In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one o...
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In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one output (command rudder angle). The track-keeping problem is decomposed into two subtasks: (i) followthe desired heading, and (ii) bring the ship onto the desired path and keep tracking. Internally, the autopilot consists of two autopilots that fulfil these tasks simultaneously. The proposed control scheme has been verified using a non-linear model of a Mariner-class vessel and steering mechanism under the influence of wave and current disturbances. Results presented show how such a control strategy enables improved tracking performance.
Disturbance rejection performance is usually the most important aspect in designing controller in the process and the chemical industries. On the other hand, such tuned control loop may exhibit large overshoots on ref...
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Disturbance rejection performance is usually the most important aspect in designing controller in the process and the chemical industries. On the other hand, such tuned control loop may exhibit large overshoots on reference tracking. The only way to decrease overshoot is to use two-degrees-of-freedom (2-DOF) controllers. Unfortunately, reducing the overshoot usually results in slower tracking response when using some of the most common 2-DOF controller structures. This paper suggests using additional first-order filter on the set-point of the PI controller in order to improve tracking performance. The calculation of compensator's parameters is straightforward and can be easily performed in practice. Several examples confirmed the efficiency of the proposed approach.
This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then prov...
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This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system. These predictions are used by the fuzzy controller, in order to accomplish a better control of an alcoholic fermentation process from chemical industry. This problem has been chosen due to its non-linearity and large accommodation time, that make it hard to control by standard controllers. Comparison of performance is made with non-predictive approaches(PID and Fuzzy-PD), and also with another predictive approach, GPC(Generalized Predictive control).
This paper describes the principles of an intelligent automaton for controlling the secondary stage of a wastewater treatment plant. The automaton has been implemented as a finite state machine that can be integrated ...
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This paper describes the principles of an intelligent automaton for controlling the secondary stage of a wastewater treatment plant. The automaton has been implemented as a finite state machine that can be integrated into the existing supervisory control and data acquisition system of any wastewater treatment plant. Human knowledge, in the form of linguistic rules, is embedded in the automaton, which has been shown to be capable of controlling the process very satisfactorily in all but extreme conditions.
The problems of 2 analysis and control synthesis for linear continuous-time parameter-dependent systems are addressed. The admissible values of the parameters and their rates of variation are assumed to belong to a gi...
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The problems of 2 analysis and control synthesis for linear continuous-time parameter-dependent systems are addressed. The admissible values of the parameters and their rates of variation are assumed to belong to a given polytope. Linear matrix inequality-based methods of 2 performance analysis and state feedback control are developed. Both the design of gain-scheduled and robust controllers are addressed. The proposed methods have the feature that stability as well as the guaranteed 2 performance cost are based on a parameter-dependent Lyapunov function which is quadratic on the system parameters. The controller implementation does not require online knowledge of the rate of variation of the parameters.
In this paper, we propose a deterministic approach to the robust filtering problem for a class of uncertain nonlinear systems. Based on polynomial Lyapunov functions and a relaxation technique, we derive linear matrix...
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ISBN:
(纸本)0972184449
In this paper, we propose a deterministic approach to the robust filtering problem for a class of uncertain nonlinear systems. Based on polynomial Lyapunov functions and a relaxation technique, we derive linear matrix inequalities conditions that minimize an upper-bound on the finite horizon 2-norm of the estimation error for all admissible uncertainty and input signals (including disturbances and measurement noise). Through a simple redefinition of the Lyapunov matrix, we extended the results for the reduced-order case without considering non-convex rank constraints.
A controlsystemsengineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detai...
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A controlsystemsengineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detail. One design alternative is based on employing fuzzy-system approximators and solving for the adaptive tracking of the given, arbitrary, desired system outputs. The other alternative is based on state equations of composite systems and the use of neural-network approximators to deal with uncertainties and control adaptation. In both alternatives similarity property of subsystems has been exploited. Both designs can be implemented within the standard computer process control technology, and are therefore believed to be promising in applied systemsengineering.
This paper deals with the linear ∞ filtering problem for a class of regionally stable uncertain nonlinear systems subject to bounded disturbances and measurement noises. The nonlinear systems is represented by differ...
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This paper deals with the linear ∞ filtering problem for a class of regionally stable uncertain nonlinear systems subject to bounded disturbances and measurement noises. The nonlinear systems is represented by differential-algebraic equations where the system matrices are allowed to be rational functions of the state and uncertain parameters. For this class of systems, LMI conditions are proposed for ensuring a prescribed upper-bound on the L2-gain of the input-to-estimation error operator for a given linear asymptotically stable filter. The result is based on polynomial Lyapunov functions. Then, using an appropriate parameterization of the Lyapunov function we extend the analysis result for designing linear filters in a ∞ sense via a convex optimization problem.
In this paper, an active fault tolerant control (FTC) strategy is presented for linear dynamic systems. The robust observer-based fault detection and isolation (FDI) systems are applied to guide the reconfiguration of...
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