Browsing by Author "Liu, Cunjia"

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    Bayesian Estimation of A Periodically-Releasing Biochemical Source Using Sensor Networks
    (IEEE, 2018) Hu, Liang; Su, Jinya; Hutchinson, Michael; Liu, Cunjia; Chen, Wen-Hua
    This paper develops a Bayesian estimation method to estimate source parameters of a biochemical source using a network of sensors. Based on existing models of continuous and instantaneous releases, a model of discrete and periodic releases is proposed, which has extra parameters such as the time interval between two successive releases. Different from existing source term estimation methods, based on the sensor characteristic of chemical sensors, the zero readings of sensors are exploited in our algorithm where the zero readings may be caused by the concentration being below the threshold of the sensors. Two types of Bayesian inference algorithms for key parameters of the sources are developed and their particle filtering implementation is discussed. The efficiency of the proposed algorithms for periodic release is demonstrated and verified by simulation where the algorithm with the exploitation of the zero readings significantly outperforms that without.
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    Dual-layer optimization-based control allocation for a fixed-wing UAV
    (Elsevier, 2021-10-29) Yan, Yunda; Liu, Cunjia; Oh, Hyondong; Chen, Wen-Hua
    Many existing control allocation methods separate the high-level control design from their low-level allocation design, assuming that the constraints of actuators can be guaranteed by the allocator. This idea may not be suitable for the nonlinear fixed-wing unmanned aerial vehicle studied here, which hence motivates this work. In this paper, we propose a new dual-layer optimization-based control allocation method, in which the proposed allocator, on the one hand, can modify the pre-designed virtual signals from the high-level when the out-layer actuator, i.e., throttle, reaches its constraint. On the other hand, it reverts the conventional constrained allocator when the throttle constraints are inactive. Another feature is that under the proposed framework, the initial state of the augmented actuator dynamics serves as design parameters, bringing more degrees of freedom for allocation design without affecting the nominal stability. Apart from the control allocator, this paper also proposes a high-level flight controller based on the control-oriented model and a combination of nonlinear dynamic inversion and disturbance observer. Disturbance observer provides robustness by estimating the model errors between the control-oriented and true models, and compensating for them in the controller. High-fidelity simulation results under realistic wind disturbances are presented to demonstrate the performance of the proposed method.
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    A Novel Disturbance Device for Aerial Manipulation Experiments
    (IEEE, 2023-03-15) Marshall, Benjamin James; Knowles, James; Yan, Yunda; Liu, Cunjia
    In the last decade, UAVs endowed with manipulators have increased in their ability to complete complex tasks such as manipulating doors and drawers. Very recent work also includes tasks with non-constant dynamics such as pushing a cart along a surface with a change in friction coefficient or pulling an electrical plug from a socket. These tasks are hard to design and compare controllers for because their dynamics are complex and they may not behave consistently. This paper proposes a tunable and repeatable mechanism for use in experiments that compare different controller designs. The proposed mechanism, called an overcentre mechanism, can provide a nonlinear resistive force and can be easily modified for different force magnitudes. Additionally, it can be quickly re-oriented to disturb altitude or position channels for vehicles with or without manipulators. This paper experimentally compares three traditional observer designs and a baseline controller in two different operating conditions.