Algorithms in Engineering Control Systems

explanatory Essay
1120 words
1120 words

Increasing requirements for design of system with increased fault tolerance is the current trend in design of control systems. Since the majority of real control systems are non- linear, algorithms dealing with a class of non-linear systems use the approach of Takagi-Sugeno fuzzy models. These algorithms deals with fault diagnosis, reconfiguration of the system and solve problems related to the constraints of the system and the time delay that occurs in complex control systems. All real systems in nature, such as physical, biological and engineering systems, are susceptible to defects of its compo- nents. Therefore the basic requirement in industrial automation is the reliability of the systems. In the technical automatic control systems, faults may occur in sensors, actuators or com- ponents of the systems. Effective way to ensure the reliability of the systems is to use a fault tolerant control (FTC). Its task is to avoid the expansion of the local faults into the system failure under which system may discontinue activity and jeopardize the safety of the whole system for personnel and environment. The main task of the FTC’s proposal is therefore to design a system that works reliably in dynamic and steady state not only for nominal operation, but also in case of fault, so that the system is able to return to its original condition before the fault occurrence. Fault tolerance is achieved on the basis of the so-called functional (analytical, inherent, custom) redundancy, which unlike physical redundancy (redundancy by technical means) uses the redundancy inherent in dynamic or static dependencies of technological parameters (variables mutually bound by technological process). Fault tolerant control systems and related control pr... ... middle of paper ... ... pp. 330–333. [5] A. Filasová, D. Krokavec, and V. Serbák, “Control reconfiguration for one class of takagi-sugeno fuzzy siso systems,” in Advances in Intelligent Systems and Computing : Intelligent Systems in Technical and Medical Diagnostics, vol. 230. Berlin Heidelberg : Springer, 2014, pp. 53–64. [6] T. Kailath, “Linear systems.” Prentice-Hall Englewood Cliffs, 1980. [7] D. Krokavec and A. Filasová, “Dynamic systems diagnosis.” Elfa, Košice Slovakia, 2006. [8] Y. Kouhi and N. Bajcinca, “Nonsmooth control design for stabilizing switched linear systems by left eigenstructure assignment,” in Prepr. 18th IFAC World Congress. Milano, Italy, 2011, pp. 380––385. [9] D. Krokavec and A. Filasová, “Novel fault detection criteria based on linear quadratic control performances,” in International Journal of Applied Mathematics and Computer Science, vol. 22, 2012, pp. 929–938.

In this essay, the author

  • Explains that takagi-sugeno fuzzy models are used to deal with non-linear system fault diagnosis, reconfiguration, and solve problems related to the constraints of the system.
  • Explains the basic requirement in industrial automation is the reliability of the systems. in the technical automaticcontrol systems, faults may occur in sensors, actuators or com-ponents.
  • Explains that the ftc's proposal is to design a system that works reliably in dynamic and steady state not only for nominal operation, but also in case of fault.
  • Explains fault tolerance is achieved on the basis of theso-called functional (analytical, inherent, custom) redundancy.
  • Explains the wide and diverse technical applications encountered by forexample in the security of critical systems such as helicopters, airplane, cars, spacecraft, nuclear power plants, or chemical plants.
  • Explains that the nominal controller has been designed, tuned and tested in order to satisfy therequired specifications for the system and still can be used without any changes.
  • Explains that vac was extended to include the integral component whose task was to eliminaterespectively minimize permanent regulatory deviation, and it increased the efficiency of reconfigurations using virtualactuators.
  • Describes control techniques with state constraints defined by linearmatrix (in)equalities, where a single sensor fault is described by an equality constraint given on the state variable associated with the faulty sensor.
  • Describes the reconfiguration method described in inteligent systems in technical and medical diag-nostics in chapter control reconfiguration for takagi-sugeno fuzzy siso systems.
  • Explains how algebraic methods are used to handle the common lefteigenvector in the state feedback control of a constituent set of closed-loop system matrices.
  • Explains that the closed loopsystem matrix a uc represents necessary condition for control law parameterdesign and provides a methodology usable in stabilizing theconstituents if the state-feedback control is used.
  • Explains that siso system classes are shackled with the same set of member-ship functions, i.e., the l-th constituent is where q(t) i r n is the vector of state variables.
  • Explains that to obtain a stable switching fuzzy system, the collection of matrices a has to be hurwitz.
  • Explains that the paper fault detection based on linear quadratic control in nonlinear systems will be presented at intenational carpathian control conference 2014.
  • Explains takagi-sugeno fuzzy model, which utilizes evaluation of equivalent approximated lq control performance index.
  • Explains that arbitrary approach resulting in static fuzzyoutput control law provides approximated performance index for applied control.
  • Explains that the following research task is design of reconfigurationmethod based on vac for systems with constraints.
  • Explains that the reconfiguration algorithm modified for a class of nonlinear systems using approaches with ts fuzzy models is among other tasks planned for the following period of time.
  • Cites works by p. m. frank, a. filasová, and v. serbák on fuzzy based virtual actuators for nonlinear systems.
  • Cites p. li cinsk and v. serbák, "control of discrete-time linear systemsconstrained in output by equality constraints," in iccc 2013.
  • Cites a. filasová, d. krokavec, and v. serbák in advances in intelligentsystems and computing : intelligent systems in technical and medicaldiagnostics, vol.
  • Cites y. kouhi and n. bajcinca's paper, "nonsmooth control design for stabilizingswitched linear systems by left eigenstructure assignment."
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