Haptic interaction is critical in physical Human-Robot Interaction (pHRI), given its wide applications in manufacturing, medical and healthcare, and various industry tasks. A stable haptic interface is always needed while the human operator interacts with the robot. Passivity-based approaches have been widely utilised in the control design as a sufficient condition for stability. However, it is a conservative approach which therefore sacrifices performance to maintain stability. This paper proposes a novel concept to characterise an ultimately passive system, which can achieve the boundedness of the energy in the steady-state. A so-called Ultimately Passive Controller (UPC) is then proposed. This algorithm switches the system between a nominal mode for keeping desired performance and a conservative mode when needed to remain stable. An experimental evaluation on two robotic systems, one admittance-based and one impedance-based, demonstrates the potential interest of the proposed framework compared to existing approaches. The results demonstrate the possibility of UPC in finding a more aggressive trade-off between haptic performance and system stability, while still providing a stability guarantee.

This paper gives a tutorial on iterative learning control nearly five decades after what is widely regarded as the first substantive paper in the literature. The focus is on algorithm development under a number of general headings (linear, optimization, frequency domain, and nonlinear), together with supporting experimental validation/industrial applications and also applications in healthcare.

It is a shared understanding among policy scholars and practitioners that governments with high levels of policy capacity are better able to design and implement public policies for driving economic growth and social development. Despite the centrality of policy capacity, a common definition and measurement of policy capacity remain elusive. There exists a long list of concepts that seek to encapsulate the ability of the governance system to deliver desired policy outcomes–such as state capacity, administrative capacity, governance capacity, bureaucratic capacity–that stimulates greater academic enthusiasm but more often contributes to intellectual divergence on the subject. This paper performed a conceptual analysis of policy capacity through a bibliometric analysis and qualitative framework synthesis of relevant literature various fields like political science, public administration and policy studies. It identified a pattern of fragmentation in the overall approach in defining and operationalizing capacity, which underlies the divergence in the conceptual and operational understanding of policy capacity. A synthetic framework is offered with the intention of putting together this disparate research into a process-oriented dynamic of the development of policy capacity.