Distributed adaptive event-triggered protocol for tracking control of leader-following multi-agent systems     

Jinfeng Gao  Mengna Zheng 《Journal of The Franklin Institute》2019,356(17):10466-10479

A novel adaptive event-triggered control protocol is developed to investigate the tracking control problem of multi-agent systems with general linear dynamics. By introducing the event-triggered control strategy, each agent can decide when to transfer its state to its neighbors at its own triggering instants, which can greatly reduce communication burden of agents. It is shown that the “Zeno phenomenon” does not occur by verifying that there exists a positive lower bound on the inter-event time intervals of agents under the proposed adaptive event-triggered control algorithm. Finally, an example is provided to testify the effectiveness of the obtained theoretical results.  相似文献   

An improved design strategy for approximation-based adaptive event-triggered tracking of a class of uncertain nonlinear systems     

Yun Ho Choi  Sung Jin Yoo 《Journal of The Franklin Institute》2019,356(8):4378-4396

This paper presents an improved adaptive design strategy for neural-network-based event-triggered tracking of uncertain strict-feedback nonlinear systems. An adaptive tracking scheme based on state variables transmitted from the sensor-to-controller channel is designed via only single neural network function approximator, regardless of unknown nonlinearities unmatched in the control input. Contrary to the existing multiple-function-approximators-based event-triggered backstepping control results with multiple triggering conditions dependent on all error surfaces, the proposed scheme only requires one triggering condition using a tracking error and thus can overcome the problem of the existing results that all virtual controllers with multiple function approximators should be computed in the sensor part. This leads to achieve the structural simplicity of the proposed event-triggered tracker in the presence of unmatched and unknown nonlinearities. Using the impulsive system approach and the error transformation technique, it is shown that all the signals of the closed-loop system are bounded and the tracking error is bounded within pre-designable time-varying bounds in the Lyapunov sense.  相似文献   

Stability of mode-dependent linear switched singular systems with stable and unstable subsystems     

Jumei Wei  Huimin Zhi  Kai Liu  Xiaowu Mu 《Journal of The Franklin Institute》2019,356(5):3102-3114

This paper studies the E-exponential stability of mode-dependent linear switched singular systems with stable and unstable subsystems. First, by constructing an appropriate multiple discontinuous Lyapunov function, new sufficient conditions of E-exponential stability for linear switched singular systems are established. Considering the feature of mode-dependent average dwell time switching, we adopt the switching strategy where fast switching and slowing switching are respectively applied to unstable and stable subsystems. Compared with the existing results, our approach is more flexible and tighter bounds can be obtained. Finally, a numerical example is provided to illustrate the effectiveness of the proposed criteria.  相似文献   

A robust unscented transformation for uncertain moments     

Hugo T.M. Kussaba  João Y. Ishihara  Leonardo R.A.X. Menezes 《Journal of The Franklin Institute》2019,356(6):3797-3810

This paper proposes a robust version of the unscented transform (UT) for one-dimensional random variables. It is assumed that the moments are not exactly known, but are known to lie in intervals. In this scenario, the moment matching equations are reformulated as a system of polynomial equations and inequalities, and it is proposed to use the Chebychev center of the solution set as a robust UT. This method yields a parametrized polynomial optimization problem, which in spite of being NP-Hard, can be relaxed by some algorithms that are proposed in this paper.  相似文献   

Enhanced speed control of a DC servo system using PI + DF controller tuned by stochastic fractal search technique     

Emre Çelik  Halil Gör 《Journal of The Franklin Institute》2019,356(3):1333-1359

Since Proportional?+?Integral?+?Derivative (PID) controller is still the workhorse in taking over the workload of process control systems, this article introduces a new design methodology toward improving the performance of such controller. After a PI control law with windup protection is given, it is combined with a derivative path employing a first-order low pass filter in an innovative way to develop a performant controller called PI?+?DF controller. In attempting to attain a high level of control performance, gains of this controller including proportional, integral, derivative and filter gains are tuned choosing the recently introduced Stochastic Fractal Search (SFS) algorithm owing to its superiority to many state-of-the-art algorithms considering convergence, accuracy and robustness. To evaluate the efficacy of SFS, Particle Swarm Optimization (PSO) is also applied to the case study. Furthermore, the presented SFS optimized PI?+?DF controller is compared to a recently reported control scheme through simulation and experimental tests on an identical DC servo system. After providing the stability proof, SFS tuned PI?+?DF controller is found to be the pioneer in exhibiting the most accurate speed response profile under complicated scenarios, which is followed by PSO tuned PI?+?DF controller and the existing control approach, respectively.  相似文献   

