Abstract In this paper, a model‐free H ∞ control method is developed for discrete‐time linear parameter‐varying (LPV) systems by leveraging Q‐learning, which employs the data encompassing system states, control inputs, exogenous disturbance, and time‐varying convex hull rather than the dynamical model known a priori. A policy iteration algorithm presented via linear matrix inequality formed by such collected data is developed with convergence guarantee. Our analysis demonstrates that, in the presence of sufficiently rich disturbances, the attenuation level converges to a lower value than the traditional H ∞ control solution derived from an exact LPV model. A numerical example is demonstrated to verify the stabilization, disturbance attenuation, adaptivity, and convergence of the H ∞ attenuation level. Moreover, a continuous stirred tank reactor (CSTR) approximated by a discrete‐time LPV system is employed to show the practical potential of the developed model‐free approach.

Hongye Wang

Jiwei Wen

Haiying Wan

Huiwen Xue

Asian Journal of Control

Q‐learning‐based H∞ control for LPV systems

基于Q学习的LPV系统H∞控制

Abstract Trajectory tracking control of wheeled mobile robots (WMRs) is still a remarkable problem for many applications. In the present paper, a hybrid control is presented based on dynamic and kinematic equations of motion for wheeled mobile robots in the presence of the sum of the external disturbances and parametric uncertainty. The designed control for the WMR utilizes control and guidance to reach the reference path. In many studies, a control strategy is normally employed for WMR. However, in this study, hybrid control was used for the mentioned purpose. Akin to other studies, the kinematic control scheme here was based on the predictive control, and the dynamic control scheme was designed based on the robust control. Therefore, in this article, having introduced the kinematic model, a nonlinear predictive control was proved and designed. In the next step, a finite‐time integral type terminal sliding mode control (FITSMC) was designed based on the nonlinear dynamic model in order to automatically adjust the control gain and eliminate online disturbances and destructive chattering phenomena completely. In particular, a finite‐time disturbance observer was designed to estimate the external disturbances. The proof of the new proposed control scheme was presented using Lyapunov stability theory and numerical results. The mentioned integrated scheme, including predictive control (outer loop) and nonlinear adaptive control (inner loop), ensures the convergence and optimal tracking performance of all signals, as a result of which the tracking errors can arbitrarily converge to the origin in a finite time. In the final step, the simulation results were presented to show the effectiveness of the proposed scheme using MATLAB software, and the introduced control design was compared with a similar controller quantitatively and qualitatively.

Fahimeh Kordi

Saleh Mobayen

Hamidreza Rezaalikhani

Javad Nikoukar

Hybrid trajectory tracking control of wheeled mobile robots using predictive kinematic control and dynamic robust control

基于预测运动学控制和动态鲁棒控制的轮式移动机器人混合轨迹跟踪控制

Abstract In this paper, the finite‐time stability and stabilization of nonlinear systems with delays is studied, via a Takagi–Sugeno approach. By using a novel Lyapunov–Krasovskii functional and introducing some fuzzy free‐weighting matrices, sufficient conditions are derived, for bounded and differentiable time‐varying delays in terms of an upper bound of the delay derivatives. Then, we achieve closed‐loop stabilization in finite time through an efficient parallel distributed compensation design. The sufficient conditions are formulated as linear matrix inequalities to achieve the desired performance. Finally, the proposed methodology is applied to various case studies, highlighting its significance.

Nabil El Fezazi

Mohamed Fahim

Said Idrissi

Rashid Farkous

Teresa Alvarez

El Houssaine Tissir

New delay‐dependent finite‐time stabilization of Takagi–Sugeno fuzzy approaches for delayed nonlinear systems

新的依赖于延迟的有限时间稳定化方法：针对延迟非线性系统的Takagi-Sugeno模糊方法

Abstract In real‐time processes, time delays are inherent due to various factors, such as delays in volume, mass, and information transfer, leading to a deterioration in process performance and stability. Therefore, this paper proposes a fractional‐order tilted integral derivative (TID) controller design for stable and unstable fractional‐order processes with time delay, where the optimal controller parameters are designed using a deterministic approach. An inner loop controller is designed using stability analysis and a graphical approach for unstable fractional‐order time delay processes. The proposed approach offers flexibility and fine‐tuning in designing the controller for a specific application. A systematic reference to the disturbance ratio is carried out to assess the disturbance handling capacity of the proposed controller. It shows the sensitivity of the designed controller against disturbances in the frequency spectrum graphically. Numerous performance indices and time‐domain parameters are computed and compared with state‐of‐the‐art techniques to analyze the efficacy. Furthermore, it is validated on the experimental setup of a four‐tank system. Simulation and experimental results demonstrate that the proposed approach outperforms recent techniques in terms of process control and disturbance rejection.

