In space systems, controlled dynamics are often modeled using linear time-varying (LTV) models due to the periodic orbital motion of spacecraft. When designing such models, it is advantageous to construct computationally feasible representations that exhibit clear controllability properties. Network modeling approaches are particularly effective in this context. This paper addresses the need for efficient rendezvous techniques in emerging orbital services, such as active debris removal and cargo delivery. To improve sustainability and extend satellite lifespans, a continuous-time feedback control framework is proposed for autonomous rendezvous operations, utilizing low-thrust propulsion based on relative orbit elements. Controllability is enhanced by deriving a periodic LTV model that incorporates J2 perturbations. Additionally, structural controllability is employed as a key design principle in the development of a control-oriented surrogate model that ensures persistent controllability throughout an entire orbital revolution while simultaneously minimizing modeling error. The proposed framework constructs a surrogate model that preserves the essential orbital dynamics while enforcing continuous controllability. The effectiveness of the framework is validated through numerical examples.
This article proposes a visibility manifold surrogate framework for satellite and constellation coverage analysis under generalized sensor footprints and secular [Formula: see text] perturbations. To characterize generalized field-of-view constraints, a unified mathematical model utilizing a signed distance field is established, reducing the visibility problem to a bounded parameter space via equivalence mapping. Building upon the resulting high-dimensional visibility boundary manifold, a topological layered decomposition approach constructs locally single-valued interpolation surrogate models. To mitigate nonlinear interpolation errors near the manifold boundaries, a vectorized tubular-parameter correction mechanism is integrated, transforming large-scale constellation coverage computations into efficient analytical queries. The framework is further extended to rapidly evaluate dynamic accumulated coverage for regional targets by incorporating polygon Boolean intersections and one-dimensional boundary extremum optimization. Simulation results demonstrate that, compared to traditional numerical root-finding approaches, the proposed method accelerates computational speed by over an order of magnitude while maintaining access window timing errors predominantly below [Formula: see text]. Consequently, the proposed visibility manifold surrogate framework provides a geometric tool for large-scale constellation design, agile resource scheduling, and Earth observation missions.
This paper presents an improved structure for an urban air route network, based on a node-edge grid. The enhanced network incorporates additional edge directions to increase routing flexibility. Flights are assigned to different flight levels according to the semicircular rule while complying with legal requirements of minimum and maximum flight altitudes. The routing algorithm integrates nonlinear penalization functions for large heading changes and large bank angles to improve passenger comfort. Furthermore, flights conducted against the primary direction of their respective flight level are penalized. The routes computed using three distinct network concepts are evaluated based on newly developed metrics for efficiency and safety. The evaluation also includes a full-day simulation of all flights to detect separation conflicts and ensure operational safety.
A hybrid-estimation-based adaptive control allocation (ACA) is proposed in this paper that incorporates a hybrid estimator and a cascaded control allocation (CA) scheme. The hybrid estimator assesses the multicollinearity of the correlation matrix and blends ordinary least squares and principal component regression solutions using a multicollinearity-dependent blending factor. When an electric vertical takeoff and landing (eVTOL) aircraft remains in hover during a steady flight, the absence of maneuver commands leads to low persistent excitation, which in turn aggravates the multicollinearity of the regressor matrix. In such a case, the hybrid estimator provides biased but low-variance parameter estimates with reduced sensitivity to noise. These parameter estimates, along with multicollinearity information, are fed into a proposed cascaded CA for allocating desired pseudo-control-rate commands. In the first stage of the cascaded CA, the desired commands are fulfilled by intermediate control inputs. In the second stage, when high multicollinearity is detected, excitation signals along the weak directions of the correlation matrix can be injected promptly into the system, which facilitates regulation of the correlation matrix and further reduces the impact of multicollinearity. The effectiveness of the proposed method is validated on a high-fidelity eVTOL aircraft model in hover mode. By considering the multicollinearity within the proposed hybrid-estimation-based ACA, the tracking performance in the roll, pitch, and heave channels is significantly improved, despite limited enhancement in the yaw channel.
