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In this paper, a new methodology for feed forward-feedback control system design is proposed. Initially, the concept of control equilibrium point is introduced. Using this concept, the steady state control command is determined so as to maintain the desired situation of the system. Non-model-based feed forward control law is conducted on this basis using an artificial neural network. The feedback...
In this paper, a general design approach based on the concept of `Control Equilibrium Point' is proposed to derive the feedforward control law in feedback-feedforward control systems. The feedback controller generates the transient control command and the feedforward controller generates the steady state command. In order to reduce the reliance on the mathematical model of the system, an artificial...
In this paper, a general design approach is proposed to derive the feedforward control law in feedback-feedforward control systems. This design approach is based on the concept of `control equilibrium point'. In this design approach, the feedback controller generates the transient control command and the feedforward controller generates the steady state one. Using the proposed feedforward controller,...
In this paper, a design approach is proposed for feedforward-feedback control systems. As the basis of the proposed design approach, steady state control command is defined as the control command which maintains the desired situation of the system. Steady state control law is derived form system's mathematical model and employed as feedforward controller. Using such a feedforward controller, for a...
In this paper, intelligent control of the outlet flow concentration of a non-thermic catalytic continuous stirred tank reactor (CSTR) is addressed. Control command is the sum of two control commands: steady state and transient commands. A fuzzy controller generates transient control command pushing the system towards the reference (desired situation). Steady state control command is generated to maintain...
In this research, double-command control of a nonlinear chemical system is addressed. The system includes a stirred tank; two flows of liquid with different concentrations are entering the system through two valves and another flow is exiting the tank with a concentration between two input concentrations. The outlet concentration is usually regulated by the control of one of the valves and the flow...
A multi-degree-of-freedom (MDOF) distributed active shock absorber (DASA) for shock vibration suppression in flexible structures is investigated in this paper. The DASA is a simple first-order controller that is designed based on the modal positive position feedback strategy to suppress transient vibrations of flexible structures at various harmonics. The DASA can be constructed by using piezoceramic...
A new control property namely ldquocontrol inertiardquo is introduced in this article. In this research, control techniques not needing a mathematical model of the system are subject to study. Neuro-predictive (NP) method is a non-model based technique works for a wide variety of nonlinear systems, and lets us compare different systemspsila behaviour. In this paper, two different nonlinear systems,...
In this paper, the pitch angle control for a lab model helicopter is discussed. This problem has some specific features. As a main unusual feature, it is observed that the steady state control command is completely dependent on the setpoint, so error-based controllers do not suit this problem. Moreover, the system is of a highly oscillating dynamic. In order to solve this control problem, two controllers...
In this research, the fuzzy control of the yaw angle of a model helicopter is studied, particularly, in order to reduce the overshoot which can be a serious problem in high inertia systems. Initially, a Sugeno-type controller is designed. This controller provides quick convergence and keeps the control input in a permitted range .Moreover, a good stability is offered by this fuzzy controller. But,...
In this paper a new control method based on a combination of inverse dynamics method and neuro-fuzzy inference systems is developed for a nonlinear industrial plant. The method is applied to a super-heater system of a steam power generating plant. The controller's performance is compared with that of the existing PID feedback control system. A neuro-fuzzy model of this nonlinear plant is also developed...
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