Constrained Control Allocation Research Articles

Distributed Constrained Control Allocation for Attitude Takeover of Combined Spacecraft

Distributed Constrained Control Allocation for Attitude Takeover of Combined Spacecraft

Disturbance observer‐based model predictive control of a coaxial octorotor with variable centre of gravity

AbstractThis paper presents a model predictive control (MPC) approach based on the extended disturbance observer (EDOB) for trajectory tracking of a coaxial octorotor unmanned aerial vehicle (UAV). First, the system dynamic model is derived using Newton–Euler relations in the presence of time‐varying centre of gravity (COG); then, a two‐loop cascade structure is presented to perform the trajectory tracking task. Both loops are controlled using MPC with feedforward compensation based on the EDOB to improve disturbance rejection abilities. When the mass changes, the moment of inertia and COG are affected. The EDOB simultaneously estimates the effects of time‐varying mass, external disturbances, and parametric uncertainties in six degrees of freedom. After obtaining virtual control inputs using designed controllers, constrained control allocation is used to obtain rotors speed in a valid range. The proposed control scheme is evaluated using simulation. The simulation results show the ability of the developed control strategy in accurate trajectory tracking and stable flight in different conditions and being robust to uncertainty and disturbance.

Constrained control allocation for dynamic ship positioning using deep neural network

Dynamic positioning (DP) is one of the key technologies towards ship autonomy. Ships in DP mode use thruster devices to maintain position and perform low-speed maneuvering. The motion controller issues force requests according to the measured ship state and motion objectives. These requests must be translated into individual thruster commands. Due to constraints in the thrusters, such as inertia and limited angles of operation, state-of-the-art control allocation methods apply constrained optimization techniques. Although such methods readily capture the handling of constraints, they may require significant computational resources in searching for optimized commands in real time. Here we show that a neural network may be applied to offer an effective evaluation of the mapping between motion controller requests and executable thruster commands. An Autoencoder-like neural network is trained with data generated using knowledge about the configuration of the thrusters. Custom loss functions shape the weights of the network, such that the overall motion objectives and thruster constraints are met. Then, the network is applied to perform low-speed maneuvering and stationkeeping in a simulator. Comparison relative to a state-of-the-art variable angle, constrained control allocator indicate similar dynamic performance with reduced peak power consumption.

Constrained Control Allocation Improving Fault Tolerance of a Four Wheel Independently Driven Articulated Vehicle

In articulated vehicles steering is accomplished by adjusting the articulation angle. Commonly a steering actuator is used to pivot the two vehicle sections. This actuator can be dispensed with if the pivoting is controlled by selective distribution of the drive torques to the individually driven wheels instead. Since steering is a safety-critical function, it must be ensured even if one of the drive motors fails. For this purpose, we propose a control method for a fault-tolerant four wheel independently driven articulated vehicle. The control method was developed and tested in a simulation environment and validated on a 1:5 scale demonstrator vehicle. The proposed method with constrained control allocation maintains the desired velocity and articulation angle by distributing the driving torques to the four wheels considering the current actuator limits. Both the simulation and the vehicle tests show that the control method meets the control objectives even when a sudden actuator limit occurs during critical driving scenarios like cornering. Thus, the vehicle can keep its maneuverability in the event of a detected failure of a drive motor. Together with reliable failure detection, the proposed approach provides a basis for further development towards innovative fault-tolerant electric articulated vehicles that meet the requirements of functional safety.

A Constrained Control Allocation and Tuning Scheme for Hybrid Actuators in Spacecraft Attitude Control

Agile rotational maneuvers of spacecraft requires careful execution since its actuators may not be able to produce the demanded torques, causing the state trajectories to deviate and a desired attitude would not be guaranteed. We investigate the control allocation problem for a redundant set of hybrid actuators that include reaction wheels, magnetorquers, and continuous-force thrusters. The main objective of the magnetorquers is to dump momentum from the reaction wheels, whereas the wheels are the primary actuators in attitude control, and more agile maneuvers or faster unloading of momentum can be handled by the thrusters. A modified mixed optimization scheme for control allocation is presented where the equality constraints account for satisfying the high-level (virtual) control inputs for both attitude control and momentum dumping. Variants of dynamic weights in the optimization are developed such that magnetorquers and thrusters may contribute with a relative degree of importance in the attitude control problem. The control allocation scheme is solved using quadratic programming where simulation results are shown for fast and slow rotational maneuvers together with fast and slow momentum dumping.

Integrated Chassis Control With Four-Wheel Independent Steering Under Constraint on Front Slip Angles

This paper presents a method to design an integrated chassis controller with four-wheel independent steering (4WIS) under the constraint on front slip angles for electric vehicles (EVs) adopting in-wheel motor (IWM) driving system. To improve lateral stability and maneuverability of a vehicle, direct yaw moment control strategy is adopted. A control allocation method is adopted to distribute control yaw moment into tire forces, generated by 4WIS. If corrective steering angles of 4WIS are added to front steering angles generated by a driver, it can deteriorate control performance because the lateral tire force of front wheels easily saturated and it causes loss of required yaw moment needed to stabilize a vehicle. To cope with the problem, it is necessary to impose constraints on front slip angles. To compensate the loss of control yaw moment caused by the constraint on front slip angles, a constrained control allocation method is presented. Simulation on driving simulation tool, CarSim <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> , shows that the proposed integrated chassis controller is capable of maintaining lateral stability and maneuverability without performance deterioration under the constraint on the front slip angles.

