In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfa...In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.展开更多
The continuous evolution of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)presents ongoing challenges and risks to public health,as it renders most reported monoclonal antibodies(mAbs)ineffective due to i...The continuous evolution of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)presents ongoing challenges and risks to public health,as it renders most reported monoclonal antibodies(mAbs)ineffective due to immune escape[1,2].Unlike conventional strategies that rely on conserved epitopes across known viral subtypes,the extraordinary pace and unpredictability of SARS-CoV-2 mutations have progressively eroded these epitopes,thereby destabilizing the foundations of traditional broadly neutralizing antibody(bnAb)development[3].展开更多
文摘In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.
基金funded by the External Cooperation Program of CAS(grant number 180GJHZ2023017MI)to G.F.G.
文摘The continuous evolution of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)presents ongoing challenges and risks to public health,as it renders most reported monoclonal antibodies(mAbs)ineffective due to immune escape[1,2].Unlike conventional strategies that rely on conserved epitopes across known viral subtypes,the extraordinary pace and unpredictability of SARS-CoV-2 mutations have progressively eroded these epitopes,thereby destabilizing the foundations of traditional broadly neutralizing antibody(bnAb)development[3].
