This paper discusses the problem of selecting a set of sensors of minimum cardinality that can be used for the synthesis of a supervisory controller. We show how this sensor selection problem is related to a type of d...
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This paper discusses the problem of selecting a set of sensors of minimum cardinality that can be used for the synthesis of a supervisory controller. We show how this sensor selection problem is related to a type of directed graph st -cut problem that has not been previously discussed in the literature. Approximation algorithms to solve the sensor selection problem can be used to solve the graph cut problem and vice-versa. Polynomial time algorithms to find good approximate solutions to either problem most likely do not exist (under certain complexity assumptions), but a time efficient approximation algorithm is shown that solves a special case of these problems.
A forward reasoning procedure is developed based on the Bode gain-phase relationship and the concept of ideal loop shaping to achieve the goal that consistence of various design requirements can eventually be examined...
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A forward reasoning procedure is developed based on the Bode gain-phase relationship and the concept of ideal loop shaping to achieve the goal that consistence of various design requirements can eventually be examined and adapted completely by an expert system. In addition, a two-step design procedure is proposed to enhance the strength of the reasoning procedure. It can assist a designer not only in performing a design, but also in handling conflicting design requirements and formulating an achievable specification. Moreover, the designer reserves all freedom in trade-off and selecting the structure of a controller.
Two multi-objective genetic algorithms, an elitist version of MOGA and NSGA-II, were applied to solve two linear controldesign problems. The first was a H 2 problem with a PI controller structure, for a first order s...
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Two multi-objective genetic algorithms, an elitist version of MOGA and NSGA-II, were applied to solve two linear controldesign problems. The first was a H 2 problem with a PI controller structure, for a first order stable plant. The second was a mixed H 2 /H ∞ control problem. In both cases, three indicators were used to evaluate each algorithm performance: Set coverage, spread and hypervolume. It was found that NSGA-II shows better performance indicators. Moreover, for the second problem, a new controller representation was proposed with corresponding cross-over and mutation operators. This approach was able to find solutions as good as those previously published. The main advantage is that the stability restriction disappears, allowing to deal with an unconstrained optimization problem.
Multi-rate controllers are not simple to design but easy to implement in any simulation software. This paper presents a tool developed both for Matlab and Sysquake which helps tuning, testing and study multi-rate PID ...
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Multi-rate controllers are not simple to design but easy to implement in any simulation software. This paper presents a tool developed both for Matlab and Sysquake which helps tuning, testing and study multi-rate PID controllers both in the frequency domain an in the time domain.
This paper proposes a design procedure for H ∞ optimal linear feedback controllers for trajectory tracking of an automated guided vehicle (AGV) based on a linearized kinematic model. The design specifications are exp...
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This paper proposes a design procedure for H ∞ optimal linear feedback controllers for trajectory tracking of an automated guided vehicle (AGV) based on a linearized kinematic model. The design specifications are expressed as a constrained H ∞ norm optimization problem to assess the potential of the H ∞ framework for the considered application. This problem is then solved for a linear parameter-varying (LPV), a full-block and a decoupled linear time-invariant (LTI) controller. The performance of all controllers is compared through numerical simulations and experiments on an AGV prototype targeted at agricultural applications.
This paper briefly presents ATOL, which is a tool developed at Snecma Moteurs for jet engine controller design. ATOL could be considered as an interfacing tool with many identification and design algorithms. ATOL is a...
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This paper briefly presents ATOL, which is a tool developed at Snecma Moteurs for jet engine controller design. ATOL could be considered as an interfacing tool with many identification and design algorithms. ATOL is able to make advanced synthesis of controllers, such as LPV H ∞ synthesis by solving LMIs. ATOL can also designcontrollers by using a traditional pole placement technique.
The paper deals with the usage of a BORIS control and simulation environment for the identification and control of a real-time laboratory model. Identification and control experiments were performed using Gas Flow Con...
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The paper deals with the usage of a BORIS control and simulation environment for the identification and control of a real-time laboratory model. Identification and control experiments were performed using Gas Flow control model by Leybold. This model is a part of a Real-time Models Laboratory at Tomas Bata University in Zlin. The aim of this paper is to introduce an experiment performed using the BORIS environment and explore usability of this environment for the real-time control. Interoperability and comparison with the well-known MATLAB/Simulink environment is also discussed.
Complex dynamic systems can be simulated using ANSYS®(ANSYS, Inc., Canonsburg, PA, USA) but for controller design Simulink®(MathWorks, Inc., Natick, MA, USA) is the appropriate software tool. The MATLAB®...
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Complex dynamic systems can be simulated using ANSYS®(ANSYS, Inc., Canonsburg, PA, USA) but for controller design Simulink®(MathWorks, Inc., Natick, MA, USA) is the appropriate software tool. The MATLAB®(MathWorks, Inc., Natick, MA, USA) program makeStateSpace , which is introduced in this paper, transfers the results of ANSYS modal analysis into a modal state space formulation that can then be included in Simulink. A model order reduction to diminish the system size is also possible. Hence, with the help of makeStateSpace the advantages of both powerful software tools ANSYS and Simulink can be used for controller design.
Mapping is the off-line allocation of the tasks that represent a parallelised algorithm across a multiprocessor architecture. In this paper the target architecture is heterogeneous, where a number of computationaly di...
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Mapping is the off-line allocation of the tasks that represent a parallelised algorithm across a multiprocessor architecture. In this paper the target architecture is heterogeneous, where a number of computationaly disparate processors are integrated within a single network. This paper describes three mapping approaches that attempt to minimise the cycle time of several parallelised algorithms. The mapping algorithms have been embedded into a suite of design tools that allow a rapid translation from an application algorithm to a parallel implementation. These tools are used to explore the efficacy of the mapping algorithms. A simple heuristic is appraised first, followed by an examination of a genetic algorithm (GA) approach. Initially, the GA utilises a simple parallel architecture model. However, this leads to the embedding of the target hardware within the objective function to improve performance. Finally, the effectiveness of these approaches are examined and contrasted.
The multivariable control that was designed for the primary grinding in the Vuonos concentrator can control important variables like the final particle size and the density of the cyclone feed. The controller was desi...
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The multivariable control that was designed for the primary grinding in the Vuonos concentrator can control important variables like the final particle size and the density of the cyclone feed. The controller was designed for the plant using an interactive CACSD-software package which included the use of the inverse Nyquist array method. The control algorithms designed were implemented in the controlcomputer in Vuonos and there was good agreement between the simulated results and the full scale tests: Changes of the setpoint of either one controlled output variable produced satisfactory responses, while the other controlled output simultaneously remained close to the desired constant value. The multivariable controller designed has been taken into continuous use in Vuonos. Autocovariance and spectral density functions have been calculated in order to analyse the behaviour of the final particle size and the density of the cyclone feed. According to the results obtained in the design by the inverse Nyquist array method and the experiments at the Vuonos Mill, this technique is suitable for the design of multivariable control of grinding. A practical advantage of this design technique is the simplicity of the final controller and the use of standard control algorithms.
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