作者:
J.R. RiehlJ.P. HespanhaCenter for Control
Dynamical Systems and Computation Electrical and Computer Engineering Department University of California Santa Barbara CA USA
We introduce methods of hierarchically decomposing three types of graph optimization problems: all-pairs shortest path, all-pairs maximum flow,and search. Each method uses a partition on the graph to create a high lev...
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We introduce methods of hierarchically decomposing three types of graph optimization problems: all-pairs shortest path, all-pairs maximum flow,and search. Each method uses a partition on the graph to create a high level problem and several lower level problems. The computations on each level are identical, so the low level problems can be further decomposed. In this way, the problems become fractal in nature. We use these decomposition methods to establish upper and lower bounds on the optimal criteria of each problem, which can be achieved with much less computation than what is required to solve the original problem. Also, for each problem, we find an optimal number of partitions that minimizes computation time. As the number of hierarchical levels increases, the computational complexity decreases at the expense of looser bounds.
This paper is concerned with the derivation of the kinematics model of the University of Tehran-Pole Climbing Robot (UT-PCR). As the first step, an appropriate set of coordinates is selected and used to describe the s...
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This paper is concerned with the derivation of the kinematics model of the University of Tehran-Pole Climbing Robot (UT-PCR). As the first step, an appropriate set of coordinates is selected and used to describe the state of the robot. Nonholonomic constraints imposed by the wheels are then expressed as a set of differential equations. By describing these equations in terms of the state of the robot an underactuated driftless nonlinear control system with affine inputs that governs the motion of the robot is derived. A set of experimental results are also given to show the capability of the UT-PCR in climbing a stepped pole.
For a class of nonlinear systems affine in controls and with unknown high frequency gain, we develop a hybrid control strategy that guarantees (practical) global input-to-state stability (ISS) with respect to measurem...
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For a class of nonlinear systems affine in controls and with unknown high frequency gain, we develop a hybrid control strategy that guarantees (practical) global input-to-state stability (ISS) with respect to measurement noise. We provide a design procedure for the hybrid controller and apply it to Freeman’s counterexample and minimum-phase relative degree one systems.
The focus of this paper is on control design and simulation for an air-breathing hypersonic vehicle. The challenges for control design in this class of vehicles lie in the inherent coupling between the propulsion syst...
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In this paper, we focus on the issue of adaptive H ∞ -control design for a class of linear parameter-varying (LPV) systems based on the Hamiltonian-Jacobi-Isaac (HJI) method. By combining the idea of polynomially par...
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In this paper, we focus on the issue of adaptive H ∞ -control design for a class of linear parameter-varying (LPV) systems based on the Hamiltonian-Jacobi-Isaac (HJI) method. By combining the idea of polynomially parameter-dependent quadratic functions and vector projection method to derive an adaptive H ∞ -control, sufficient conditions with high precision are given to guarantee both robust asymptotic stability and disturbance attenuation of the LPV systems with unknown constant parameters. The applicability of the proposed design method is illustrated on a simple example.
In this paper, we deal with the issue of robust delay-independent asymptotic stability and robust disturbance attenuation problem for linear parameter-dependent systems. Using Hamiltonian-Jacoby-Isaac approach, a para...
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In this paper, we deal with the issue of robust delay-independent asymptotic stability and robust disturbance attenuation problem for linear parameter-dependent systems. Using Hamiltonian-Jacoby-Isaac approach, a parameter-dependent LMI optimization is obtained. It is shown that by utilizing polynomial parameter-dependent quadratic Lyapunov functions, a parameter-dependent LMI optimization problem is derived. Therefore, state feedback control is determined by solving a parameter-independent LMI. Finally, the applicability of the proposed design is illustrated on a simple example
Two invariance principles for generalized hybrid systems are presented. One version involves the use of a nonincreasing function, like in the original work of LaSalle. The other version involves "meagreness"...
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Two invariance principles for generalized hybrid systems are presented. One version involves the use of a nonincreasing function, like in the original work of LaSalle. The other version involves "meagreness" conditions. These principles characterize asymptotic convergence of bounded hybrid trajectories to weakly invariant sets. A detectability property is used to locate a set in which the Q-limit set of a trajectory is contained. Next, it is shown how the invariance principles can be used to certify asymptotic stability in hybrid systems. Lyapunov and Krasovskii theorems for hybrid systems are included.
Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks, can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which w...
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Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks, can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present an alternative for traditional inference mechanisms and CRI method. The most attractive advantage of this new method is its higher robustness with respect to changes in rule base and ability to operate when latter is sparse. In this paper interpolation with high order polynomials and /spl beta/-function is reported.
This paper explores feedback controller design for cavity flows based on reduced-order models derived using Proper Orthogonal Decomposition (POD) along with Galerkin projection method. Our preliminary analysis shows t...
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This paper explores feedback controller design for cavity flows based on reduced-order models derived using Proper Orthogonal Decomposition (POD) along with Galerkin projection method. Our preliminary analysis shows that the equilibrium of the POD model is unstable and a static output feedback controller cannot stabilize it. We develop Linear Quadratic (LQ) optimal state feedback controllers and LQ optimal observers for the linearized models. The linear controllers and observers are applied to the nonlinear system using simulations. The controller robustness is numerically tested with respect to different POD models generated at different forcing frequencies. An estimation for the region of attraction of the linear controllers is also provided.
We present explicit bounds on the classical communication cost and inefficiency of entanglement dilution via the Lo-Popescu protocol, for the case of two-term (single-qubit) entangled states. By considering a two-stag...
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We present explicit bounds on the classical communication cost and inefficiency of entanglement dilution via the Lo-Popescu protocol, for the case of two-term (single-qubit) entangled states. By considering a two-stage dilution, we consequently use prior results to obtain meaningful bounds on the classical communication cost and inefficiency of dilution between two-term partially entangled states
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