Research And Application Of Control Allocation Theory For Overactuated Systems

Overactuated systems with redundant control effectors can be found in many places, such as aerospace, marine vessels, automatic vehicles, robotics and industrial process applications. In this kind of system, control allocation is one of key problems for design and analysis, and has been one of the important and hot research topics in control theory and engineering. Using control allocation, it is possible to split control design into two steps: firstly, a control law is designed to specify the total control effort (virtual commands); secondly, a control allocation algorithm is designed to distribute the required control moment over the actuators in order to obtain the desired response. With the increasing complexity of plants and environment, the traditional control allocation algorithms are not suitable for modern system. It is necessary to study advanced control allocation algorithms and overactuated systems related problems.The control allocation problem of overactuated systems is investigated, and the limitation of current methods is analyzed. Several topics, such as robust control allocation under uncertainty modeling, nonlinear control allocation under representative nonlinear condition and dynamic control allocation including actuator dynamics are discussed in this paper. Some new methods are obtained. Some of the results are applied to the flight control system of modern aircraft with multiple effectors. The main research contents are listed as follows:(1) Aiming at the uncertainty modeling for control effectiveness of aircraft with multiple effectors, a new control allocation algorithm based on robust optimization is proposed when control effectiveness uncertainties are considered. The original robust optimal model is established. Following with the transformation of its robust counterpart with ellipsoidal and the conic quadratic representable uncertainty set are researched. The numerical solution of robust control allocation algorithm is discussed. Simulations on optimal control allocation of aircraft with multiple effectors show that the proposed algorithm can reduce the impact of the control effectiveness uncertainties, so the results are more reasonable.(2) As the number of control effectors placed on a vehicle increases, the likelihood of the occurrence of control effector interactions increases. In this case, the nonlinearity of control effectiveness can not be ignored. We studied the control allocation problem including control effector interactions. And a compensate algorithm based on sequential linear programming methods is devised to improve the allocation results.(3) Traditional methods assume that a perfect linear relationship exists between control moments and effector deflections. However, this relationship is intrinsically nonlinear, especially in the event of failure of one or more actuators. In this paper we consider the control allocation problem with nonmonotonic nonlinearities for overactuated systems. To solve this problem, we propose a differential evolution (DE) strategy. The problem formulation and the algorithm's procedure are studied. Simulation results show that the proposed method outperforms the traditional approaches.(4) A data driven subspace predictive control allocation approach is proposed for overactuated system with actuator dynamics.Through online subspace identification,uncertainty model is used for description of actuator dynamic characteristic.A novel control allocation with actuator dynamics is designed by using subspace predictive control theory. The actuator modeling, designing of control allocator and the actuator controller are then included in a framework, which increases robustness of the control system.Simulation examples are given to demonstrate the efficiency of the proposed strategy.(5) The Backstepping method combined with online control allocation is applied to flight control system design of a class of aircrafts with multiple effectors. The strict feedback form of nonlinear dynamic model is introduced. A high level backstepping controller is developed, and the stability is proved. The least squares method is used to estimate the actuator effectiveness and the online control allocation is implemented by using robust algorithm proposed in chapter 3. The simulations show the effectiveness, robustness and the control reconfiguration capability in presence of actuator failure.