Controller Synthesis for Probabilistic Signal Temporal ..

N2 - This paper considers the fixed-structure, discrete-time mixed ℋ2/ℋ∞ controller synthesis problem in the delta operator (difference operator) framework. The differential operator and shift operator versions of the problem are reviewed for comparison, and necessary conditions are derived for all three formulations. A quasi-Newton/continuation algorithm is then used to obtain approximate solutions to these equations. Controllers are synthesized for two numerical examples, and the performance of the algorithm on the differential, difference and shift operator versions of the problems is compared.

09/01/2018 · We study the controller synthesis problem under budget constraints

The Synopsys Synthesis Example illustrates that the RTL synthesis is moreefficient than the behavior synthesis, although the simulation of previousone requires a few clock cycles.


Controller Synthesis with Budget Constraints | …

Most of the examples have been simulated by ActiveHDL Simulator and  Design Analyzer, as well as synthesized with Synopsys Design Compiler .

Proceedings, Magnus Egerstedt and Bud Mishra (eds.), HSCC, 72-86, April, 2008.Abstract
We study the controller synthesis problem under budget constraints.


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Optimal controller synthesis is a challenging problem to solve. However, in many applications such as robotics, nonlinearity is unavoidable. Apart from optimality, correctness of the system behaviors with respect to system specifications such as stability and obstacle avoidance is vital for engineering applications. Many existing techniques consider either the optimality or the correctness of system behavior. Rarely, a tool exists that considers both. Furthermore, most existing optimal controller synthesis techniques are not scalable because they either require ad-hoc design or they suffer from the curse of dimensionality.

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In addition to studying synthesisunder a fixed budget constraint, we study the budget optimizationproblem, where given a plant, an objective, and observation costs,we have to find a controller that achieves the objective with minimalaverage accumulated cost (or minimal peak cost).

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Modern control is implemented with digital microcontrollers, which are designed to work in an embedded environment, within a dynamical plant that represents physical components. We present a new algorithm based on counterexample guided inductive synthesis that automates the design of digital controllers that are correct by construction. The synthesis result is sound with respect to the complete range of approximations, including time discretization, quantization effects, and finite-precision arithmetic and their related rounding errors. We have implemented our new algorithm in a tool called DSSynth, and are able to automatically generate stable controllers for a set of intricate plant models taken from the literature within minutes.

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In this paper, we identify a fragment of second-order logic with restricted quantification that is expressive enough to capture numerous static analysis problems (e.g. safety proving, bug finding, termination and non-termination proving, superoptimisation). We call this fragment the synthesis fragment. Satisfiability of a formula in the synthesis fragment is decidable over finite domains; specifically the decision problem is NEXPTIME-complete. If a formula in this fragment is satisfiable, a solution consists of a satisfying assignment from the second order variables to functions over finite domains. To concretely find these solutions, we synthesise programs that compute the functions. Our program synthesis algorithm is complete for finite state programs, i.e. every function over finite domains is computed by some program that we can synthesise. We can therefore use our synthesiser as a decision procedure for the synthesis fragment of second-order logic, which in turn allows us to use it as a powerful backend for many program analysis tasks. To show the tractability of our approach, we evaluate the program synthesiser on several static analysis problems.