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Affine Formation Maneuver control of Multi-Agent Systems with Directed Interaction Graphs

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Affine Formation Maneuver Control of Multi-Agent Systems wit...

第37届中国控制会议

作者： Yang Xu Shiyu Zhao Delin Luo Yancheng You School of Aerospace Engineering Xiamen University Department of Electrical and Computer Engineering National University of Singapore Department of Automatic Control and Systems Engineering University of Sheffield

The affine formation maneuver control problem of a leader-follower type multi-agent systems with the directed interaction graphs is studied in this paper. This paper firstly gives and proves a sufficient and necessary condition of achieving the affine localizability. Then, under the（d + 1）-reachable condition of the given d-dimensional nominal formation with d + 1 leaders, a formation of agents can be reshaped in arbitrary dimension by only controlling these leaders. In the sequel, a novel distributed control method for the followers with single-integrator dynamics is proposed to achieve the desired time-varying maneuvers, and the global stability is also proved. Corresponding simulations are carried out to verify the theoretical results,which show that these followers are tracking the time-varying references accurately and continuously.

关键词： Affine formation control Multi-agent systems Directed graph Signed Laplacian

A Sliding Mode Observer for Uncertain Nonlinear Systems Based on Multiple Models Approach

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International Journal of Automation and computing 2017年第2期14卷 202-212页

作者： Kd s Hfa edh Karim Dahech Tarak Damak Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA) National School of Engineers of Sfax University of Sfax B.P. 1173 3038 Sfax Tunisia

This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters＇ variations of the nonlinear system. Linear matri~ inequalities （LMIs） have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.

关键词： Uncertain nonlinear system norm bounded uncertainty multiple models approach multiple observer sliding modeobserver.

Algorithms and performance analysis for stochastic wiener system identification

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arXiv 2018年

作者： Wahlberg, Bo Ljung, Lennart Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Automatic Control Linköping University LinköpingSE-581 83 Sweden

We analyze the statistical performance of identification of stochastic dynamical systems with non-linear measurement sensors. This includes stochastic Wiener systems, with linear dynamics, process noise and measured by a non-linear sensor with additive measurement noise. There are many possible system identification methods for such systems, including the Maximum Likelihood (ML) method and the Prediction Error Method (PEM). The focus has mostly been on algorithms and implementation, and less is known about the statistical performance and the corresponding Cramér-Rao Lower Bound (CRLB) for identification of such non-linear systems. We derive expressions for the CRLB and the asymptotic normalized covariance matrix for certain Gaussian approximations of Wiener systems to show how a non-linear sensor affects the accuracy compared to a corresponding linear sensor. The key idea is to take second order statistics into account by using a common parametrization of the mean and the variance of the output process. This analysis also leads to a ML motivated identification method based on the conditional mean predictor and a Gaussian distribution approximation. The analysis is supported by numerical simulations. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

Steady-state analysis of a neural-cognition based human-social behavior model

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arXiv 2018年

作者： Wei, Jieqiang Nekouei, Ehsan Wu, Junfeng Cvetkovic, Vladimir Johansson, Karl H. Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden College of Control Science and Engineering Zhejiang University Hangzhou China School of Architecture and the Built Environment

We consider an extension of the Rescorla-Wagner model which bridges the gap between conditioning and learning on a neural-cognitive, individual psychological level, and the social population level. In this model, the interaction among individuals is captured by a Markov process. The resulting human-social behavior model is a recurrent iterated function systems which behaves differently from the classical Rescorla- Wagner model due to randomness. Convergence and ergodicity properties of the internal states of agents in the proposed model are studied. Copyright © 2018, The Authors. All rights reserved.

关键词： Decision making

An asymptotically optimal indirect approach to continuous-time system identification

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arXiv 2018年

作者： González, Rodrigo A. Rojas, Cristian R. Welsh, James S. Department of Automatic Control Access Linnaeus Centre Kth Royal Institute of Technology Stockholm10044 Sweden School of Electrical Engineering and Computer Science University of Newcastle

The indirect approach to continuous-time system identification consists in estimating continuous-time models by first determining an appropriate discrete-time model. For a zero-order hold sampling mechanism, this approach usually leads to a transfer function estimate with relative degree 1, independent of the relative degree of the strictly proper real system. In this paper, a refinement of these methods is developed. Inspired by indirect PEM, we propose a method that enforces a fixed relative degree in the continuous-time transfer function estimate, and show that the resulting estimator is consistent and asymptotically efficient. Extensive numerical simulations are put forward to show the performance of this estimator when contrasted with other indirect and direct methods for continuous-time system identification. Copyright © 2018, The Authors. All rights reserved.

