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1.
The advantages of maximally transferring similar process data for modeling make the process transfer model attract increasing attention in quality prediction and optimal control. Unfortunately, due to the difference between similar processes and the uncertainty of data-driven model, there are usually a more serious mismatch between the process transfer model and the actual process, which may result in the deterioration of process transfer model-based control strategies. In this research, a process transfer model based optimal compensation control strategy using just-in-time learning and trust region method is proposed to cope with this problem for batch processes. First, a novel JITL-JYKPLS (Just-in-time learning Joint-Y kernel partial least squares) model combining the JYKPLS (Joint-Y kernel partial least squares) process transfer model and just-in-time learning is proposed and employed to obtain the satisfactory approximation in a local region with the assistance of sufficient similar process data. Then, this paper integrates JITL-JYKPLS model with the trust region method to further compensate for the NCO (necessary condition of optimality) mismatch in the batch-to-batch optimization problem, and the problem of estimating experimental gradients is also avoided. Meanwhile, a more elaborate model update scheme is designed to supplement the lack of new data and gradually eliminate the adverse effects of partial differences between similar process production processes. Finally, the feasibility of the proposed optimal compensation control strategy is demonstrated through a simulated cobalt oxalate synthesis process.  相似文献   

2.
The goal of this paper is to propose an optimal fault tolerant control (FTC) approach for multi-agent systems (MASs). It is assumed that the agents have identical affine dynamics. The underlying communication topology is assumed to be a directed graph. The concepts of both inverse optimality and partial stability are further employed for designing the control law fully developed in the paper. Firstly, the optimal FTC problem for linear MASs is formulated and then it is extended to MASs with affine nonlinear dynamics. To solve the Hamilton-Jacobi-Bellman (HJB) equation, an Off-policy Reinforcement Learning is used to learn the optimal control law for each agent. Finally, a couple of numerical examples are provided to demonstrate the effectiveness of the proposed scheme.  相似文献   

3.
黄丽丽  黄振芳 《资源科学》2016,38(11):2157-2167
针对基于“Max-min”算子的区间模糊多目标规划仅采用一或两个控制变量放松所有目标和模糊约束会造成某些约束过满意而某些约束不满意的情况,本文引入两相模糊规划,构建了区间-两相模糊多目标规划模型,并以辽宁省大连市种植结构优化为例进行研究。结果表明,该模型引入多个控制变量放松每个不确定目标和约束条件,且要求它们分别不小于“Max-min”算子中相应目标和约束条件的隶属度,更充分地利用了约束资源,保证了求解的有效性,减少了农业灌溉用水量;另外区间形式的最优解及4种不同情景的优化方案为决策者提供了决策空间,更真实地反映输入参数的不确定性对配置结果的影响。  相似文献   

4.
The present paper deals with an optimal boundary control problem in which the process of systems under consideration is governed by a linear parabolic partial differential equation over an infinite time interval. The objective of the paper is to determine the optimal boundary control that minimize a given energy-based performance measure. The performance measure is specified as a quadratic functional of displacement and a suitable penalty term involving the boundary controls. In order to determine the optimal boundary controls, the problem with boundary controls are converted into a problem with distributed controls. The modal space technique is then used to reduce the system into the optimal control of time invariant lumped parameter system. The associated system of uncoupled first order initial value problems is solved in terms of controllers. Next step deals with the computation of the control and trajectory of the linear time-invariant lumped parameter. For this we approximate the controllers by a finite number of orthogonal exponential zero-interpolants over the interval [0,∞). The resultant performance index after using the optimality condition leads to a system of linear algebraic equations. The suggested technique is easy to implement on digital computer. We provide a numerical example to demonstrate the applicability and efficiency of the proposed approach.  相似文献   

5.
In this paper, we mainly tend to consider distributed leader-following fixed-time quantized consensus problem of nonlinear multi-agent systems via impulsive control. An appropriate quantized criterion and some novel control protocols are proposed in order to solve the problem. The protocols proposed integrates the two control strategies from the point of view of reducing communication costs and constraints, which are quantized control and impulsive control. The fixed-time quantized consensus of multi-agent is analyzed in terms of algebraic graph theory, Lyapunov theory and comparison system theory, average impulsive interval. The results show that if some sufficient conditions are met, the fixed-time consensus of multi-agent systems can be guaranteed under impulsive control with quantized relative state measurements. In addition, compared with finite-time consensus, the settling-time of fixed-time quantized consensus does not depend on the initial conditions of each agent but on the parameters of the protocol. Finally, numerical simulations are exploited to illustrate the effectiveness and performance to support our theoretical analysis.  相似文献   

6.
In a multi-agent framework, distributed optimization problems are generally described as the minimization of a global objective function, where each agent can get information only from a neighborhood defined by a network topology. To solve the problem, this work presents an information-constrained strategy based on population dynamics, where payoff functions and tasks are assigned to each node in a connected graph. We prove that the so-called distributed replicator equation (DRE) converges to an optimal global outcome by means of the local-information exchange subject to the topological constraints of the graph. To show the application of the proposed strategy, we implement the DRE to solve an economic dispatch problem with distributed generation. We also present some simulation results to illustrate the theoretic optimality and stability of the equilibrium points and the effects of typical network topologies on the convergence rate of the algorithm.  相似文献   

