the contribution addresses the problem of robust trajectory tracking control and disturbance rejection for a non contact, high-precision Lorentz force planar motion stage of linear DC brushless type. the control probl...
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the contribution addresses the problem of robust trajectory tracking control and disturbance rejection for a non contact, high-precision Lorentz force planar motion stage of linear DC brushless type. the control problem is accomplished by using a composite control law including a simple computed torque type controller together with an extended Luenberger type of state and disturbance observer also known as extended state or generalized proportional integral observer (GESO/GPIO). We provide stability proofs and estimation error bounds of the GESO/GPIO related to the choice of the eigenvalues of the observer estimation error dynamics. Finally, we assess the performance of the proposed controller on the basis of a recently developed motion stage model that comprises a realistic disturbance modeling and thus is capable of reflecting the major challenges for control.
this paper describes the control aspects and results of a student project called “MonoChair”. the goal was to have students walk through a complete control systems development cycle. the focus in this contribution i...
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this paper describes the control aspects and results of a student project called “MonoChair”. the goal was to have students walk through a complete control systems development cycle. the focus in this contribution is put on the design of a stabilizing linear controller, a sensitivity analysis in order to study the impact of parameter variations, and the design and test of an adaptive controller using a model reference approach. the linear controller has been implemented on the physical system and has extensively been tested in driving experiments. the adaptive controller has been tested in simulations and implemented on the physical plant as well. Initial experimental results are presented. A video showing the performance withthe nominal linear controller can be found on [1].
this elaboration presents the numerical model of the Active Magnetic Levitation (AML). the model is developed in the 2D axis symmetry mode. the Finite Element Method is used to calculate the magnetic field. the Ordina...
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this elaboration presents the numerical model of the Active Magnetic Levitation (AML). the model is developed in the 2D axis symmetry mode. the Finite Element Method is used to calculate the magnetic field. the Ordinary Differential Equation is solved simultaneously to simulate the levitated object motion. the model is solved in the time domain, together withthe levitated object motion being simulated. A few investigation simulations are realized to diagnose the basic properties of the model. the PID current mode controller is used to drive the coil and keep the object levitated in the desired position. the electromagnetic force and magnetic flux density are investigated to analyze the AML non-linearities. Finally, the conclusions towards the experimental research are given.
In the paper an adaptive Linear-Quadratic (LQR) control system for Multi-Input, Multi-Output (MIMO) nonlinear dynamic plants is presented. A nonlinear four-Degrees-of-Freedom (4-DoF) mathematical model of a singlescre...
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In the paper an adaptive Linear-Quadratic (LQR) control system for Multi-Input, Multi-Output (MIMO) nonlinear dynamic plants is presented. A nonlinear four-Degrees-of-Freedom (4-DoF) mathematical model of a singlescrew, high-speed container vessel is used as a MIMO plant. the main task of the proposed system is control the course angle and forward speed of the ship according to the changing hydrodynamic operating conditions. Due to the strongly nonlinear nature of the equations of the ship motions adaptive LQR controller is tuned according to the current operating point of the ship. the system synthesis is carried out by linearization of the nonlinear model of the ship at its nominal operating points in the steady-state. the final part of the paper includes results of simulation tests of the proposed control system carried out in the MATLAB/Simulink environment.
the paper presents an application of LQ control dedicated to a semiactive quarter-car model (2 degrees of freedom) which includes nonlinear model of a magnetorheological (MR) damper. Optimal control gains are derived ...
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the paper presents an application of LQ control dedicated to a semiactive quarter-car model (2 degrees of freedom) which includes nonlinear model of a magnetorheological (MR) damper. Optimal control gains are derived based on known quarter car model parameters and limitations imposed on absolute vertical velocities of sprung and unsprung masses as well as on desired force generated by MR damper. Solutions of the algebraic Riccati equation obtained for LQ continous time infinite horizon problem using system output and control weights matrices are approximated using neural network. the static feedforward neural network model was identified using Levenberg-Marquardt backpropagation method in order to map nonlinear relations between system variables limitations and control gains. the algorithm was adapted to the semiactive system using a linearized inverse MR damper model. Simulation based analysis of vibration mitigation was carried out in frequency domain for different experiments conditions; the analysis justifies application of neural networks in LQ based control of semiactive suspension.
the Fuzzy-neural development system is presented in two versions. the First version is the implementation in C, C++ with interface to Matlab or other programs using DLL calling. the second implementation is newer, con...
