arXiv subjects

Huanshui Zhang

Publications and source records attributed to Huanshui Zhang.

At least 37 records · Page 2Linked to original sources

arXiv2024

Distributed Optimal Control and Application to Consensus of Multi-Agent Systems

This paper develops a novel approach to the consensus problem of multi-agent systems by minimizing a weighted state error with neighbor agents via linear quadratic (LQ) optimal control theory. Existing consensus control algorithms only utilize the current state of each agent, and the design of distributed controller depends on nonzero eigenvalues of the communication topology. The presented optimal consensus controller is obtained by solving Riccati equations and designing appropriate observers to account for agents' historical state information. It is shown that the corresponding cost function under the proposed controllers is asymptotically optimal. Simulation examples demonstrate the effectiveness of the proposed scheme, and a much faster convergence speed than the conventional consensus methods. Moreover, the new method avoids computing nonzero eigenvalues of the communication topology as in the traditional consensus methods.

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arXiv2024

Distributed Consensus of Heterogeneous Multi-Agent Systems Based on Feedforward Control

This paper studies the consensus problem of heterogeneous multi-agent systems by the feedforward control and linear quadratic (LQ) optimal control theory. Different from the existing consensus control algorithms, which require to design an additional distributed observer for estimating the leader's information and to solve a set of regulator equations. In this paper, by designing a distributed feedforward controller, a non-standard neighbor error system is transformed into a standard linear system, and then an optimal consensus controller is designed by minimizing a combined state error with neighbour agents. The proposed optimal controller is obtained by solving Riccati equations, and it is shown that the corresponding cost function under the proposed distributed controllers is asymptotically optimal. The proposed consensus algorithm can be directly applicable to solve the consensus problem of homogeneous systems. Simulation example indicates the effectiveness of the proposed scheme and a much faster convergence speed than the existing algorithm.

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arXiv2023

Exact Controllability of Discrete-Time Stochastic System with Multiplicative Noise

This paper is concerned with the exact controllability of discrete-time stochastic system which is one of the basic problems of modern control theory. Though the exact controllability of continuous-time system governed by Ito stochastic differential equations has been well studied in S. Peng, Progress in Natural Science, 1994, the counterpart of the discrete-time case is still open due to the adaptiveness constraint of the controllers and the solvability challenging of stochastic difference equation with terminal value. The main contribution in this paper is to present both the Gramian matrix criterion and the Rank criterion for the exact controllability of discrete-time stochastic system. The novelty lies in the transformation of the forward stochastic difference equation into a novel backward one.

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arXiv2023

Private Inputs for Leader-Follower Game with Feedback Stackelberg Strategy

In this paper, the two-player leader-follower game with private inputs for feedback Stackelberg strategy is considered. In particular, the follower shares its measurement information with the leader except its historical control inputs while the leader shares none of the historical control inputs and the measurement information with the follower. The private inputs of the leader and the follower lead to the main obstacle, which causes the fact that the estimation gain and the control gain are related with each other, resulting that the forward and backward Riccati equations are coupled and making the calculation complicated. By introducing a kind of novel observers through the information structure for the follower and the leader, respectively, a kind of new observer-feedback Stacklberg strategy is designed. Accordingly, the above-mentioned obstacle is also avoided. Moreover, it is found that the cost functions under the presented observer-feedback Stackelberg strategy are asymptotically optimal to the cost functions under the optimal feedback Stackelberg strategy with the feedback form of the state. Finally, a numerical example is given to show the efficiency of this paper.

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arXiv2023

Optimization Method Based On Optimal Control

In this paper, we focus on a method based on optimal control to address the optimization problem. The objective is to find the optimal solution that minimizes the objective function. We transform the optimization problem into optimal control by designing an appropriate cost function. Using Pontryagin's Maximum Principle and the associated forward-backward difference equations (FBDEs), we derive the iterative update gain for the optimization. The steady system state can be considered as the solution to the optimization problem. Finally, we discuss the compelling characteristics of our method and further demonstrate its high precision, low oscillation, and applicability for finding different local minima of non-convex functions through several simulation examples.

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arXiv2023

An Approach to Mismatched Disturbance Rejection Control for Continuous-Time Uncontrollable Systems

This paper focuses on optimal mismatched disturbance rejection control for linear continuoustime uncontrollable systems. Different from previous studies, by introducing a new quadratic performance index to transform the mismatched disturbance rejection control into a linear quadratic tracking problem, the regulated state can track a reference trajectory and minimize the influence of disturbance. The necessary and sufficient conditions for the solvability and the disturbance rejection controller are obtained by solving a forward-backward differential equation over a finite horizon. A sufficient condition for system stability is obtained over an infinite horizon under detectable condition. This paper details our novel approach for transforming disturbance rejection into a linear quadratic tracking problem. The effectiveness of the proposed method is provided with two examples to demonstrate.

