This article presents an algorithm to integrate the passive and active control for automotive suspension systems. The objective of the algorithm is to simultaneously find: 1) the optimal values of the stiffness and da...
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This article presents an algorithm to integrate the passive and active control for automotive suspension systems. The objective of the algorithm is to simultaneously find: 1) the optimal values of the stiffness and damping ratios for the springs and dampers; and 2) an optimal stabilizing controller such that the active control energy is minimized subject to the prespecified RMS constraints on the outputs and the constraints on the stiffness and damping ratios. The algorithm is given in the linear matrix inequality form, and the convergence is guaranteed.
Coach active suspension systemdesign must meet requirements for comfort and safety, and technical requirements. A hydropneumatic system was taken to be the most appropriate spring system. In a hydropneumatic strut, s...
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Coach active suspension systemdesign must meet requirements for comfort and safety, and technical requirements. A hydropneumatic system was taken to be the most appropriate spring system. In a hydropneumatic strut, spring and damper elements are replaced by hydraulic ones, the flat spiral spring being replaced by a hydraulic accumulator and an actuator with the damper being replaced by a throttle and an actuator. The stabilizer is abolished altogether. After the statical properties were established a dynamical model of the entire coach, including active components, was made up helping to verify further dynamical loads and demands relating to control engineering. The article describes the design process.
The paper describes an oleo-pneumatic active suspension which has been developed using a linear multivariable controller. In order to optimise the performance of the system it has been necessary to address the nonline...
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The paper describes an oleo-pneumatic active suspension which has been developed using a linear multivariable controller. In order to optimise the performance of the system it has been necessary to address the nonlinearities of the system, such as those inherent in the gas spring, bump and rebound stops, dampers and flow control valves. A description is given of the nonlinearities and effects encountered under changing load, manoeuvre and ride inputs. Results are presented which demonstrate the benefits of using a nonlinear controller model within an adaptive control scheme.
In the design of mechatronic systems the predefined functionality is generally reached by a coupling of elements from mechanics, hydraulics, and electrical engineering, combined with information processing. This leads...
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In the design of mechatronic systems the predefined functionality is generally reached by a coupling of elements from mechanics, hydraulics, and electrical engineering, combined with information processing. This leads to complex and extremely heterogeneous systems based on the most diverse physical principles. One of the problems with the design of mechatronic systems is the variety of the models need to be studied. To solve it the present approach introduces two conceptions of object-orientation, namely inheritance and polymorphism, into the model description language Objective-DSS and make them available to the user. The resulting advantages are exemplified by an application in vehicle dynamics.
This paper deals with the implementation problems of a digital computer for a well designed linear continuous-time variable structure controlsystem. An upper bound of the sampling period is given by some calculations...
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This paper deals with the implementation problems of a digital computer for a well designed linear continuous-time variable structure controlsystem. An upper bound of the sampling period is given by some calculations. If the chosen sampling period is smaller than this upper bound the zero-order-hold of the VSS controller designed in a continuous-time system can still be used without any modification to stabilize its sampling data system. The so-called discrete-time weak-pseudo-sliding mode will take place along a prescribed sliding hyperplane. Simulation results are presented to show the effectiveness of the decision of the upper bound.
A hidden Markov model toolbox is presented within the Scilab environment. In this toolbox popular methods for the resolution of HMM problems are incorporated. These methods cover the training and recognition phases. M...
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A hidden Markov model toolbox is presented within the Scilab environment. In this toolbox popular methods for the resolution of HMM problems are incorporated. These methods cover the training and recognition phases. Models may be used with discret and continuous observations. This toolbox includes conventional methods as well as extensions.
The paper discusses the measurement of a controller robustness for given uncertainties in plant parameters for an LTI and SISO model. Robustness is calculated according to some regions of z-plane or s-plane where the ...
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The paper discusses the measurement of a controller robustness for given uncertainties in plant parameters for an LTI and SISO model. Robustness is calculated according to some regions of z-plane or s-plane where the closed-loop system poles must be delimited. The method employs a geometric representation of the uncertainty space in the system parameters and is based on algebraic relationships characteristic of R/sup N/ vector spaces; thus, a calculation environment like MatLab is very suitable for its implementation.
In this paper we present a method of planning control strategies for assembly systems with complex material flows. In order to be able to make available components just-in-time in-sequence, the sequence of components ...
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In this paper we present a method of planning control strategies for assembly systems with complex material flows. In order to be able to make available components just-in-time in-sequence, the sequence of components in the different material flows has to be coordinated. Local control strategies describe how this can be reached at a place of location by means of sorting buffers. Global control strategies express how local control strategies can be combined optimally. The effect of control strategies on the operating performance of complex assembly systems can only be determined by means of a computeraided simulation. For the elements behavioural regulations are prescribed which are appropriate to execute the required control measures. The regulations are expressed as a set of rules constructed by use of elements known from predicate calculus.
Even though it is possible to simulate mixed discrete continuous (hybrid) dynamics systems in scientific environments such as Matlab and Scilab using ordinary differential equation solvers, implementing the discrete r...
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Even though it is possible to simulate mixed discrete continuous (hybrid) dynamics systems in scientific environments such as Matlab and Scilab using ordinary differential equation solvers, implementing the discrete recursions and the logic for interfacing the discrete and the continuous parts usually requires a great deal of programming. These programs are often complex, difficult to debug and slow. Scicos is a Scilab package that provides an easy to use graphical editor for building complex models of hybrid systems, a compiler which converts the graphical description into Scicos executable code, and a simulator for simulating Scicos executable codes. This paper describes briefly some of Scicos's features.
This paper presents two nonlinear examples of mechanical systems. The first example is a simple inverted pendulum, the second example is a simplified bicycle model. In Maple, using the Euler Lagrange equations, we com...
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This paper presents two nonlinear examples of mechanical systems. The first example is a simple inverted pendulum, the second example is a simplified bicycle model. In Maple, using the Euler Lagrange equations, we compute the equations of motion. We have shown how to use the interface to transfer the equations to Scilab for simulation or control. We have shown that for dealing with complex models, we need the full power of Maple to perform change of variables which cannot be automatized since they require a deep a priori knowledge of the model.
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