computer in the distributed flight control and control allocation system, a fault-tolerant control design method was established in the case of multiple failure modes of the actuators, which compensates the influence caused by the failures. Finally, the effectiveness of the proposed strategy was verified by numerical simulation.

Control Allocation for Reaction Thrusters of a Moon Lander using Linear Programming

Attitude control of the lunar lander is achieved through reaction control system (RCS). RCS works in pulsing mode and needs control allocation system which takes care of attitude tracking with minimum fuel consumption. Most of the control allocation techniques are based on pulse modulation technique, which are difficult to implement for RCS, where torques generated by RCS are generally coupled with each other. In this paper, eight unilateral pulsing mode attitude thruster for attitude correction of lunar module targeted for soft landing is presented. Linear programming based control allocation technique for RCS has been discussed, which gives fuel optimal solution with accurate tracking as a constraint. Landing specific simulation is done to validate the control system.

Multivariate Spline-Based Adaptive Control of High-Performance Aircraft with Aerodynamic Uncertainties

In this paper, a new modular adaptive control system is presented to compensate for aerodynamic uncertainties in high-performance flight control systems. This approach combines nonlinear dynamic inversion with multivariate spline-based adaptive control allocation. A new real-time identification routine for multivariate splines is presented to compensate for aerodynamic uncertainties in the control allocation system. This method, indicated as spline-based adaptive nonlinear dynamic inversion, is applied to control an F-16 aircraft subject to significant aerodynamics uncertainties. Simulation results indicate that the new controller can tune itself each time a model error is detected and has superior adaptability compared to an ordinary polynomial-based adaptive controller. Multivariate splines have sufficient flexibility and approximation power to accurately model nonlinear aerodynamics over the entire flight envelope. As a result, the global model remains intact. Although a part of the model is being reconfigured using incoming observations, the remainder of the model remains unchanged and can be used as an a priori source of information. This prevents the occurrence of sudden fundamental changes in the global model structure, which are experienced when using ordinary polynomials.

Global Chassis Control System Using Suspension, Steering, and Braking Subsystems

A novelGlobal Chassis Control(GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation.

Control Allocation Design of Reaction Control System for Reusable Launch Vehicle

During the early stage of reusable launch vehicle (RLV) reentry flight, reaction control system (RCS) is the major attitude control device. RCS, which is much different from the atmospheric steer’s control, requires a well designed control allocation system to fit the attitude control in high altitude. In this paper, an indexed control method was proposed for RCS preallocation, a 0-1 integer programming algorithm was designed for RCS allocation controller, and then this RCS scheme’s effect was analyzed. Based on the specified flight mission simulation, the results show that the control system is satisfied. Moreover, several comparisons between the attitude control effect and RCS relevant parameters were studied.

Closed-loop dynamic control allocation for aircraft with multiple actuators

A closed-loop control allocation method is proposed for a class of aircraft with multiple actuators. Nonlinear dynamic inversion is used to design the baseline attitude controller and derive the desired moment increment. And a feedback loop for the moment increment produced by the deflections of actuators is added to the angular rate loop, then the error between the desired and actual moment increment is the input of the dynamic control allocation. Subsequently, the stability of the closed-loop dynamic control allocation system is analyzed in detail. Especially, the closed-loop system stability is also analyzed in the presence of two types of actuator failures: loss of effectiveness and lock-in-place actuator failures, where a fault detection subsystem to identify the actuator failures is absent. Finally, the proposed method is applied to a canard rotor/wing (CRW) aircraft model in fixed-wing mode, which has multiple actuators for flight control. The nonlinear simulation demonstrates that this method can guarantee the stability and tracking performance whether the actuators are healthy or fail.

A control allocation method based on equivalent virtual control surfaces

Most existing allocation methods need the control effectiveness matrix to solve the problem, and their allocation accuracy directly depends on the identification precision of the control effectiveness matrix. If the matrix is poorly identified, the designed allocator may not work well. This paper presents an allocation method based on equivalent virtual control surface whose aerodynamic effect is equivalent to the real effectors. The method divides the design of control allocation system into two parts: the longitudinal and lateral, solve the problem and find the allocation law by choosing reasonable equivalent virtual effectors. Simulation results show that the proposed method can make the responses of roll angle and yaw angle follow the command signals well.

Control allocation and management of redundant control effectors based on bases sequenced optimal method

For an advanced aircraft, the amount of its effectors is much more than that for a traditional one, the functions of effectors are more complex and the coupling between each other is more severe. Based on the current control allocation research, this paper puts forward the concept and framework of the control allocation and management system for aircrafts with redundancy control effectors. A new optimal control allocation method, bases sequenced optimal (BSO) method, is then presented. By analyzing the physical meaning of the allocation process of BSO method, four types of management strategies are adopted by the system, which act on the control allocation process under different flight conditions, mission requirements and effectors working conditions. Simulation results show that functions of the control allocation system are extended and the system adaptability to flight status, mission requirements and effector failure conditions is improved.