Formation control from optimal control strategy is derived based on the position estimation for second-order molded agents using only the relative *** the proposed strategy,agents can realize the convergence to the de...
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ISBN:
(纸本)9781479947249
Formation control from optimal control strategy is derived based on the position estimation for second-order molded agents using only the relative *** the proposed strategy,agents can realize the convergence to the desired formation configure if and only if the interaction graph for the agents has a spanning *** control input is added into the derived control strategy,with the help of detecting obstacles using the relative position and taking avoidance measures using the estimated position,it can also realize obstacle avoidance for agents between themselves.
In this paper, the problem of parameter estimation is investigated for a class of discrete-time linear systems with missing outputs and outliers. It is assumed that the unknown parameters are constant and the evolutio...
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In this paper, the problem of parameter estimation is investigated for a class of discrete-time linear systems with missing outputs and outliers. It is assumed that the unknown parameters are constant and the evolution of the systems is subject to some unknown but bounded noises. To solve such a problem, a recursive algorithm based on set membership identification is proposed and employed. Besides, the data validation is processed and outliers are set aside. The effectiveness of the algorithm is verified by performing some numerical simulations.
This paper studies the stability of state estimation for a discrete-time linear stochastic system, the states of which are measured by multiple sensors and transmitted over multiple wireless channels. Random packet lo...
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ISBN:
(纸本)9781479947249
This paper studies the stability of state estimation for a discrete-time linear stochastic system, the states of which are measured by multiple sensors and transmitted over multiple wireless channels. Random packet loss process introduced by each wireless channel is modeled by an independent and identically distributed(i.i.d.) Bernoulli process. The estimation strategy designed in this paper is based on Covariance Intersection fusion of local state estimates of the observable subsystem of each sensor. The sufficient conditions, imposing constraint on the packet success probability of each channel, are established by taking into account each observable subsystem structure to guarantee the expectation of the trace of estimation error covariance matrices is exponentially bounded, and the upper bound is given. Simulation examples are provided to demonstrate the effectiveness of the results.
Wireless networked controlsystems have gained significant popularity due to commissioning and maintenance *** there are various wireless communication protocols available to accomplish the control networks. Recently,...
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Wireless networked controlsystems have gained significant popularity due to commissioning and maintenance *** there are various wireless communication protocols available to accomplish the control networks. Recently, IEEE802.15.4e protocol for low latency deterministic network has been introduced that shows prominent theoretical characteristics under effective frequency planning to minimize mutual interference. Factory automation, highly exacting from low latency point of view, requires sensors refresh rate not more than of order 10 milliseconds. This new protocol meets such stringent requirement of industrial automation systems. In this paper, we compare the new protocol with its previous version and observe its suitability for industrial networked controlsystems as a communication protocol. We introduce different LLDN(low latency deterministic network) superframe configurations that show trade-offs among various network parameters. It gives an insight of relationship among various network parameters like sensors refresh rate, number of devices accommodated in network and data payload exchanged between coordinator and end devices with emphasis on different levels of security incorporated.
This paper presents a novel adaptive IIR filter modeling for the hysteresis characteristic in PEA (piezoelectric actuator). First, the PEA hysteresis operators are introduced and the modeling methods of traditional ad...
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This paper presents a novel adaptive IIR filter modeling for the hysteresis characteristic in PEA (piezoelectric actuator). First, the PEA hysteresis operators are introduced and the modeling methods of traditional adaptive IIR (infinite-impulse response) filter are discussed. Then, delay operators of IIR adaptive filter are replaced with Backlash operators to compose a new adaptive IIR filter model. During the modeling process, LMS (Least Mean Square) algorithm is used to adjust the weight values. At last the modeling effectiveness is verified via a micro-positioning system experiment platform based on PEA. Experimental results show that the proposed Backlash operator based IIR adaptive filter can achieve accurate hysteresis modeling.
One crucial problem for a humanoid service robot is to be able to communicate with humans naturally. This study focuses on this issue and develops a social interactive system for a humanoid robot to interact with huma...
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In this paper, we propose a distributed adaptive approach for tracking problem without using leader's velocity information, where agents are modeled by Euler-Lagrange equations. It is assumed that only a small fra...
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In this paper, we propose a distributed adaptive approach for tracking problem without using leader's velocity information, where agents are modeled by Euler-Lagrange equations. It is assumed that only a small fraction of agents within the leader's communication range are informed about the position of the leader. Without using the leader's velocity information, a connectivity-preserving adaptive controller is proposed to achieve tracking control on Lagrangian systems with the leader of constant velocity. Moreover, position and velocity consensus can be achieved asymptotically with the proposed control strategy. Numerical simulations are further provided to illustrate the theoretical results.
This paper investigates the distributed tracking control problem for multiple Lagrangian systems under a general directed graph where only a portion of the agents have access to the desired time-varying trajectory. To...
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This paper investigates the distributed tracking control problem for multiple Lagrangian systems under a general directed graph where only a portion of the agents have access to the desired time-varying trajectory. To overcome the problem that only positions are measured, a observer is designed to estimate the velocity for each follower. By employing the estimated states, the distributed observer-based controller is proposed using only position measurements. Furthermore, the condition for the distributed tracking problem on the directed graph is derived, such that the tracking errors and observer errors semi-globally converge to zero. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.
In this paper,a novel particle swarm algorithm for solving constrained multiobjective optimization problems is *** new algorithm is able to utilize valuable information from the infeasible region by intentionally keep...
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ISBN:
(纸本)9781479947249
In this paper,a novel particle swarm algorithm for solving constrained multiobjective optimization problems is *** new algorithm is able to utilize valuable information from the infeasible region by intentionally keeping a set of infeasible solutions in each *** enhance the diversity of these preserved infeasible solutions,a modified version of adaptive grid is *** addition,a voting mechanism is designed to balance the preference of infeasible solutions with smaller constraint violation and the exploration of the infeasible *** effectiveness of the proposed method is validated by simulations on several commonly used benchmark *** using the hypervolume indicator,it is shown that the proposed algorithm is more powerful than two other state-of-the-art algorithms.
This paper aims to present a robust attitude control strategy with guaranteed transient performance. Firstly, a Lyapunov-based control law is designed to achieve high-performance attitude control in the absence of dis...
This paper aims to present a robust attitude control strategy with guaranteed transient performance. Firstly, a Lyapunov-based control law is designed to achieve high-performance attitude control in the absence of disturbance and parameter variation. The proposed control law uses small feedback gains to suppress the control torque at large attitude error, and increases those gains with the convergence of attitude error to accelerate the system response. The overshooting phenomenon is also avoided by imposing a restriction on the parameter selection. Then, the integral sliding mode control technique is employed to improve the robustness, where the Lyapunov-based control law is used as the equivalent control part. Theoretical analysis and simulation results verify the effectiveness of the proposed strategy.
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