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In this paper, we introduce operators, semantics, and conditions that, when possible, are solution-independent to guarantee basic temporal logic specifications for hybrid dynamical systems. Employing sufficient conditions for forward invariance and finite time attractivity of sets for such systems, we derive such sufficient conditions for the satisfaction of formulas involving temporal operators and atomic propositions. Furthermore, we present how to certify formulas that have more than one operator. Academic examples illustrate the results throughout the paper.

This paper presents a model predictive control (MPC) algorithm that asymptotically stabilizes a compact set of interest for a given hybrid dynamical system. The considered class of systems are described by a general model, which identifies the dynamics by the combination of constrained differential and difference equations. The model allows for trajectories that exhibit multiple jumps at the same time instant, or portray Zeno behavior. At every optimization time, the proposed algorithm minimizes a cost functional weighting the state and the input during both the continuous and discrete phases, and at the terminal time via a terminal cost, without discretizing the continuous dynamics. To account for the structure of time domains defining solution pairs, the minimization is performed in a manner akin to free end-time optimal control. When the terminal cost is a control Lyapunov function on the terminal constraint set, recursive feasibility and asymptotic stability of the proposed algorithm can be guaranteed. A sample-and-hold control system and a bouncing ball model are two examples reported to demonstrate the applicability and effectiveness of the proposed approach.

In this paper we propose a hybrid control strategy to solve the problem of rendezvous, proximity operations, and docking of an autonomous spacecraft in 3D. Due to the different constraints and tasks to perform, a hybrid systems approach is implemented to solve the problem in three phases: 1) rendezvous; 2) rendezvous with smaller relative distance; 3) docking phase; and 4) docked phase; with range and angle measurements. In this approach, we implement a supervisor that robustly coordinates the individual controllers to accomplish the whole mission. We also present the designs of these individual controllers that solve the appropriate control problems for the individual phases. Numerical results for both the nominal and perturbed case validate the hybrid control strategy for the spacecraft close-proximity mission.

This paper presents a model predictive control (MPC) algorithm that asymptotically stabilizes a compact set of interest for a given hybrid dynamical system. The considered class of systems are described by a general model, which identifies the dynamics by the combination of constrained differential and difference equations. The model allows for trajectories that exhibit multiple jumps at the same time instant, or portray Zeno behavior. At every optimization time, the proposed algorithm minimizes a cost functional weighting the state and the input during both the continuous and discrete phases, and at the terminal time via a terminal cost, without discretizing the continuous dynamics. To account for the structure of time domains defining solution pairs, the minimization is performed in a manner akin to free end-time optimal control. When the terminal cost is a control Lyapunov function on the terminal constraint set, recursive feasibility and asymptotic stability of the proposed algorithm can be guaranteed. A sample-and-hold control system and a bouncing ball model are two examples reported to demonstrate the applicability and effectiveness of the proposed approach.

Pointwise asymptotic stability is a property of a set of equilibria of a dynamical system, where every equilibrium is Lyapunov stable and every solution converges to some equilibrium. Hybrid systems are dynamical systems which combine continuous-time and discrete-time dynamics. In this paper, they are modeled by a combination of differential equations or inclusions, of difference equations or inclusions, and of constraints on the resulting motions. Sufficient conditions for pointwise asymptotic stability of a closed set are given in terms of set-valued Lyapunov functions: they require that the values of the Lyapunov function shrink along solutions. Cases of strict and weak decrease are considered. Lyapunov functions, not set-valued, which imply that solutions have finite length are used in sufficient conditions and related to the set-valued Lyapunov functions. Partial pointwise asymptotic stability is also addressed.

Pointwise asymptotic stability is a property of a set of equilibria of a dynamical system, where every equilibrium is Lyapunov stable and every solution converges to some equilibrium. Hybrid systems are dynamical systems which combine continuous-time and discrete-time dynamics. In this paper, they are modeled by a combination of differential equations or inclusions, of difference equations or inclusions, and of constraints on the resulting motions. Sufficient conditions for pointwise asymptotic stability of a closed set are given in terms of set-valued Lyapunov functions: they require that the values of the Lyapunov function shrink along solutions. Cases of strict and weak decrease are considered. Lyapunov functions, not set-valued, which imply that solutions have finite length are used in sufficient conditions and related to the set-valued Lyapunov functions. Partial pointwise asymptotic stability is also addressed.

This paper deals with the estimation of the state of linear time invariant systems for which measurements of the output are available sporadically. An observer with jumps triggered by the arrival of such measurements is proposed and studied in a hybrid systems framework. The resulting system is written in estimation error coordinates and augmented with a timer variable that triggers the event of new measurements arriving. The design of the observer is performed to achieve uniform global asymptotic stability (UGAS) of a closed set including the points for which the state of the plant and its estimate coincide. Furthermore, a computationally tractable design procedure for the proposed observer is presented and illustrated in an example.