Attitude control of magnetically actuated satellites with an uneven inertia distribution

This paper addresses magnetic attitude control of a satellite with one axis of inertia significantly lower than that of the other two. With onboard resources often limited, this paper considers the development of an effective control strategy that remains easy to implement. Often used in this type of application, the classical ‘torque-projection’ approach is shown to be unsuitable for satellites with an uneven inertia distribution. To tackle the weaknesses in this approach a new ‘weighted’ PD approach is proposed, with the control torque determined through minimization of a simple cost function. Through a similar philosophy, a feed-forward compensator is designed to supplement the feedback control and improve the disturbance rejection characteristics of the controller. Floquet analysis is used to verify stability of the control strategy for the nominal case and satellites with uncertainties. Simulations carried out on a high fidelity model demonstrate the effectiveness of the proposed control law and the significant performance benefits offered over existing approaches

Model predictive control of low earth orbiting spacecraft with magneto-torquers

The problem of attitude control using magnetic torque rods is addressed, in order to demonstrate predictive control as a suitable and effective technique of magnetic attitude control. The study addresses the key issues of magnetic field modeling, controller stability and implementation. Two controller designs are implemented, the first adopting an MPC approach with a constant magnetic field assumption, while the second method includes the true variation of the magnetic field within the control law. Both methods demonstrate significantly improved performance over PD control with the inclusion of the true magnetic field variation leading to the best results. Controller stability is considered with and without terminal penalty within the cost function. Floquet analysis demonstrates both methods to be stable, however the terminal penalty based method leads to a more stable controller

Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer

In this paper, the adaptive fuzzy tracking control is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems in the presence of system uncertainties, unknown non-symmetric input saturation and external disturbances. Fuzzy logic systems (FLS) are used to approximate the system uncertainty of MIMO nonlinear systems. Then, the compound disturbance containing the approximation error and the time-varying external disturbance that cannot be directly measured are estimated via a disturbance observer. By appropriately choosing the gain matrix, the disturbance observer can approximate the compound disturbance well and the estimate error converges to a compact set. This control strategy is further extended to develop adaptive fuzzy tracking control for MIMO nonlinear systems by coping with practical issues in engineering applications, in particular unknown non-symmetric input saturation and control singularity. Within this setting, the disturbance observer technique is combined with the FLS approximation technique to compensate for the effects of unknown input saturation and control singularity. Lyapunov approach based analysis shows that semi-global uniform boundedness of the closed-loop signals is guaranteed under the proposed tracking control techniques. Numerical simulation results are presented to illustrate the effectiveness of the proposed tracking control schemes

Explicit non-linear model predictive control for autonomous helicopters

Trajectory tracking is a basic function required for autonomous helicopters, but it also poses challenges to control design due to the complexity of helicopter dynamics. This article introduces an explicit model predictive control (MPC) to solve this problem, which inherits the advantages of non-linear MPC but eliminates time-consuming online optimization. The explicit solution to the non-linear MPC problem is derived using Taylor expansion and exploiting the helicopter model. With the explicit MPC solution, the control signals can be calculated instantaneously to respond to the fast dynamics of helicopters and suppress disturbances immediately. On the other hand, the online optimization process can be removed from the MPC framework, which can accelerate the software development and simplify onboard hardware. Due to these advantages of the proposed method, the overall control framework has a low complexity and high reliability, and it is easy to deploy on small-scale helicopters. The proposed explicit non-linear MPC has been successfully validated in simulations and in actual flight tests using a Trex-250 small-scale helicopter

Failure boundary estimation for lateral collision avoidance manoeuvres

This paper proposes a method for predicting the point at which a simple lateral collision avoidance manoeuvre fails. It starts by defining the kinematic failure boundary for a range of conflict geometries and velocities. This relies on the assumption that the ownship aircraft is able to turn instantaneously. The dynamics of the ownship aircraft are then introduced in the form of a constant rate turn model. With knowledge of the kinematic boundary, two optimisation algorithms are used to estimate the location of the real failure boundary. A higher fidelity simulation environment is used to compare the boundary predictions. The shape of the failure boundary is found to be heavily connected to the kinematic boundary prediction. Some encounters where the ownship aircraft is travelling slower than the intruder were found to have large failure boundaries. The optimisation method is shown to perform well, and with alterations to the turn model, its accuracy can be improved. The paper finishes by demonstrating how the failure boundary is used to determine accurate collision avoidance logic. This is expected to significantly reduce the size and complexity of the verification problem

