Nowadays autonomous systems are expected to perform complex tasks that go beyond traditional control objectives such as setpoint tracking or consensus of multi-agent systems. More specifically, in a plethora of applications agents often need to collaborate with their peers in order to perform a variety of spatial tasks within strict deadlines. Spatio-temporal tasks of this form can be easily expressed in Signal Temporal Logic (STL), a predicate language that allow us to formally introduce time-constrained tasks defined as Boolean combinations of simpler subformulas involving temporal operators such as the always, eventually and until operator.

In this thesis we consider the problem of control under high-level specifications for single as well as multi-agent systems. Our work is divided in three parts. In the first part we consider spatio-temporal objectives expressed in Signal Temporal Logic and propose feedback control laws guaranteeing the satisfaction of the tasks under consideration using various levels of state information. First, motivated by multi-platoon coordination scenarios we design a nonlinear feedback control law ensuring minimal violation of a STL task involving merging and splitting of given pairs of platoons when the satisfaction of the task can not be achieved due to actuation limitations. Next, we propose a novel control barrier function to encode the satisfaction of a STL fragment involving disjunctions of selected STL tasks. As a further contribution, we propose a distributed switching feedback control law for the satisfaction of a given set of relative position-based STL tasks that is based on the prescribed performance control philosophy.

In the second part model predictive control schemes are designed for single and multi-agent systems subject to STL, input and state constraints. Contrary to state of the art, the proposed approaches encode the satisfaction of the STL tasks under consideration using continuous variables. In addition, the proposed MPC schemes are shown to be recursively feasible thanks to appropriately designed terminal ingredients while the planning horizon of the related  problems can be chosen arbitrarily small and independent of the STL task. To deal with collaborative tasks often present in multi-agent setups we present a novel approach to decompose the tasks into agent-dependent objectives allowing the design of non-cooperative control schemes that guarantee the satisfaction of the initial task with limited communication. Finally, a sequential distributed MPC scheme is proposed for coupled STL tasks offering a desired trade-off between the systems' performance and the computational complexity of previously proposed centralized approaches. The proposed scheme is solved in discrete-time yet continuous-time constraint satisfaction is ensured thanks to an appropriate tightening of the constraint sets.

Finally, in part III we consider time-invariant objectives such as safety, formation and tracking of single and multiple agents, respectively, and propose a set of feedback control laws ensuring the satisfaction of the desired objectives at all times.

Moderna autonoma system förväntas utföra komplexa uppgifter bortom traditionella reglermål såsom referensspårning och konsensus hos fler-agent-system. Många applikationer kräver att agenter samarbetar med sina kamrater för att utföra olika rumsliga uppgifter inom strikta deadlines. Spatio-temporal uppgifter av denna form kan enkelt uttryckas i Signal Temporal Logic (STL), ett predikatspråk som tillåter oss att formellt introducera tidsbegränsade uppgifter i form av booleska kombinationer av enklare underformler, vilka involverar temporala operatorer såsom alltid-, så småningom- och till dess att-operatorer.

I den här avhandlingen behandlar vi styrning under högnivå-specifikationer av system med både enstaka och flera agenter. Vårt arbete är uppdelat i tre delar. I den första delen behandlar vi spatio-temporal mål uttryckta i Signal Temporal Logic och föreslår återkopplingsreglering som garanterar att de givna målen uppnås, med hjälp av olika nivåer av tillståndsinformation. I den andra delen utformar vi modell-prediktiva reglersystem för system med enstaka och flera agenter och STL-, inmatnings- och tillståndsbegränsningar. Slutligen behandlar vi i den sista delen tidsinvarianta mål såsom säkerhet, formation och spårning av enstaka respektive flera agenter, och föreslår en uppsättning återkopplingskontrolllagar som säkerställer att de önskade målen uppnås hela tiden.