Modeling,analysis and control of networked autonomous agents     

Mario Di Bernardo 《Journal of The Franklin Institute》2019,356(2):719-721

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Decentralized state estimation for the control of network systems     

Francesca Boem  Lorenzo Sabattini  Cristian Secchi 《Journal of The Franklin Institute》2019,356(2):860-882

The paper proposes a decentralized state estimation method for the control of network systems, where a cooperative objective has to be achieved. The nodes of the network are partitioned into independent nodes, providing the control inputs, and dependent nodes, controlled by local interaction laws. The proposed state estimation algorithm allows the independent nodes to estimate the state of the dependent nodes in a completely decentralized way. To do that, it is necessary for each independent node of the network to estimate the control input components computed by the other independent nodes, without requiring communication among the independent nodes. The decentralized state estimator, including an input estimator, is developed and the convergence properties are studied. Simulation results show the effectiveness of the proposed approach.  相似文献   

Adaptive coordinated attitude control for spacecraft formation with saturating actuators and unknown inertia   总被引：1，自引：0，他引：1  

Zhihao Zhu  Yu Guo 《Journal of The Franklin Institute》2019,356(2):1021-1037

In this paper, an adaptive attitude coordination control problem for spacecraft formation flying is investigated under a general directed communication topology containing a directed spanning tree with a leader as the root. In the presence of unknown time-varying inertia, persistent external disturbances and control input saturation, a novel robust adaptive coordinated attitude control algorithm with no prior knowledge of inertia for spacecraft is proposed to coordinately track the common time-varying reference states. Aiming at optimizing the control algorithm, a dynamic adjustment function is introduced to adjust the control gain according to the tracking errors. The effectiveness of the proposed control scheme is illustrated through numerical simulation results.  相似文献   

Modified tracking performance limitation of networked time-delay systems with two-channel constraints     

Xi-Sheng Zhan  Ling-Li Cheng  Jie Wu  Huai-Cheng Yan 《Journal of The Franklin Institute》2019,356(12):6401-6418

This paper investigates the modified tracking performance limitation of the networked time-delay systems with two-channel constraints. We consider both the white Gaussian noise and packet dropout constraints in the communication channels. In the plant, the non-minimum phase, unstable poles and time-delay are considered. The modified tracking performance limitation expressions will be achieved using the co-prime factorization and the spectral decomposition technique, and the two-parameter controller is adopted. The results show that the modified tracking performance limitation is related to the intrinsic properties of the given plant, including the non-minimum phase zeroes, the unstable poles and the time-delay. Furthermore, the network communication parameters, e.g. the white Gaussian noise, the packet-dropouts probability and the modified factor affect the modified tracking performance limitation of the networked time-delay systems. Finally, some particular examples are provided to illustrate the efficiency of the proposed method.  相似文献   

Primal-dual stochastic distributed algorithm for constrained convex optimization     

Youcheng Niu  Haijing Wang  Zheng Wang  Dawen Xia  Huaqing Li 《Journal of The Franklin Institute》2019,356(16):9763-9787

This paper investigates distributed convex optimization problems over an undirected and connected network, where each node’s variable lies in a private constrained convex set, and overall nodes aim at collectively minimizing the sum of all local objective functions. Motivated by a variety of applications in machine learning problems with large-scale training sets distributed to multiple autonomous nodes, each local objective function is further designed as the average of moderate number of local instantaneous functions. Each local objective function and constrained set cannot be shared with others. A primal-dual stochastic algorithm is presented to address the distributed convex optimization problems, where each node updates its state by resorting to unbiased stochastic averaging gradients and projects on its private constrained set. At each iteration, for each node the gradient of one local instantaneous function selected randomly is evaluated and the average of the most recent stochastic gradients is used to approximate the true local gradient. In the constrained case, we show that with strong-convexity of the local instantaneous function and Lipschitz continuity of its gradient, the algorithm converges to the global optimization solution almost surely. In the unconstrained case, an explicit linear convergence rate of the algorithm is provided. Numerical experiments are presented to demonstrate correctness of the theoretical results.  相似文献