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the Fuzzy-neural development system is presented in two versions. the First version is the implementation in C, C++ with interface to Matlab or other programs using DLL calling. the second implementation is newer, conform to Referential transparency. For implementation we choose functional programming language Scheme. the Scheme version R5RS is adopted on different platforms like PC, microprocessors and FPGAs. this allows easy transfer of Scheme code on mentioned platforms. there is presented short programming example of Takagi Sugeno Kang fuzzy rule based model in form of the Fuzzy Neural Network. the possible applicatons of the proposed development system are presented.
this contribution introduces three sensorless vibration suppression methods for flexible, fast moving linear robots. After some investigations concerning the required mathematical models of the flexible linear robot, ...
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the prototyping process of a fuzzy logic-based anti-sway control scheme for the laboratory scaled overhead crane is described. the software-hardware equipment of control system, as well as the contact and contactless ...
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the prototyping process of a fuzzy logic-based anti-sway control scheme for the laboratory scaled overhead crane is described. the software-hardware equipment of control system, as well as the contact and contactless techniques of sway angle of a payload sensing which have been implemented on the laboratory stand are presented. Proposed anti-sway control system is based on a set of the linear controllers determined at the selected operating points using a pole placement method (PPM) and the fuzzy interpolation of controllers parameters within the range of scheduling variables: rope length and mass of a payload. the control algorithm, a linear dynamic model of a planar crane, as well as the fuzzy schedulers of controllers and model's parameters were implemented using structured text (ST) on the PAC system with RX3i controller. the softwarehardware tools allows to automate the crane's models identifications for the selected operating points, determine the controllers parameters, validate the closed-loop system through real-time simulating on the PAC system and finally pass to conducting the experiments on the laboratory device.
the estimation of non-measurable state variables as well as the reliable identification of unknown system parameters are important prerequisites for the design and implementation of controllers for nonlinear dynamic s...
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the estimation of non-measurable state variables as well as the reliable identification of unknown system parameters are important prerequisites for the design and implementation of controllers for nonlinear dynamic systems. However, these tasks are often impeded by the nonlinearity of dynamic system models as soon as observer techniques are sought for, which can be used for large operating ranges. Moreover, parameters and measured data are typically only known within given tolerance bounds. Such uncertainty makes the proof of the asymptotic stability of the error dynamics of classical state observers quite difficult. therefore, a novel interval-based sliding mode observer providing point-valued estimates is presented in this paper which is designed in such a way that asymptotic stability can be guaranteed by means of an online evaluation of a suitable Lyapunov function. Furthermore, an efficient strategy for the adaptation of the switching amplitude of the observer's variable structure part is presented to reduce the amplification of measurement noise as far as possible if time-varying state variables and time-invariant system parameters are estimated simultaneously. An illustrative example, describing the longitudinal dynamics of a vehicle, is presented to highlight the practical applicability of the observer.
this paper studies the linearization and control design for a class of Affine Nonlinear Parameter Varying (ANPV) systems. In advance, a kind of Takagi-Sugeno (T-S) fuzzy modeling procedure with homogeneous consequent ...
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this paper studies the linearization and control design for a class of Affine Nonlinear Parameter Varying (ANPV) systems. In advance, a kind of Takagi-Sugeno (T-S) fuzzy modeling procedure with homogeneous consequent part based on the ANPV system is proposed to deal withthe nonlinearity and the LPV T-S fuzzy system is obtained. then, taking the LPV T-S fuzzy system as the control design model, the piecewise parameter-dependent Lyapunov function is introduced for the LPV T-S fuzzy gain scheduling control. Especially, the statefeedback H ∞ control design of the LPV T-S fuzzy system is studied and the sufficient conditions are given in LMIs form. Finally, a numerical example is provided to validate the availability of the approaches. the simulation results show the universal approximation ability of the LPV T-S fuzzy system to the nonlinearity and the effectiveness of the LPV T-S fuzzy gain scheduling control.
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