关键词： Continuous time systems

Non-uniqueness of stationary solutions in extremum seeking control

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arXiv 2018年

作者： Trollberg, Olle Jacobsen, Elling W. Department of Automatic Control Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Osquldas v. 10 Stockholm100 44 Sweden

Extremum seeking control (ESC) is a classical adaptive control method for steady-state optimization, purely based on output feedback and without the need for a plant model. It is well known that the extremum seeking control loop, under certain mild conditions on the controller, has a stable stationary periodic solution in the vicinity of an extremum point of the steady-state input-output map of the plant. However, this is a local result only and this paper investigates whether this solution is necessarily unique given that the underlying optimization problem is convex. Wefirst derive a necessary condition that any stationary solution of the ESC loop must satisfy. For plants in which the extremum point is due to a purely static nonlinearity, such as in Hammerstein or Wiener plants, the condition involves the steady-state gradient. However, for more general plants the necessary condition involves the phase lag of the locally linearized plant, indicating the possible existence of solutions without any relationship to optimality. Combining the derived necessary condition with the existence of a local solution close to the optimum, we employ the implicit function theorem and bifurcation theory to trace out branches of stationary solutions for varying loop parameters. The focus is on solutions corresponding to limit cycles of the same period as the forcing. We derive conditions on when these branches bifurcate, resulting in multiple stationary solutions. The results show that cyclic fold bifurcations may exist, resulting in the existence of multiple stationary period one solutions, of which only one is related to the optimality conditions. We illustrate the results through an example in which the conversion in a chemical reactor is optimized using ESC. We show that at least_ve stationary solutions may exist simultaneously for realistic control parameters, and that several of these solutions are stable. One consequence of the non-uniqueness is that one in general needs to

关键词： Bifurcation (mathematics)

Combining Lattice-Based Planning and Path Optimization in Autonomous Heavy Duty Vehicle Applications

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Combining Lattice-Based Planning and Path Optimization in Au...

IEEE Symposium on Intelligent Vehicle

作者： Rui Oliveira Mårcello Cirillo Jonas M artensson Bo Wahlberg Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Scania Autonomous Transport Solutions Sodertalje Sweden

Lattice-based motion planners are an established method to generate feasible motions for car-like vehicles. However, the solution paths can only reach a discretized approximation of the intended goal pose. Moreover, they can be optimal only with respect to the actions available to the planner, which can result in paths with excessive steering. These drawbacks have a negative impact when used in real systems. In this paper we address both drawbacks by integrating a steering method into a state-of-the-art lattice-based motion planner. Un- like previous approaches, in which path optimization happens in an a posteriori step after the planner has found a solution, we propose an interleaved execution of path planning and path optimization. The proposed approach can run in real-time and is implemented in a full-size autonomous truck, and we show experimentally that it is able to greatly improve the quality of the solutions provided by a lattice planner.

关键词： Lattices Planning Optimization Real-time systems Space exploration Path planning Autonomous vehicles

Trajectory generation using sharpness continuous dubins-like paths with applications in control of heavy-duty vehicles

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arXiv 2018年

作者： Oliveira, Rui Lima, Pedro F. Cirillo, Marcello Mårtensson, Jonas Wahlberg, Bo Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Scania Autonomous Transport Solutions Södertälje Sweden

We present a trajectory generation framework for control of wheeled vehicles under steering actuator constraints. The motivation is smooth driving of autonomous heavy-duty vehicles, which are characterized by slow actuator dynamics. In order to deal with the slow dynamics, we take into account rate and, additionally, torque limitations of the steering actuator directly. Previous methods only take into account limitations in the path curvature, which deals indirectly with steering rate limitations. We propose the new concept of Sharpness Continuous curves, which uses cubic curvature paths together with circular arcs to steer the vehicle. The obtained paths are characterized by a smooth and continuously differentiable steering angle profile. The final trajectories computed with our method provide low-level controllers with reference signals which are easier to track, resulting in improved performance. The smoothness of the obtained steering profiles also results in increased passenger comfort. The method is characterized by fast computation times. We detail possible path planning applications of the method, and conduct simulations that show its advantages and real-time capabilities. Copyright © 2018, The Authors. All rights reserved.

关键词： Motion planning

Computing monotone policies for Markov decision processes: a nearly-isotonic penalty approach

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IFAC-PapersOnLine 2017年第1期50卷 8429-8434页

作者： Mattila R. Rojas C.R. Krishnamurthy V. Wahlberg B. Department of Automatic Control School of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering Cornell University Cornell TechNY United States

This paper discusses algorithms for solving Markov decision processes (MDPs) that have monotone optimal policies. We propose a two-stage alternating convex optimization scheme that can accelerate the search for an optimal policy by exploiting the monotone property The first stage is a linear program formulated in terms of the joint state-action probabilities. The second stage is a regularized problem formulated in terms of the conditional probabilities of actions given states. The regularization uses techniques from nearly-isotonic regression. While a variety of iterative method can be used in the first formulation of the problem, we show in numerical simulations that, in particular, the alternating method of multipliers (ADMM) can be significantly accelerated using the regularization step. © 2017

关键词： alternating direction method of multipliers (ADMM) isotonic regression l1-regularization Markov decision process (MDP) monotone policy sparsity stochastic control