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arXiv2023

Decentralized Control of Linear Systems with Private Input and Measurement Information

In this paper, we study the linear quadratic (LQ) optimal control problem of linear systems with private input and measurement information. The main challenging lies in the unavailability of other regulators' historical input information. To overcome this difficulty, we introduce a kind of novel observers by using the private input and measurement information and accordingly design a kind of new decentralized controllers. In particular, it is verified that the corresponding cost function under the proposed decentralized controllers are asymptotically optimal as comparison with the optimal cost under optimal state-feedback controller. The presented results in this paper are new to the best of our knowledge, which represent the fundamental contribution to classical decentralized control.

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arXiv2022

An Approach to Mismatched Disturbance Rejection Control for Uncontrollable Systems

This study focuses on the problem of optimal mismatched disturbance rejection control for uncontrollable linear discrete-time systems. In contrast to previous studies, by introducing a quadratic performance index such that the regulated state can track a reference trajectory and minimize the effects of disturbances, mismatched disturbance rejection control is transformed into a linear quadratic tracking problem. The necessary and sufficient conditions for the solvability of this problem over a finite horizon and a disturbance rejection controller are derived by solving a forward-backward difference equation. In the case of an infinite horizon, a sufficient condition for the stabilization of the system is obtained under the detectable condition. This paper details our novel approach to disturbance rejection. Four examples are provided to demonstrate the effectiveness of the proposed method.

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arXiv2022

Distributed Control of Linear Quadratic Mean Field Social Systems with Heterogeneous Agents

In this paper, we study the social optimality for mean field linear quadratic control systems following the direct approach, where subsystems are coupled via individual dynamics and costs according to a network topology. A graph is introduced to represent the network topology of the large-population system, where nodes represent subpopulations called clusters and edges represent communication relationship. By the direct approach, we first seek the optimal controller under centralized information structure, which characterized by a set of forward-backward stochastic differential equations. Then the feedback controller is obtained with the help of Riccat equations. Finally, we design the distributed controller with mean field approximations, which has the property of asymptotically social optimality.

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arXiv2022

Decentralized Strategies for Finite Population Linear-Quadratic-Gaussian Games and Teams

This paper is concerned with a new class of mean-field games which involve a finite number of agents. Necessary and sufficient conditions are obtained for the existence of the decentralized open-loop Nash equilibrium in terms of non-standard forward-backward stochastic differential equations (FBSDEs). By solving the FBSDEs, we design a set of decentralized strategies by virtue of two differential Riccati equations. Instead of the $\varepsilon$-Nash equilibrium in classical mean-field games, the set of decentralized strategies is shown to be a Nash equilibrium. For the infinite-horizon problem, a simple condition is given for the solvability of the algebraic Riccati equation arising from consensus. Furthermore, the social optimal control problem is studied. Under a mild condition, the decentralized social optimal control and the corresponding social cost are given.

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arXiv2022

LQG Differential Stackelberg Game under Nested Observation Information Pattern

We investigate the linear quadratic Gaussian Stackelberg game under a class of nested observation information pattern. Two decision makers implement control strategies relying on different information sets: The follower uses its observation data to design its strategy, whereas the leader implements its strategy using global observation data. We show that the solution requires solving a new type of forward-backward stochastic differential equations whose drift terms contain two types of conditional expectation terms associated to the adjoint variables. We then propose a method to find the functional relations between each adjoint pair, i.e., each pair formed by an adjoint variable and the conditional expectation of its associated state. The proposed method follows a layered pattern. More precisely, in the inner layer, we seek the functional relation for the adjoint pair under the sigma-sub-algebra generated by follower's observation information; and in the outer layer, we look for the functional relation for the adjoint pair under the sigma-sub-algebra generated by leader's observation information. Our result shows that the optimal open-loop solution admits an explicit feedback type representation. More precisely, the feedback coefficient matrices satisfy tuples of coupled forward-backward differential Riccati equations, and feedback variables are computed by Kalman-Bucy filtering.

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arXiv2022

Mismatched Disturbance Rejection Control for Second-Order Discrete-Time Systems

This paper is concerned with mismatched disturbance rejection control for the second-order discrete-time systems.Different from previous work, the controllability of the system is applied to design the disturbance compensation gain, which does not require any coordinate transformations. Via this new idea, it is shown that disturbance in the regulated output is immediately and directly compensated in the case that the disturbance is known. When the disturbance is unknown, an extra generalized extended state observer is applied to design the controller. Two examples are given to show the effectiveness of the proposed methods. Numerical simulation shows that the designed controller has excellent disturbance rejection effect when the disturbance is known. The example with respect to the permanent-magnet direct current motor illustrates that the proposed control method for unknown disturbance rejection is effective.

