Browsing by Author "Yan, Yunda"
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Item Embargo Continuous output feedback sliding mode control for underactuated flexible-joint robot(Elsevier, 2022-08-23) Wang, Huiming; Zhang, Zhize; Tang, Xianlun; Zhao, Zhenhua; Yan, YundaThe tracking control based on output feedback for a category of flexible-joint robot (FJR) systems is investigated in this brief. Control performance of the systems is inevitably bearing the brunt of various unknown time-varying disturbances, which can be categorized to be matched and mismatched and generally cover internal parameter uncertainties, couplings, unmodelled dynamics, and external load or changing operating environments. To cope with these disturbances, the mismatched disturbances are first transferred to the matched ones by a flatness method, which eliminates the computational cost of estimating mismatched disturbances. Then, a generalized proportional integral observer (GPIO) is constructed to estimate the unavailable states and disturbances. By integrating the estimated disturbance and states provided by the GPIO, a novel dynamic sliding surface is constructed. Finally, a continuous sliding mode control (CSMC)-based output feedback control framework is further designed. The presented control strategy only requires link position information and is continuous, which can effectively reduce the chattering driven by the high-frequency switching item in the traditional SMC method. Asymptotic convergence of output tracking error is guaranteed by theoretical analysis under some mild conditions. Comparative tests on a two-link FJR verify the claimed control performance.Item Embargo Dual-layer optimization-based control allocation for a fixed-wing UAV(Elsevier, 2021-10-29) Yan, Yunda; Liu, Cunjia; Oh, Hyondong; Chen, Wen-HuaMany 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.Item Open Access Generalized Dynamic Predictive Control for Nonlinear Systems Subject to Mismatched Disturbances with Application to PMSM Drives(IEEE, 2023-02-22) Dong, Xin; Mao, Jianliang; Yan, Yunda; Zhang, Chuanlin; Yang, JunThis paper investigates a generalized dynamic predictive control (GDPC) strategy with a novel autonomous tuning mechanism of the horizon for a class of nonlinear systems subject to mismatched disturbances. As a new incremental function for the predictive control method, the horizon can be determined autonomously with respect to the system working conditions, instead of selecting a fixed value via experience before, which is able to effectively improve the control performance optimization ability to a certain extent considering different system perturbation levels. To this aim, firstly, a non-recursive composite control framework is constructed based on a series of disturbance observations via higher-order sliding modes. Secondly, by designing a simple one-step scaling gain update mechanism into the receding horizon optimization, the horizon can be therefore adaptively tuned according to its real-time practical operating conditions. A three-order numerical simulation and a typical engineering application of permanent magnet synchronous motor (PMSM) drive system are carried out to demonstrate the effectiveness and conciseness of the proposed GDPC method.Item Embargo A Novel Disturbance Device for Aerial Manipulation Experiments(IEEE, 2023-03-15) Marshall, Benjamin James; Knowles, James; Yan, Yunda; Liu, CunjiaIn 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.Item Open Access Vision-Based UAV Landing with Guaranteed Reliability in Adverse Environment(MDPI, 2023-02-15) Ge, Zijian; Jiang, Jingjing; Pugh, Ewan; Marshall, Ben; Yan, Yunda; Sun, JiangSafe and accurate landing is crucial for Unmanned Aerial Vehicles (UAVs). However, it is a challenging task, especially when the altitude of the landing target is different from the ground and when the UAV is working in adverse environments, such as coasts where winds are usually strong and changing rapidly. UAVs controlled by traditional landing algorithms are unable to deal with sudden large disturbances, such as gusts, during the landing process. In this paper, a reliable vision-based landing strategy is proposed for UAV autonomous landing on a multi-level platform mounted on an Unmanned Ground Vehicle (UGV). With the proposed landing strategy, visual detection can be retrieved even with strong gusts and the UAV is able to achieve robust landing accuracy in a challenging platform with complex ground effects. The effectiveness of the landing algorithm is verified through real-world flight tests. Experimental results in farm fields demonstrate the proposed method’s accuracy and robustness to external disturbances (e.g., wind gusts).