7.
In this paper, a novel iterative approximate dynamic programming scheme is proposed by introducing the learning mechanism of value iteration (VI) to solve the constrained optimal control problem for CT affine nonlinear systems with utilizing only one neural network. The idea is to show the feasibility of introducing the VI learning mechanism to solve for the constrained optimal control problem from a theoretical point of view, and thus the initial admissible control can be avoided compared with most existing works based on policy iteration (PI). Meanwhile, the initial condition of the proposed VI based method can be more general than the traditional VI method which requires the initial value function to be a zero function. A general analytical method is proposed to demonstrate the convergence property. To simplify the architecture, only one critic neural network is adopted to approximate the iterative value function while implementing the proposed method. At last, two simulation examples are proposed to validate the theoretical results.  相似文献   

8.
In this paper, the finite horizon tracking control problem of probabilistic Boolean control networks (PBCNs) is studied. For a given reference output trajectory, two trackability definitions are introduced according to whether the tracking probability is 1. Under the framework of the semi-tensor product, some necessary and sufficient conditions are obtained to determine whether the reference output trajectory is trackable with probability (probability one) by a PBCN starting from a given initial state. Based on this, two algorithms are proposed to determine the maximum tracking probability and the corresponding optimal control policy sequence. By determining the tracking error of the reference output trajectory, two related optimal control problems are considered: one is to minimize the expected value of the total tracking error, and the other is to minimize the maximum tracking error. Inspired by dynamic programming, corresponding algorithms are given to solve these two problems. Finally, two examples are given to verify the validity and correctness of the results.  相似文献   

9.
In this paper, finite-time synchronization problem is considered for a class of Markovian jump complex networks (MJCNs) with partially unknown transition rates. By constructing the suitable stochastic Lyapunov–Krasovskii functional, using finite-time stability theorem, inequality techniques and the pinning control technique, several sufficient criteria have been proposed to ensure the finite-time synchronization for the MJCNs with or without time delays. Since finite-time synchronization means the optimality in convergence time and has better robustness and disturbance rejection properties, this paper has important theory significance and practical application value. Finally, numerical simulations illustrated by mode jumping from one mode to another according to a Markovian chain with partially unknown transition probability verify the effectiveness of the proposed results.  相似文献   

10.
This paper focuses on binary optimal control of fed-batch fermentation of glycerol by Klebsiella pneumoniaewith pH feedback considering limited number of switches. To maximize the concentration of 1,3-propanediol at terminal time, we propose a binary optimal control problem subjected to time-coupled combinatorial constraint with the ratio of feeding rate of glycerol to that of NaOH as control variables. Based on time-scaling transformation and discretization, the binary optimal control problem is first transformed into a mixed binary parameter optimization problem consisting of not only continuous variables but also binary variables, which is then divided into two subproblems via combinatorial integral approximation decomposition. Finally, a novel fruit fly optimizer with modified sine cosine algorithm and adaptive maximum dwell rounding are applied to solve the obtained subproblems numerically. Numerical results show the rationality and feasibility of the proposed method.  相似文献   

11.
A distributed linear-quadratic-regulator (LQR) semistability theory for discrete-time systems is developed for designing optimal semistable controllers for discrete-time coupled systems. Unlike the standard LQR control problem, a unique feature of the proposed optimal control problem is that the closed-loop generalized discrete-time semistable Lyapunov equation can admit multiple solutions. Necessary and sufficient conditions for the existence of solutions to the generalized discrete-time semistable Lyapunov equation are derived and an optimization-based design framework for distributed optimal controllers is presented.  相似文献   

12.
This paper mainly focuses on the adaptive synchronization problem of multi-agent systems via distributed impulsive control method. Different from the existing investigations of impulsive synchronization with fixed time impulsive inputs, the proposed distributed variable impulsive protocol allows that the impulsive inputs are chosen within a time period (namely impulsive time window) which can be described by the distances of the left (right) endpoints or the centers between two adjacent impulsive time windows. Obviously, this kind of flexible control scheme is more effective in practical systems (especially for the complex environment with physical restrictions). Moreover, the proposed adaptive control technique is helpful to solve the problem with uncertain system parameters. By means of Lyapunov stability theory, impulsive differential equations and adaptive control technique, three sufficient impulsive consensus conditions are given to realize the synchronization of a class of multi-agent nonlinear systems. Finally, two numerical simulations are provided to illustrate the validity of the theoretical analysis.  相似文献   

13.
In this paper, the problem of synchronization on interval type-2 (IT2) stochastic fuzzy complex dynamical networks (CDNs) with time-varying delay via fuzzy pinning control is fully studied. Firstly, a more general complex network model is considered, which involves the time-varying delay, IT2 fuzzy and stochastic effects. More specifically, IT2 fuzzy model, as a meaningful fuzzy scheme, is investigated for the first time in CDNs. Then, with the aid of Lyapunov stability theory and stochastic analysis technique, some new sufficient criteria are established to ensure synchronization of the addressed systems. Moreover, on basis of the parallel-distributed compensation (PDC) scheme, two effective fuzzy pinning control protocols are proposed to achieve the synchronization. Finally, a numerical example is performed to illustrate the effectiveness and superiority of the derived theoretical results.  相似文献   