BFA fuzzy logic based control allocation for fault-tolerant control of multirotor UAVs

ABSTRACTThis paper deals with the problem of fault-tolerant control (FTC) for redundant multirotor unmanned aerial vehicles (UAVs) subject to actuators failures. A fuzzy logic approach is used to solve the constrained control allocation problem by adjusting the components of the multiplexing vector once a motor failure is detected. This fuzzy logic allocation problem is tuned using the Bacterial Foraging Algorithm (BFA), a powerful bio-inspired optimisation technique. The effectiveness of this approach is illustrated through real experimental application to a hexarotor UAV, where up to two motors failures are considered.

Dynamic infinity‐norm constrained control allocation for attitude tracking control of overactuated combined spacecraft

In this study, a dynamic L ∞ (infinity-norm) constrained control allocation scheme is designed for attitude tracking control of combined spacecraft with inertia uncertainties and external disturbances. A disturbance-observer-based constrained backstepping control law is developed to generate the control command signals considering non-symmetric constraints on control input, where the lumped disturbance containing inertia uncertainties and external disturbances is compensated by the output of stable non-linear disturbance observer. The control scheme can guarantee that the attitude and angular velocity tracking error converge to small neighbourhood of zero by appropriately tuning the control parameters. With the consideration of physical amplitude and rate constraints on actuators, the dynamic L ∞ constrained control allocation problem is solved by linear programming technique. Numerical examples demonstrate the effectiveness of the proposed disturbance-observer-based constrained backstepping control method and the dynamic L ∞ constrained control allocation algorithm.

A Fault Tolerant Control Scheme Using the Feasible Constrained Control Allocation Strategy

This paper investigates the necessity of feasibility considerations in a fault tolerant control system using the constrained control allocation methodology where both static and dynamic actuator constraints are considered. In the proposed feasible control al-location scheme, the constrained model predictive control (MPC) is employed as the main controller. This considers the admissible region of the control allocation problem as its constraints. Using the feasibility notion in the control allocation problem provides the main controller with information regarding the actuator′s status, which leads to closed loop system performance improvement. Several simulation examples under normal and faulty conditions are employed to illustrate the effectiveness of the proposed methodology. The main results clearly indicate that closed loop performance and stability characteristics can be significantly degraded by neglecting the actuat-or constraints in the main controller. Also, it is shown that the proposed strategy substantially enlarges the domain of attraction of the MPC combined with the control allocation as compared to the conventional MPC.

A Method to Compensate Interaction between Actuator Dynamics and Control Allocator under Incremental Nonlinear Dynamic Inversion Controller

When designing flight control allocator for an over-actuated flight system, actuator dynamics, generally, are assumed to be ideal since the bandwidths of actuators are much larger than the frequency of aircraft. However, under incremental nonlinear dynamic inversion controller, the interaction between the constrained control allocation frame and actuator dynamics can cause serious consequence. In this work, a method is developed to compensate for actuator dynamics in s-domain analysis. Here, first-order and second-order actuator dynamics are taken into consideration as more complicated actuator dynamics can be combined by these two simplified models. This method solves for gains, which post-processe the output of control allocation frame. The gains are terse in form and are easy to be calculated, which means that it can be implemented into typical flight computer. Simulation results show proposed method can significantly compensate the flaw caused by actuator dynamics.

Input Matrix Factorizations for Constrained Control Allocation

Control allocation (CA) is part of a hierarchical control architecture and distributes the desired control effort of a controller among a set of redundant actuators as it is used, for example, to meet high reliability requirements. Before applying CA, a factorization of a linear plant's input matrix must be carried out. This paper investigates the influence of this factorization on two common algorithms for constrained CA: direct allocation and redistributed pseudoinverse (RPINV). It is shown why the factorization does not affect the first method, whereas it influences the latter one as soon as the number of actuator saturations exceeds a certain threshold. On this basis a modification of RPINV is proposed, which allows the prioritization of virtual control vector components. If the actuator saturations prevent an exact solution, the errors of those components with high priority are preferentially forced to zero. Finally simulations demonstrate the main results.

Torque control allocation based on constrained optimization with regenerative braking for electric vehicles

This paper proposes a constrained optimization-based torque control allocation method aimed to improve energy efficiency, and thus, driving range for electric vehicles. In the proposed method, the cost function is defined not only to achieve desired yaw moment for vehicle handling and stability, but also to minimize power losses for energy efficiency. The particular attention is paid to the power losses due to tire slips both longitudinally and laterally. The constraints are also set based on thorough investigation on various causes of power disppation such that the torque is allocated with restraint to use regenerative braking in its maximum capacity. The proposed control allocation method has been tested and verified to be effective on energy efficiency improvement through both simulation and experiment under various driving maneuvers.