Model predictive control of low earth orbiting spacecraft with magneto-torquers

The problem of attitude control using magnetic torque rods is addressed, in order to demonstrate predictive control as a suitable and effective technique of magnetic attitude control. The study addresses the key issues of magnetic field modeling, controller stability and implementation. Two controller designs are implemented, the first adopting an MPC approach with a constant magnetic field assumption, while the second method includes the true variation of the magnetic field within the control law. Both methods demonstrate significantly improved performance over PD control with the inclusion of the true magnetic field variation leading to the best results. Controller stability is considered with and without terminal penalty within the cost function. Floquet analysis demonstrates both methods to be stable, however the terminal penalty based method leads to a more stable controller

Artificial situation awareness for increased autonomy of unmanned aerial systems in the terminal area

Situation awareness is the human function of perceiving, comprehending and projecting the state of the environment which is of critical importance to the safe operation of aircraft. A highly autonomous Unmanned Aerial System (UAS) must replicate this behaviour in order to maintain an acceptable level of safety verses a manned vehicle. Nowhere in the flight is situation awareness more critical than during operation in the terminal area. Of primary concern during this stage of flight is the awareness of other traffic heading for the same airfield. This paper presents of a novel method of spatial projection of traffic vehicles encountered by an autonomous UAS in the terminal stage of flight. This projection method relies on a cooperative means of traffic perception, such as Automated Dependant Surveillance - Broadcast (ADS-B) and assumes there is a predefined route which vehicles follow through the terminal region. Whilst this is the case at the majority of airfield, traffic vehicles will not follow this path perfectly. This uncertainty in path following accuracy is captured by utilising a curvilinear reference frame and dealing with discrete transitions (such as the initiation of a turn) separately. It is shown that whilst this technique increases the computational complexity of the problem it can offer significant performance benefit

Plant template generation of uncertain plants in quantitative feedback theory

The creation of templates for uncertain plants is an essential first step in Quantitative Feedback Theory (QFT) and other frequency domain methods. For the plants with general uncertain structure, a method to identify the critical interior points in an uncertain parameter set which map to the boundaries of plant templates is presented. It is shown that the boundaries of templates are only generated by the edges of an uncertain parameter set and those critical interior points. With the help of symbolic computation, a computational tractable procedure for generating the templates is developed. This general procedure is illustrated by a vehicle clutch systems and the longitudinal dynamics of a small aircraft where the underlying uncertain parameters perturb both plants nonlinearly

Locust recognition and detection via aggregate channel features

Locust plagues are very harmful for food security, quality and quantity of agricultural products. With this consideration, precise locust detection is significant for preventing locust plagues. To achieve this task, aggregate channel feature (ACF) object detector with parameters optimization is applied to detect locusts. Experiment results show that ACF object detector with optimized parameters can achieve 0.39 for average precision and 0.86 for log-average miss rate. Moreover, ACF is a non-deep method using a simple model to detect objects. That is, the proposed method is promising to be embedded in a real-time locust detection system

Static disturbance-to-output decoupling for nonlinear systems with arbitrary disturbance relative degree

Static disturbance-to-output decoupling problem for nonlinear systems with arbitrary disturbance relative degree is addressed in this paper without resorting to a high-gain design. A systematic design method is developed for the design of the disturbance compensation gain in the control law. It is shown that the influence of the disturbance can be eliminated from the output channel in steady state with the proposed design method. More interesting, the exact disturbance decoupling methods turn out to be special cases of the proposed control law. The feasibility of extending the proposed method to unmeasurable disturbance case is also investigated by integrating a nonlinear disturbance observer. It is further discussed that the proposed method can be extended to multiple disturbance cases with almost no modification. Simulation example of a missile shows that the proposed method is effective in rejecting disturbance with arbitrary relative degree