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This paper presents a decentralized method to the problem of multiple unmanned aerial vehicles (UAVs) cooperative search of an unknown area. Firstly, based on search map model, the multiple UAVs cooperative search problem is posed as a receding horizon (RH) optimization decision problem, and a RH based UAV search decision process is proposed. Then, this centralized online optimization problem is partitioned...
This paper addresses two problems in visually-controlled robots. The first consists of positioning the end-effector of a robot manipulator on a plane of interest by using a monocular vision system. The problem amounts to estimating the transformation between the coordinates of an image point and its three-dimensional location supposing that only the camera intrinsic parameters are known. The second...
Solving the load flow equations is an important problem in power systems. This paper proposes an approach for addressing this problem via a convex optimization with LMI constraints. This approach ensures to find all solutions provided that the dimension of a linear space provided by the optimization is smaller than a known threshold. Then, this paper considers the characterization of the set of admissible...
In practical applications, it is often encountered that the jump modes of a Markovian jump linear system may not be fully accessible to the filter, and thus designing a filter which partially or totally independent of the jump modes becomes significant. In this paper, by virtue of a new stability and Hinfin performance characterization, a novel necessary and sufficient condition for the existence...
Structural controllability evaluation for heat exchanger networks (HENs) was proposed in this paper. Structural singularities, right-half plane zeros, time delays, and interactions were considered as structural analysis tools, in which the evaluation was formulated as an integer linear programming (ILP). The solutions comprising of the number of parallel opposing effects, the sum of relative orders,...
This paper presents Model predictive control (MPC) of nonlinear hybrid system based on neural network (NN) optimization. Multiple model method is used to modeling of nonlinear hybrid system and these models are combined using Bayes theorem. NN optimization combined gradient NN with recurrent NN is proposed to solve optimization problem of each sample time in MPC. An example of benchmark three spherical...
This paper is concerned with the simultaneous design of plant structure parameters (passive components) and controllers (active components) in order to achieve the optimal system performance. With LFT (linear fractional transformation) formulation, the simultaneous design problem can be transferred into a design problem of a controller with specific construction. It is a complex control problem with...
The connection-coefficients control is a new control model, which is proposed for regulating connection coefficients of the state variables the subsystems of the interconnected systems. It is the direct regulations for the connections of system states and is different from the traditional feedback compensation. This paper is focused on the Connection-Coefficients Synergic Stabilization Problem of...
The online computation efficiency is always an important issue of the robust model predictive control (RMPC), especially for fast systems. For uncertain systems with polytopic description, two synthesis approaches of off-line RMPC are presented. By offline designing several polyhedral invariant sets properly, the online computation of RMPC is only simple algebra calculation, which reduces the online...
The flow control problem of urban sewer networks to minimize overflows is cast in the framework of model predictive control. The predictive control algorithm is developed based on the discrete maximum principle, employing nonlinear constrained optimal control concepts. By introducing element models, the mathematical model of a sewer network can be formulated. Since the function of the reservoir overflow...
In this paper, a new robust and optimization based nonlinear controller with respect to a certain kind of nonlinear disturbed systems is proposed based on control Lyapunov functions (CLF) concept and receding horizon control (RHC) scheme. This new controller can be divided into two components, one is the robust control law with measurable disturbance information; another is the robust receding horizon...
Parametric optimization techniques is an established practice for designing controllers. It was used, for example, to obtain the parameters of PI and PID controllers in several works. An important criticism to this technique is the dependence of the design from a parametric model of the plant, which have to be very accurate. In the current work, the problem of designing a continuous-time PID controller...
For an oversampled linear phase (LP) perfect reconstruction filter banks with lattice structure, the synthesis FB is not unique. However, existing methods to choose a synthesis FB for ldquooptimalrdquo noise reduction may destroy the linear phase and lattice structure property. This paper studies the noise reduction design problem for oversampled filter banks (FBs) preserving lattice structure. Both...
A novel integration of design and controllability method is proposed for the process design under uncertainty. The key idea is to integrate the robust eigenvalue assignment with the robust optimal design to achieve the desirable design performance and dynamic performance. The robust optimal design is to have a trade-off between robustness and optimization for the steady-state economic design, and...
Estimation of distribution algorithm (EDA) is a kind of evolutionary algorithm which updates and samples from probabilistic model in evolutionary course. The key of EDA is the construction of probability model suitable for real distribution. Gaussian distribution is widely used in EDAs but the assumption of normality is not realistic for many real-life problems. In this paper, a new EDA using kernel...
A novel method for planning point-to-point robot trajectories will be introduced in this paper. With the new method, the requirement of an optimal path and the need of a slim motion due to the lack of free space can be compromised. The generated slim motion is suitable for applications where human-robot cooperation takes place and the workspace is considered to be constrained. This new method is based...
This paper proposes a novel method to synthesize robust proportional-integral-derivative (PID) controllers using particle swarm optimization (PSO). Robust control is well known for its ability in dealing with system uncertainties and disturbances. Standard robust control design, however, can result in controllers that are high-order and complicated and can be difficult to implement in practical applications...
In HVAC plants of medium-high cooling capacity, multiple-chiller systems are often employed. In such systems, chillers are independent of each other to provide standby capacity, operational flexibility, and less disruption maintenance. However, the problem of efficiently managing multiple-chiller systems is complex in many respects. In particular, the electrical energy consumption in the chiller plant...
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