Constrained control allocation for nonlinear systems with actuator failures or faults

Constrained control allocation for nonlinear systems with actuator failures or faults

Constrained Control Allocation for Overactuated Aircraft Using a Neurodynamic Model

In this paper, a constrained control allocation scheme is designed based on the neurodynamic model for an overactuated aircraft with system uncertainties and unknown time-varying external disturbances. To generate the control command signals, an adaptive neural attitude controller is developed, taking into consideration the nonsymmetric input saturation constraint. This control scheme can guarantee semi-global uniform ultimate boundedness for all signals in the closed-loop system. The control command signals are sent to the actuators of the overactuated aircraft via the constrained control allocation scheme. Based on the developed adaptive neural attitude control scheme, the control allocation is designed with the position and rate constraints of actuators taken into account. We pose this constrained control allocation as a convex nonlinear programming problem and use a recurrent neural network as its solver. Simulation study on a near space vehicle is conducted to illustrate the effectiveness of the developed adaptive neural attitude control scheme and the constrained control allocation scheme.

New control allocation algorithms in fixed point framework for overactuated systems with actuator saturation

ABSTRACTIn this paper, two control allocation algorithms have been proposed for overactuated systems. The algorithms are developed by formulating constrained control allocation problem into an equivalent fixed point framework. The first algorithm follows sequential solving method while the other one involves a zero finding technique by the Newton method. In order to consider limiting constraints, the saturation function has been taken into account that leads to a nonsmooth zero finding problem and the proposed method guarantees superlinear convergence. The second algorithm is easy to implement and faster than the algorithm developed based on the sequential solving technique. To demonstrate the effectiveness of the proposed algorithms, a detail simulation study has been carried out, in which one example considers both the actuator rate and amplitude constraints.

Flight Control with Optimal Control Allocation Incorporating Structural Load Feedback

Advances in sensors and avionics computation power suggest real-time structural load measurements could be used in flight control systems for improved safety and performance. A conventional transport flight control system determines the moments necessary to meet the pilot’s command while rejecting disturbances and maintaining stability of the aircraft. Control allocation is the problem of converting these desired moments into control effector commands. In this paper, a framework is proposed to incorporate real-time structural load feedback and structural load constraints in the control allocator. Constrained optimal control allocation can be used to achieve desired moments without exceeding specified limits on monitored load points. Furthermore, certain criteria can be minimized, such as loads on certain parts of the aircraft. Flight safety issues can be addressed by using system health monitoring information to change control allocation constraints during flight. The framework to incorporate structural loads in the flight control system and an optimal control allocation algorithm are described and demonstrated on a nonlinear simulation of a generic transport aircraft with flight dynamics and static structural loads.

Adaptive control and constrained control allocation for overactuated ocean surface vessels

In this article, the constrained control allocation is proposed for overactuated ocean surface vessels with parametric uncertainties and unknown external disturbances. The constrained control allocation is transformed into a convex quadratic programming problem and a recurrent neural network is employed to solve it. To complete the control allocation, the control command is derived via the backstepping method. Adaptive tracking control is proposed for the full-state feedback case using the backstepping technique and the Lyapunov synthesis. It is proved that the proposed adaptive tracking control is able to guarantee semi-global uniform ultimate boundedness of all signals in the closed-loop system. Then, the obtained control command is distributed to each actuator of overactuated ocean vessels. Finally, simulation studies are presented to illustrate the effectiveness of the proposed adaptive tracking control and the constrained control allocation scheme.

A control allocation sterategy based on multi-parametric quadratic programming algorithm

Control allocation is an important part of a system. It implements the function that map the desired command forces from the controller into the commands of the different actuators. In this paper, the authors present an approach for solving constrained control allocation problem in vessel system by using multi-parametric quadratic programming (mp-QP) algorithm. The goal of mp-QP algorithm applied in this study is to compute a solution to minimize a quadratic performance index subject to linear equality and inequality constraints. The solution can be pre-computed off-line in the explicit form of a piecewise linear (PWL) function of the generalized forces and constrains. The efficiency of mp-QP approach is evaluated through a dynamic positioning simulation for a vessel by using four tugboats with constraints about limited pushing forces and found to work well.

Constrained Control Allocation for Vessels with Azimuth Thrusters

Control allocation may produce particular thruster configurations which cause poor maneuverability and temporary loss of controllability in certain directions. The paper presents a new approach for dealing with these singular configurations, which allows to formulate the control allocation problem into optimization problems easy to set up. The approach is validated with numerical simulations on experimental model test data.

Development of constrained control allocation for ship berthing by using autonomous tugboats

In this paper, we propose a new approach to ship berthing by using autonomous tugboats. This approach overcomes the nominal effectiveness problem of actuators at slow speed maneuvering to improve the ship operation in the harbor area. The proposed SMC gave us a sliding mode control law that guarantees position tracking with desired velocity in the presence of environmental disturbances. The thrust allocation problem is solved by using a redistributed pseudo-inverse (RPI) algorithm to determine the thrust and direction of each individual tugboat. The main goal of RPI method is to minimize the power supplied to tugboats and increase their controllability. The proposed approach has been simulated on a model of a supply vessel with excellent results.