14.
This paper proposes an optimal three-dimensional (3-D) spatial-temporal cooperative guidance (STCG) law for intercepting a maneuvering target with impact angle and time constraints. The guidance problem is studied to achieve spatial cooperation for multi-directional attack in the normal channel and temporal cooperation for simultaneous interception in the tangential channel, respectively. Firstly, the 3-D optimal impact-angle-control guidance (OIACG) is introduced to formulate spatial interception geometry. Based on this law, the relative trajectory length is analytically derived and an accurate time-to-go predictor is formulated against maneuvering targets. In the tangential channel, an optimal temporal cooperative guidance is proposed by leveraging high-dimensional Schwarz inequality method. The proposed algorithm is believed to outperform the existing nonlinear cooperative guidance laws due to its optimality with specific performance index for minimizing the control expenditure. The convergence properties of the proposed STCG law are provided to facilitate its practical implementation. Comparison simulations and application under the realistic pursuer model and target estimation are performed to demonstrate the effectiveness and robustness of the proposed cooperative method.  相似文献   

15.
In this paper, we considered a time-optimal control problem for a new type of linear parameter varying (LPV) system which is obtained through data identification in the process of dealing with actual problems. The addition of non-linear terms is compensation for the method that does not require linear expansion at the equilibrium point. Since the objective function is the terminal time which is an implicit function concerning decision variables, it is a non-standard optimal control problem with uncertain terminal time. To find the global optimal solution to this problem, firstly, the control parameterization method is used to transform it into a nonlinear optimization problem of parameter selection, and then the modifed particle swarm optimization (PSO) algorithm is combined to solve the equivalent nonlinear programming problem. Numerical examples are used to illustrate the effectiveness of the proposed algorithm.  相似文献   

16.
This work deals with an environmental problem related to controlling eutrophication inside a sensitive zone, by means of a regulation of the wastewater discharges in the region. After setting a detailed mathematical formulation of the optimal control problem posed on a free-boundary moving domain, we present several theoretical results on existence-regularity of optimal solutions, and their characterization by a first order optimality system. In the second part of the work a complete numerical algorithm for the resolution of the control problem is proposed, and several numerical examples are also given.  相似文献   

17.
In this paper, a flatness-based adaptive sliding mode control strategy is presented to solve the trajectory tracking problem of a quadrotor. According to the differential flatness theory, the typical under-actuated quadrotor dynamics is transformed into a fully-actuated one. Based on this model, backstepping sliding mode controllers are designed to solve the trajectory tracking problem. To improve the robustness to disturbances, extended state observers are applied as a feedforward compensation of disturbances. Moreover, considering the high-order dynamics and possible instability caused by large observer gains, the adaptive method is applied to compensate for the estimation error. The effectiveness of the proposed control scheme is verified in simulations.  相似文献   

18.
In this paper, the optimal synchronization controller design problem for complex dynamical networks with unknown system internal dynamics is studied. A necessary and sufficient condition on the existence of the optimal control minimizing a quadratic performance index is given. The optimal control law consists of a feedback control and a compensated feedforward control, and the feedback control gain can be obtained by solving the well-known Algebraic Riccati Equation (ARE). Especially, in the presence of unknown system dynamics, a novel adaptive iterative algorithm using the information of system states and inputs is proposed to solve the ARE to get the optimal feedback control gain. Finally, a simulation example shows the effectiveness of the theoretical results.  相似文献   

19.
A sliding mode controller is developed for optimal transient operation of a continuous bioreactor. The sliding mode is the singular arc from the solution of an optimal control problem. The proposed controller is applied through simulations to an anaerobic digester and its performance is evaluated in terms of optimality and robustness properties.  相似文献   

20.
In this paper, a new direct method based on the Chebyshev cardinal functions is proposed to solve a class of variable-order fractional optimal control problems (V-OFOCPs). To this end, a new operational matrix (OM) of variable-order (V-O) fractional derivative in the Caputo sense is derived for these basis functions and is used to obtain an approximate solution for the problem under study. In the proposed method, the state and the control variables are expanded in terms of the Chebyshev cardinal functions with unknown coefficients, at first. Then, the OM of V-O fractional derivative and some properties of the Chebyshev cardinal functions are employed to achieve a nonlinear algebraic equation corresponding to the performance index and a nonlinear system of algebraic equations corresponding to the dynamical system in terms of the unknown coefficients. Finally, the method of constrained extremum is applied, which consists of adjoining the constraint equations derived from the given dynamical system and the initial conditions to the performance index by a set of undetermined Lagrange multipliers. As a result, the necessary conditions of optimality are derived as a system of algebraic equations in the unknown coefficients of the state variable, control variable, and Lagrange multipliers. Furthermore, some numerical examples of different types are demonstrated with their approximate solutions for confirming the high accuracy and applicability of the proposed method.  相似文献   

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