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This monograph presents some existing and new results on analysis and design of finite-time and fixed-time converging systems. Two main groups of appr...Lees meer
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Multi-Agent Systems (MAS) use networked multiple autonomous agents to accomplish complex tasks in areas such as space-based applications, smart grids,...Lees meer
As modern systems become larger and the impact of a failure can be wide-ranging in some cases causing havoc to everyday life system reliance, the abil...Lees meer
Economic Model Predictive Control (EMPC) is a control strategy that moves process operation away from the steady-state paradigm toward a potentially t...Lees meer
Reduced order models, or model reduction, have been used in many technologically advanced areas to ensure the associated complicated mathematical mode...Lees meer
A reset controller is a linear controller whose output is reset to zero whenever its input and output satisfy an appropriate algebraic relationship. I...Lees meer
This monograph provides the reader with a comprehensive overview of game theory covering the foundations of the theory of noncooperative and cooperati...Lees meer
Model Predictive Control (MPC) can be dated back to the 1960s, and can now be regarded as a mature control method, which has had significant impact on...Lees meer
Real-world problems are often formulated as diverse properties of different types of dynamical systems. Hence property verification and synthesis have...Lees meer
Max-plus linear systems theory was inspired by and originated from classical linear systems theory more than three decades ago, with the purpose of de...Lees meer
Recent years have seen the advent of new large cyber-physical systems such as sensor and social networks. These network systems are typically spatiall...Lees meer
Multi-robot systems have huge potential for practical applications, which include sensor networks, area surveillance, and environment mapping. In many...Lees meer
The methods for hybrid systems are distributed across a wide spectrum, ranging from methods known in the discrete (cyber-)domain at one end, to tradit...Lees meer
The recent success of Reinforcement Learning and related methods can be attributed to several key factors. First, it is driven by reward signals obtai...Lees meer
This monograph describes the use of principles of reinforcement learning (RL) to design feedback policies for continuous-time dynamical systems that c...Lees meer
Positive Markov Jump Linear Systems are piecewise positive linear systems affected by a stochastic signal generated by a Markov chain. Positive system...Lees meer
Positive systems are an important class of systems that frequently arise in application areas, such as in the chemical process industry, electronic ci...Lees meer
In an increasingly connected world, the term cyber-physical networks has been coined to refer to the communication among devices that is turning smart...Lees meer
One of the open questions in neuroscience is the function of the cerebellum, a major brain region involved in regulation of the motor systems, speech,...Lees meer