Gnaneshwar K

Rishika Trivedi

Sudeep Sharma

Prabin Kumar Padhy

A frequency domain fractional order tilted integral derivative controller design for fractional order time delay processes

分数阶时滞过程的频域分数阶倾斜积分微分控制器设计

Abstract In the real‐world environment, the path planning method of tracked robot is widely studied when driving on uneven terrain. How to solve the problem that the traditional path planning algorithm cannot adapt to uneven terrain because of the constraints of obstacle avoidance and path length is a challenge for tracked robots. In this paper, a stability‐based path planning framework for tracked robot is proposed to reduce the risk of rollover when the tracked robot passes through uneven terrain. First, a virtual plane method is proposed to estimate the attitude of tracked robot. Second, on this basis, a dynamic high‐stability path evaluation algorithm for tracked robot based on force angle stability margin (FASM) is proposed, which transforms the stability‐based path planning problem into a hypergraph problem. Moreover, considering that the optimization problem is strongly nonlinear and nonconvex, a hybrid algorithm of covariance matrix adaptive evolution strategy (CMAES) and Levenberg–Marquardt (LM) is designed under the framework of generalized graph optimization (G2O) to improve the solution efficiency. Finally, simulation and experiments show that the stability‐based path planning framework can effectively plan the high‐quality path, and the maximum stability of the tracked robot is 0.9156 when the robot crosses uneven terrain using optimal path 2.

Jiangbo Zhao

Jiaquan Zhang

Hanze Liu

Junzheng Wang

Zhihua Chen

Path planning for a tracked robot traversing uneven terrains based on tip‐over stability

基于倾覆稳定性的履带机器人穿越不平地形的路径规划

Abstract Aerodynamic parameter estimation involves modeling both force and moment coefficients along with the computation of stability and control derivatives from recorded flight data. Classical methods like output, filter, and equation errors apply extensively to this problem. Machine learning approaches like artificial neural networks (ANNs) provide an alternative to model‐based methods. This work presents a novel aerodynamic parameters estimation technique involving the fusion of two of the most popular machine learning methods. The process uses biologically inspired optimization techniques, the artificial bee colony (ABC) optimization with the widely used ANN for simulated data contaminated with the noise of varying intensity (5%, 10%) and for real aircraft while considering system and measurement uncertainty. Combining ABC and ANN results in a novel and promising method that can address the sensor noise challenges of system identification and parameter estimation. Comparing the proposed approach's results with other benchmark estimation techniques like Least Square and Filter Error Methods established its efficacy. Furthermore, the feasibility of the proposed hybrid method in extracting the stability and control variables from the stable aircraft kinematics is shown even with insufficient information in its data history.

Prashant Kumar

Sarvesh Kumar Sonkar

Riya Catherine George

Deepu Philip

Ajoy Kanti Ghosh

Data‐driven approach for estimating longitudinal aerodynamic parameters using neural artificial bee colony fusion algorithm

基于神经人工蜂群融合算法的数据驱动纵向气动参数估计方法

Abstract In this paper, the robustness of global exponentially stable (ES) linear time‐invariant (LTI) systems with feedback control protocols is examined under the influence of random disturbances (RDs). For a given LTI system with global ES, a state feedback (SF) control protocol and a output feedback (OF) control protocol are proposed to keep the robustness of the discussed system, respectively. Meanwhile, how much the intensity of RDs that LTI system can withstand is obtained by the transcendental equation, in which the feedback gains are also designed and calculated by a proposed iterative algorithm. The theoretical analysis results demonstrate that the perturbed LTI systems may remain ES when the RDs are smaller than the upper bounds obtained in this paper. Finally, three cases are proposed to illustrate the effectiveness of the theoretical research.

Shifan Wen

Wanpeng Zhang

Wenxiang Fang

Robustness of linear time‐invariant systems with feedback control protocols under random disturbances

随机扰动下具有反馈控制协议的线性时不变系统的鲁棒性

Abstract In this paper, an innovative adaptive dynamic programming (ADP) algorithm with fast convergence speed is designed for the optimal containment control problem of discrete‐time linear multi‐agent systems. Precisely, a quadratic input energy cost function, including local containment error information and actuator information in the neighborhood, is designed for each follower. Solving the stationary condition of the cost function, the optimal containment controllers are obtained. Traditional ADP methods use actor–critic neural networks to approximate optimal costs and control strategies, it is time‐consuming to solve large‐scale multi‐agent problems due to the computational complexity of neural networks. In order to seek faster convergence speed of optimal containment control without knowing the model information, the fast ADP algorithm framework is designed, it is proved theoretically that the convergence speed is determined by some configurable parameters, and the whale optimization algorithm is employed to globally optimize the parameters of given spaces to derive the optimal configuration. Finally, numerical simulation results are given to verify the effectiveness of the designed algorithm.

