The task of motion planning for robotic manipulators means to drive an end-effector between designated points in the work area while obstacles are not hit. This contribution investigates the case of dynamic obstacles ...
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The task of motion planning for robotic manipulators means to drive an end-effector between designated points in the work area while obstacles are not hit. This contribution investigates the case of dynamic obstacles (like human operators) and the consideration of a performance criterion to be maximized for the motion. The proposed approach maps the dynamics of the manipulator and the obstacles into the C times T-space (spanned by the configuration C and the time T). Within this space, an (sub-)optimal sequence of configurations in the collision-free subspace is determined by mixed-integer linear programming. To achieve sufficient computational efficiency, the optimization task is approached by employing the principles of model predictive control. The paper describes the approach based on the example of a two-link robot interacting with a human operator.
A recursive procedure is proposed to reduce a set of inequality constraints of high relative order to single constraints of relative order one for a class of uncertain,multi-input nonlinear systems.A modification of a...
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A recursive procedure is proposed to reduce a set of inequality constraints of high relative order to single constraints of relative order one for a class of uncertain,multi-input nonlinear systems.A modification of a nominal control signal on the newly constructed constraints guarantees robust constraint *** resulting robust invariant controller is applied to the constrained flight and the obstacle avoidance problem of a VTOL helicopter.
Abstract The paper presents a moving horizon ℓ 2 control approach for the class of linear parameter-varying systems. By solving online a convex optimization problem subject to linear matrix inequality constraints the ...
Abstract The paper presents a moving horizon ℓ 2 control approach for the class of linear parameter-varying systems. By solving online a convex optimization problem subject to linear matrix inequality constraints the ℓ 2 gain from the energy bounded external disturbance to the performance output is minimized at each sampling instant. The approach guarantees satisfaction of state and input constraints and it is shown that the online recalculation of the control law improves disturbance attenuation significantly when compared to a static control law.
This paper proposes a model predictive control scheme for a class of constrained nonlinear time-delay systems with guaranteed closed-loop asymptotic *** stability of the closed-loop is guaranteed by utilizing an appro...
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This paper proposes a model predictive control scheme for a class of constrained nonlinear time-delay systems with guaranteed closed-loop asymptotic *** stability of the closed-loop is guaranteed by utilizing an appropriate terminal cost functional and an appropriate terminal region.A novel structured procedure is derived to determine the terminal cost and the terminal region *** this purpose,a combination of Lyapunov-Krasovskii and LyapunovRazumikhin arguments is used to compute a locally stabilizing *** resulting conditions are formulated in terms of linear matrix inequalities.
This note studies the iterative solution to the Stein matrix equation. Firstly, it is shown that the recently developed Smith ( l ) iteration converges to the exact solution for arbitrary initial condition whereas a s...
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This note studies the iterative solution to the Stein matrix equation. Firstly, it is shown that the recently developed Smith ( l ) iteration converges to the exact solution for arbitrary initial condition whereas a special initial condition is required in the literature. Secondly, by presenting a new accelerative Smith iteration named the r -Smith iteration that includes the well-known ordinary Smith accelerative iteration as a special case, we have shown that the r -Smith accelerative iteration requires less computation than the Smith iteration and the Smith ( l ) iteration, and the ordinary Smith accelerative iteration requires the least computations comparing with other Smith-type iterations.
Despite the availability of lane departure and lane keeping systems for highway assistance, unmarked and winding rural roads still pose challenges to lane recognition systems. To detect an upcoming curve as soon as po...
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ISBN:
(纸本)9781424435036
Despite the availability of lane departure and lane keeping systems for highway assistance, unmarked and winding rural roads still pose challenges to lane recognition systems. To detect an upcoming curve as soon as possible, the viewing range of image-based lane recognition systems has to be extended. This is done by evaluating 3D information obtained from stereo vision or imaging radar in this paper. Both sensors deliver evidence grids as the basis for road course estimation. Besides known Kalman filter approaches, particle filters have recently gained interest since they offer the possibility to employ cues of a road, which can not be described as measurements needed for a Kalman filter approach. We propose to combine both principles and their benefits in a Kalman particle filter. The comparison between the results gained from this recently published filter scheme and the classical approaches using real world data proves the advantages of the Kalman particle filter.
In order to study the structural properties of electrical network over F(z), it is necessary to analyze the coefficient matrix A of the state equations. In paper, author has proved that the characteristic roots of A a...
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In order to study the structural properties of electrical network over F(z), it is necessary to analyze the coefficient matrix A of the state equations. In paper, author has proved that the characteristic roots of A are zeros or unequal non-constants. According to electrical theory, all-capacitor cut-set and all-inductor loop would cause zero eigenvalue. In this paper author expatiates an algorithm on how to find the independent all-capacitor cut-set in electrical network with computer and uses an example to show the process.
This paper presents a computationally attractive nonlinear model predictive control approach for the class of continuous time Lure systems. The control law is obtained via the repeated solution of an efficient to solv...
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This paper presents a computationally attractive nonlinear model predictive control approach for the class of continuous time Lure systems. The control law is obtained via the repeated solution of an efficient to solve convex optimization problem based on linear matrix inequalities (LMIs). Closed-loop stability and satisfaction of input and state constraints are guaranteed by the feasibility of the LMIs at initial time. The simulation of a flexible link robotic arm shows the applicability and effectiveness of the proposed controller.
Decomposition of acceleration was investigated as an alternative to commonly used direct spectral analysis of measured acceleration or angular velocity for tremor quantification. Orientation estimation algorithm was d...
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This paper proposes a model predictive control scheme for a class of constrained nonlinear time-delay systems with guaranteed closed-loop asymptotic stability. Asymptotic stability of the closed-loop is guaranteed by ...
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This paper proposes a model predictive control scheme for a class of constrained nonlinear time-delay systems with guaranteed closed-loop asymptotic stability. Asymptotic stability of the closed-loop is guaranteed by utilizing an appropriate terminal cost functional and an appropriate terminal region. A novel structured procedure is derived to determine the terminal cost and the terminal region offline. For this purpose, a combination of Lyapunov-Krasovskii and Lyapunov-Razumikhin arguments is used to compute a locally stabilizing controller. The resulting conditions are formulated in terms of linear matrix inequalities.
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