This paper presents a new strategy for robust dynamic output-feedback control synthesis for uncertain discrete-time linear time-invariant systems represented by polytopic models. It is proposed a multiobjective optimi...
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This paper presents a new strategy for robust dynamic output-feedback control synthesis for uncertain discrete-time linear time-invariant systems represented by polytopic models. It is proposed a multiobjective optimization problem to guarantee tracking response specifications, disturbance rejection, and noise attenuation. The novelty is to consider as an additional objective function the minimization of the H ∞ -norm of the error between the closed-loop transfer function from the reference signal to the controlled output and a reference model to attain the tracking response specifications. It is applied a two step iterative procedure to solve the bilinear matrix inequality problem. A numeric example is presented to illustrate the effectiveness of combining the closed-loop reference model together with other control objectives.
μ-analysis has for many years been the de facto standard robustness analysis tool in a wide variety of control applications. To use μ-analysis, the uncertain system must be cast in the form of a linear fractional tr...
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μ-analysis has for many years been the de facto standard robustness analysis tool in a wide variety of control applications. To use μ-analysis, the uncertain system must be cast in the form of a linear fractional transformation (LFT). Once it is appropriately transformed, a variety of algorithms are available to calculate the upper and the lower bounds on μ. Several difficulties arise during this process. Firstly, the uncertainties in the system must appear as polynomial fractions - if they do not, then some approximation steps must be applied in order to write the system as an LFT. Secondly, symbolic manipulations are required in general in order to obtain linear fractional transformation automatically. Finally, for problems involving real parametric uncertainties calculating the lower bound is a well known NP(Non-deterministic Polynomialtime)-hard problem. Therefore, there will always be some conservatism introduced in the bound or else the computation time will increase exponentially with the number of uncertain parameters. We present an efficient algorithm to overcome these issues by combining a randomisation approach and a geometric interpretation of the robustness analysis problem. The uncertainty is re-defined by a subtraction between the uncertain system and the nominal system. Thus the procedure does not require that the uncertain parameters are actually decoupled from the system (as with LFT's) but only requires the evaluation of the difference between the nominal system and the perturbed system. Here, we illustrate the application of the proposed approach to the robustness analysis of uncertain linear periodically time-varying systems, and in particular to magnetic torquer controlled spacecraft attitude dynamics.
The demand for visualizing schedule management information of construction work, which used to be comprised of numerical data is increasing by the web application and virtual reality (VR) technology. Web application w...
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The nonlinear dynamical behavior of the crassulacean acid metabolism is discussed from the control theoretical viewpoint. The state-variables of the nonlinear dynamic equations are an internal CO 2 concentration, a m...
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The nonlinear dynamical behavior of the crassulacean acid metabolism is discussed from the control theoretical viewpoint. The state-variables of the nonlinear dynamic equations are an internal CO 2 concentration, a malate concentration in the cytoplasm, a malate concentration in the vacuole, and an order of the tonoplast membrane. The input variables are an external CO 2 concentration, a light intensity and a temperature. We have recently presented a dynamic estimator of the tonoplast order and a fuzzy identifier of the nonlinear function in the dynamics of the tonoplast order. In this paper, we propose two types of the feedback controllers of the CAM model using the external CO 2 concentration and the light intensity as an input.
Using the Approximate Dynamic Programming (ADP) approach, nonlinear optimal control problems can be solved by using a dual neural network architecture called the Adaptive Critic (AC). A Single Network Adaptive Critic ...
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Using the Approximate Dynamic Programming (ADP) approach, nonlinear optimal control problems can be solved by using a dual neural network architecture called the Adaptive Critic (AC). A Single Network Adaptive Critic (SNAC) architecture has been shown to have much faster convergence than AC. Even though the SNAC offers a systematic optimal controldesign method for optimal state regulation for a class of nonlinear controlsystems, it lacks the generality necessary for command tracking as it is practically difficult to anticipate a proper training domain in state space when the command sequence is not known a priori. Dynamic Inversion (DI), on the other hand, is a very popular nonlinear controldesign method for both output regulation and command tracking that offers a closed form expression for control. However, it lacks the interpretation and advantages of optimal controldesign. In this paper we propose a systematic technique for selecting the DI gains with the help of a pre-synthesized SNAC network in order that the resulting DI solution closely mimics the SNAC solution for output regulation and can be extended to command tracking problems. Moreover, it retains all the benefits of DI design. The potential of this new methodology of near-optimal dynamic inversion design is demonstrated in this paper by considering a benchmark nonlinear system.
A sliding mode controller for uncertain systems is proposed in this paper. The class of system considered has matched and mismatched uncertainties. The design framework involves linear matrix inequality methods and po...
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This paper provides a summary of several recently detailed recursive, filtering strategies as applied to the task of tracking deformable objects from a video sequence. Estimation theory provides the foundation for fil...
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The main aim of this paper is to improve and further develop numerical iterative methods for calculating the optimum sequence of switching angles for the multilevel converter of direct to alternating voltage in the th...
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The performance of distributed controlsystems, apart from the sampling period, depends on many parameters, such as the control loop execution time, jitter and communication parameters of data transmission channels. L...
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This paper studies robust adaptive flocking control of multi-agent systems with nonlinear dynamics. In this setting, the coupling weights, perturbed by asymmetric uncertain parameters, are dynamically updated while th...
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