Ao Cao

Fuyong Wang

Zhongxin Liu

Zengqiang Chen

Optimal containment control for multi‐agent systems using fast adaptive dynamic programming

多智能体系统的最优包容控制利用快速自适应动态规划

Abstract This paper studies an active fault‐tolerant control problem for multi‐UAV (unmanned aerial vehicle) system with time‐varying topology subject to actuator failures. A polytopic model is used to construct the time‐varying topological structure. Based on the quantitative estimation method of actuator faults' upper limit, an adaptive fault‐tolerant tracking control strategy is established by an active adjusting control parameters to compensate for unknown actuator faults, so as to obtain consensus tracking under time‐varying topology. Furthermore, the comparison simulations with the traditional control algorithm are given to demonstrate the effectiveness of the obtained results. The tracking control strategy in this paper has better fault tolerance performance with short tracking time and superior robustness.

Lijing Dong

Ying Xie

Chongchong Han

Shengli Du

Active fault‐tolerant control of multi‐unmanned aerial vehicle system with time‐varying topology

多无人机系统时变拓扑下的主动容错控制

Abstract This paper presents the development of the dynamical model of a planar vertical take‐off and landing (PVTOL) carrying a suspended load. The complete model is obtained using the Euler–Lagrange approach. Furthermore, the synthesis of a nonlinear control is presented that stabilizes the vehicle to a desired position, and the load is stabilized as well. The stability is obtained using LaSalle invariance theorem. The performance of the obtained controller is shown in numerical simulations.

Rogelio Lozano

Ivan Gonzalez‐Hernandez

Sergio Salazar

Samantha Calderon

Nonlinear control of a planar vertical take‐off and landing with a slung load

平面垂直起降带悬挂负载的非线性控制

《亚洲控制杂志》是亚洲控制协会（ACA）和中国自动控制学会（CACS）的附属期刊，是起源于亚太地区的第一本国际期刊。 《亚洲控制杂志》发表关于控制领域原创理论和实践研究与发展的论文，涉及控制理论及其应用的各个方面。该杂志每年出版六期，旨在成为整个亚洲控制社区的重要平台WORLD.THE JOURNAL 提供了一个论坛，控制研究人员和从业人员可以在此交流控制领域最新进展的知识和经验，并为对这一不断发展的领域感兴趣的其他学科的学生和经验丰富的研究人员发挥教育作用。期刊范围广泛。主题包括：控制系统和组件的理论和设计，包括：使用几何、最优、随机和非线性方法的鲁棒和分布式控制博弈论和状态估计自适应控制，包括神经网络、学习、参数估计和系统故障检测人工智能、模糊和专家系统分层和人机系统考虑组件和系统可靠性的系统工程的所有部分新兴应用领域，例如：机器人、机电一体化用于计算机辅助设计、制造和控制各种工业过程的计算机、航天器和飞机、船舶、交通生物医学系统国民经济电力系统农业自然资源。

The Asian Journal of Control is an affiliated journal of the Asian Control Association (ACA) and the Chinese Association of Automatic Control (CACS), and it is the first international journal originating from the Asia-Pacific region. The journal publishes original theoretical and practical research papers in the field of control, covering all aspects of control theory and its applications. It is published six times a year and aims to be an important platform for the entire Asian control community. The journal provides a forum for control researchers and practitioners to exchange knowledge and experiences on the latest advancements in the field of control, and to educate students and experienced researchers from other disciplines interested in this evolving field. The scope of the journal is broad, including topics such as the theory and design of control systems and components, robust and distributed control using geometric, optimal, stochastic, and nonlinear methods; game theory and state estimation; adaptive control, including neural networks, learning, parameter estimation, and system fault detection; artificial intelligence, fuzzy and expert systems; hierarchical and human-machine systems; system engineering considerations for component and system reliability; and emerging application areas such as robotics, mechatronics, computer-aided design, manufacturing, and control of various industrial processes, spacecraft and aircraft, ships, transportation, biomedical systems, national economy, power systems, and agricultural natural resources.

《亚洲控制杂志》是亚洲控制协会（ACA）和中国自动控制学会（CACS）的附属期刊，是起源于亚太地区的第一本国际期刊。该杂志发表关于控制领域原创理论和实践研究与发展的论文，涵盖控制理论及其应用的各个方面。每年出版六期，旨在成为整个亚洲控制社区的重要平台。期刊提供了一个论坛，供控制研究人员和从业人员交流控制领域最新进展的知识和经验，并为对这一不断发展的领域感兴趣的其他学科的学生和经验丰富的研究人员发挥教育作用。期刊范围广泛，主题包括：控制系统和组件的理论与设计，涉及鲁棒和分布式控制的几何、最优、随机和非线性方法；博弈论和状态估计；自适应控制，包括神经网络、学习、参数估计和系统故障检测；人工智能、模糊和专家系统；分层和人机系统；考虑组件和系统可靠性的系统工程的各个部分；以及新兴应用领域，例如机器人、机电一体化、计算机辅助设计、制造和控制各种工业过程的计算机、航天器和飞机、船舶、交通、生物医学系统、国民经济、电力系统和农业自然资源。

期刊	Asian Journal of Control
ISSN	1561-8625, 1934-6093
h-index	62
Journal Impact	2.56
国际分区	AUTOMATION & CONTROL SYSTEMS(Q2)
国内分区	计算机科学(4区)计算机科学自动化与控制系统(4区)