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arXiv2022

Indefinite Linear Quadratic Mean Field Social Control Problems with Multiplicative Noise

This paper studies uniform stabilization and social optimality for linear quadratic (LQ) mean field control problems with multiplicative noise, where agents are coupled via dynamics and individual costs. The state and control weights in cost functionals are not limited to be positive semi-definite. This leads to an indefinite LQ mean field control problem, which may still be well-posed due to deep nature of multiplicative noise. We first obtain a set of forward-backward stochastic differential equations (FBSDEs) from variational analysis, and construct a feedback control by decoupling the FBSDEs. By using solutions to two Riccati equations, we design a set of decentralized control laws, which is further shown to be asymptotically social optimal. Some equivalent conditions are given for uniform stabilization of the systems with the help of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed control laws.

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arXiv2021

Stabilization of Stackelberg Game-Based Control Systems

In this paper, we are concerned with the stabilizatbility of Stackelberg game-based systems. In particular, two players are involved in the system where one is the follower to minimize the related cost function and the other is the leader to stabilize the system. The main contribution is to derive the necessary and sufficient condition for the stabilization of the game-based system. The key technique is to explicitly solve the forward and backward difference equations (FBDEs) based on the maximum principle and give the optimal feedback gain matrix of the leader by using the matrix maximum principle.

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arXiv2020

Optimal Control for Discrete-time NCSs with Input Delay and Markovian Packet Losses: Hold-Input Case

This paper is concerned with the linear quadratic optimal control problem for networked system simultaneously with input delay and Markovian dropout. Different from the results in the literature, we consider the hold-input strategy, which is much more computationally complicated than zero-input strategy, but much better in most cases especially in the transition phase. Necessary and sufficient conditions for the solvability of optimal control problem over a finite horizon are given by the coupled difference Riccati-type equations. Moreover, the networked control system is mean-square stability if and only if the coupled algebraic Riccati-type equations have a particular solution. The key technique in this paper is to tackle the forward and backward difference equations, which are more difficult to be dealt with, due to the adaptability of controller and the temporal correlation caused by simultaneous input delay and Markovian jump.

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arXiv2020

Optimal control and stablilization for linear continuous-time mean-field systems with delay

This paper studies optimal control and stabilization problems for continuous-time mean-field systems with input delay, which are the fundamental development of control and stabilization problems for mean-field systems. There are two main contributions: 1) To the best of our knowledge, the present paper is first to establish the necessary and sufficient solvability condition for this kind of optimal control problem with delay, and to derive an optimal controller through overcoming the obstacle that separation principle no longer holds for multiplicative-noise systems; 2) For the stabilization problem, under the assumption of exact observability, we strictly prove thatthe system is stabilizable if and only if the algebraic Riccati equation has a unique positive definite solution.

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arXiv2020

A New Approach for Solving Delayed Forward and Backward Stochastic Differential Equations

This paper is concerned with the decoupling of delayed linear forward-backward stochastic differential equations (D-FBSDEs), which is much more involved than the delay-free case due to the infinite dimension caused by the delay. A new approach of `discretization' is proposed to obtain the explicit solution to the D-FBSDEs. Firstly, we transform the continuous-time D-FBSDEs into the discrete-time form by using discretization. Secondly, we derive the solution of the discrete-time D-FBSDEs by applying backward iterative induction. Finally the explicit solution of the continuous-time D-FBSDEs is obtained by taking the limit to the solution of discrete-time form. The proposed approach can be applied to solve more general FBSDEs with delay, which would provide a complete solution to the stochastic LQ control with time delay.

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arXiv2020

Optimal Local and Remote Controls of Multiple Systems with Multiplicative Noises and Unreliable Uplink Channels

In this paper, the optimal local and remote linear quadratic (LQ) control problem is studied for a networked control system (NCS) which consists of multiple subsystems and each of which is described by a general multiplicative noise stochastic system with one local controller and one remote controller. Due to the unreliable uplink channels, the remote controller can only access unreliable state information of all subsystems, while the downlink channels from the remote controller to the local controllers are perfect. The difficulties of the LQ control problem for such a system arise from the different information structures of the local controllers and the remote controller. By developing the Pontyagin maximum principle, the necessary and sufficient solvability conditions are derived, which are based on the solution to a group of forward and backward difference equations (G-FBSDEs). Furthermore, by proposing a new method to decouple the G-FBSDEs and introducing new coupled Riccati equations (CREs), the optimal control strategies are derived where we verify that the separation principle holds for the multiplicative noise NCSs with packet dropouts. This paper can be seen as an important contribution to the optimal control problem with asymmetric information structures.

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