The differentially flat system, a class of nonlinear systems, contains many mechanical systems. However, few control laws for differentially flat systems are tolerant of disturbances despite many mechanical systems suffer from some disturbances. We aim to design a stabilization control law for differentially flat systems under constant disturbances by using its linearizability and the minimum projection method. First, we design a static control Lyapunov function (CLF) that includes a disturbance for the nonlinear system via a CLF for the linearized system. After that, we prove the designed CLF satisfies the condition of an adaptive control Lyapunov function (ACLF). Finally, we demonstrate an example of designing the proposed adaptive controller for a PVTOL system under winds and verify the effectiveness of the proposed method.
In recent years, control barrier functions have attracted much attention for ensuring safety in collision avoidance and human assist control. However, control laws cannot guarantee the solution of differential equations without properly considering the shape of the target system. In this study, we designed a control law that considers the shape of the control target and designs a control barrier function for non-convex safe sets. Based on this, we proposed an integral control barrier function and confirmed its effectiveness by testing it for collision avoidance between a three-link robot arm and obstacles through simulation and experiment.
This paper addresses a control mechanism to strengthen the cross-sector resilience of dynamic energy and mobility systems. To realize electrification towards decarbonizing smart cities and early recovery in emergencies, the real-time management of electric vehicles (EVs) is essential. EVs cannot achieve both the energy management function and the mobility function depending on user behavior in parallel. To minimize the physical costs and the enforced human behavior change, the dynamic optimization problem of cross-sector energy and mobility systems is proposed. Through simulations imitating the central Tokyo area, the effectiveness, economic cost, and environmental impact of the proposed algorithm are also numerically evaluated.