Hybrid modeling and model based control of the four tank process

MACRo 2015 ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 67-78 ◽  
Author(s):  
Tamás Kardos ◽  
Dénes Nimród Kutasi
Keyword(s):  
Hybrid Systems ◽  
Hybrid Model ◽  
Pi Controller ◽  
Finite State Automata ◽  
Discrete Elements ◽  
Nonlinear Characteristics ◽  
Model Based Control ◽  
Operating Modes ◽  
Hybrid Controller ◽  
Finite State

AbstractHybrid systems contain both continuous dynamics and discrete elements, where discrete transitions happen between different continuous operating modes as a consequence of certain events. The notion of modeling these types of systems is discussed in regard to the four tank process, which has hybrid and nonlinear characteristics. This paper describes the modeling of this system in Simscape software and a hybrid model is created as well, with a hybrid controller being built around it that includes finite-state automata and PI controller. Simulations implemented in Matlab Simulink software prove the viability and correctitude of the method presented.

A Time Complexity Gap for Two-Way Probabilistic Finite-State Automata

1990 ◽  
Vol 19 (6) ◽  
pp. 1011-1023 ◽  
Author(s):  
Cynthia Dwork ◽  
Larry Stockmeyer
Keyword(s):  
Time Complexity ◽  
Finite State Automata ◽  
Finite State ◽  
Probabilistic Finite State Automata

Characterizations of rough finite state automata

2015 ◽  
Vol 8 (3) ◽  
pp. 721-730 ◽  
Author(s):  
Shambhu Sharan ◽  
Arun K. Srivastava ◽  
S. P. Tiwari
Keyword(s):  
Finite State Automata ◽  
Finite State

scholarly journals Copyful Streaming String Transducers

2021 ◽  
Vol 178 (1-2) ◽  
pp. 59-76
Author(s):  
Emmanuel Filiot ◽  
Pierre-Alain Reynier
Keyword(s):  
Polynomial Time ◽  
Equivalence Problem ◽  
Expressive Power ◽  
The Other ◽  
Finite State Automata ◽  
Finite State ◽  
Variable Content ◽  
Deterministic Automata ◽  
Intermediate Output ◽  
Linear Manner

Copyless streaming string transducers (copyless SST) have been introduced by R. Alur and P. Černý in 2010 as a one-way deterministic automata model to define transductions of finite strings. Copyless SST extend deterministic finite state automata with a set of variables in which to store intermediate output strings, and those variables can be combined and updated all along the run, in a linear manner, i.e., no variable content can be copied on transitions. It is known that copyless SST capture exactly the class of MSO-definable string-to-string transductions, and are as expressive as deterministic two-way transducers. They enjoy good algorithmic properties. Most notably, they have decidable equivalence problem (in PSpace). On the other hand, HDT0L systems have been introduced for a while, the most prominent result being the decidability of the equivalence problem. In this paper, we propose a semantics of HDT0L systems in terms of transductions, and use it to study the class of deterministic copyful SST. Our contributions are as follows: (i)HDT0L systems and total deterministic copyful SST have the same expressive power, (ii)the equivalence problem for deterministic copyful SST and the equivalence problem for HDT0L systems are inter-reducible, in quadratic time. As a consequence, equivalence of deterministic SST is decidable, (iii)the functionality of non-deterministic copyful SST is decidable, (iv)determining whether a non-deterministic copyful SST can be transformed into an equivalent non-deterministic copyless SST is decidable in polynomial time.

Synthesis with Mandatory Stop Actions

2021 ◽  
Author(s):  
Giuseppe De Giacomo ◽  
Antonio Di Stasio ◽  
Giuseppe Perelli ◽  
Shufang Zhu
Keyword(s):  
Model Checking ◽  
Finite State Automata ◽  
Deep Impact ◽  
Synthesis Technique ◽  
Büchi Automata ◽  
Finite State ◽  
Ltl Synthesis ◽  
Buchi Automata ◽  
The Impact

We study the impact of the need for the agent to obligatorily instruct the action stop in her strategies. More specifically we consider synthesis (i.e., planning) for LTLf goals under LTL environment specifications in the case the agent must mandatorily stop at a certain point. We show that this obligation makes it impossible to exploit the liveness part of the LTL environment specifications to achieve her goal, effectively reducing the environment specifications to their safety part only. This has a deep impact on the efficiency of solving the synthesis, which can sidestep handling Buchi determinization associated to LTL synthesis, in favor of finite-state automata manipulation as in LTLf synthesis. Next, we add to the agent goal, expressed in LTLf, a safety goal, expressed in LTL. Safety goals must hold forever, even when the agent stops, since the environment can still continue its evolution. Hence the agent, before stopping, must ensure that her safety goal will be maintained even after she stops. To do synthesis in this case, we devise an effective approach that mixes a synthesis technique based on finite-state automata (as in the case of LTLf goals) and model-checking of nondeterministic Buchi automata. In this way, again, we sidestep Buchi automata determinization, hence getting a synthesis technique that is intrinsically simpler than standard LTL synthesis.

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