1,256 publications from this institution
In this paper, a Model Predictive Control (MPC) based tracking control design method for air-breathing hypersonic vehicles (AHVs) with input constraints is proposed. The tracking controller design problem is challenging because the relationship between flight dynamics and the control input is not so clear, especially when the input is subject to input constraints. Since the upper and lower bound of the constrained function are not symmetric, the anti-windup design method is not suitable. For the tracking control objective, an optimization based reference reconfiguration method is given. Through the reconfiguration, a new reference command, which can be realized by the constrained system, is constructed. A MPC based controller reconfiguration method is proposed with respect to the new command and input constraints. Finally, simulations are given to show the effectiveness of the proposed control method.
This paper is concerned with the problems of stability analysis and l 2-gain control for a class of two-dimensional (2D) nonlinear stochastic systems with time-varying delays and actuator saturation. Firstly, a convex hull representation is used to describe the saturation behavior, and a sufficient condition for the existence of mean-square exponential stability of the considered system is derived. Then, a state feedback controller which guarantees the resulting closed-loop system to be mean-square exponentially stable with l 2-gain performance is proposed, and an optimization procedure to maximize the estimation of domain of attraction is also given. All the obtained results are formulated in a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method.
The problem of H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control design for vibration reduction of a base isolated structure with limited wireless communication capacity is studied in this paper. The network under consideration is subjected to measurement quantization, signal transmission delay, and data packet dropout, which appear typically in a network environment. Based on Lyapunov-Krasovskii functional (LKF) theory, some delay-range-dependent conditions are established for the existence of desired controllers such that the resulting closed-loop system is asymptotically stable and its performance is kept within a prescribed level. Finally, some simulation results are given to illustrate the effectiveness of our method.
This paper investigates the problem of automatic speed tracking control of an electric vehicle (EV) that is powered by a permanent-magnet synchronous motor (PMSM). A reconfiguration scheme, based on higher order sliding mode (HOSM) observer, is proposed in the event of sensor faults/failures to maintain a good control performance. The corresponding controlled motor output torque drives EVs to track the desired vehicle reference speed for providing uninterrupted vehicle safe operation. The effectiveness of the overall sensor fault-tolerant speed tracking control is highlighted when an EV is subjected to disturbances like aerodynamic load force and road roughness using high-fidelity software package CarSim. Experiments with a 26-W, three-phase PMSM are presented to demonstrate the validity of the proposed fault-detection scheme.
This paper investigates the multipeakon dissipative behavior of the modified coupled two-component Camassa-Holm system arisen from shallow water waves moving. To tackle this problem, we convert the original partial differential equations into a set of new differential equations by using skillfully defined characteristic and variables. Such treatment allows for the construction of the multipeakon solutions for the system. The peakon-antipeakon collisions as well as the dissipative behavior (energy loss) after wave breaking are closely examined. The results obtained herein are deemed valuable for understanding the inherent dynamic behavior of shallow water wave breaking.
This paper discusses the problem of the fuzzy sliding mode control for a class of disturbed systems. First, a fuzzy auxiliary controller is constructed based on a feedback signal not only to estimate the unknown control term, but also participates in the sliding mode control due to the fuzzy rule employed. Then, we extend our theory into the cases, where some kind of system information can not be obtained, for better use of our theoretical results in real engineering. Finally, some typical numerical examples are included to demonstrate the effectiveness and advantage of the designed sliding mode controller.
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This paper considers the design of an H ∞ controller for tool point control of a hydraulically actuated knuckle boom crane. The paper describes the modelling of the crane's mechanical and hydraulic systems and a disturbance model. These are linearised and combined in a state-space model used for the controller design. The controller synthesis problem is to design (if possible) an admissible controller that solves the problem of robust regulation against step inputs with an H ∞ constraint based on the internal model principle. Simulation results are given to show the effectiveness of the method.
In this article, we address a convex optimisation approach to the problem of state-feedback H ∞ control design for vibration reduction of base-isolated building structures with delayed measurements, where the delays are time-varying and bounded. An appropriate Lyapunov–Krasovskii functional and some free-weighting matrices are utilised to establish some delay-range-dependent sufficient conditions for the design of desired controllers in terms of linear matrix inequalities. The controller, which guarantees asymptotic stability and an H ∞ performance, simultaneously, for the closed-loop system of the structure, is then developed. The performance of the controller is evaluated by means of simulations in MATLAB/Simulink.
Despite the fact that the zero-forcing block-linear equalizer (ZF-BLE) represents an entry-level solution to the joint-detection problem as applied to the TD-CDMA air-interface proposal for UMTS, it is nevertheless accompanied by a prohibitive computational complexity when supporting long data sequences, multiple users and channels with long impulse responses. A primary contributor to this computational complexity is the need to perform a Cholesky factorization of a sparse yet large correlation matrix. This paper presents a novel technique which exploits the pseudo block-Toeplitz nature of the Cholesky factor to derive an approximate triangular factorization, thereby allowing significant reductions in computational complexity and finite-precision effects at the expense of little or no degradation in performance. The technique is equally applicable to other block-based linear or decision-feedback joint-detection schemes whose operation relies on the Cholesky factorization.
The quadratic knapsack problem is an NP-hard optimization problem with many diverse applications in industrial and management engineering. However, computational complexities still remain in the quadratic knapsack problem. In this study, a logarithmic descent direction algorithm is proposed to approximate a solution to the quadratic knapsack problem. The proposed algorithm is based on the Karush–Kuhn–Tucker necessary optimality condition and the damped Newton method. The convergence of the algorithm is proven, and the numerical results indicate its effectiveness.
This paper deals with the problem of robust model predictive control (RMPC) for a class of linear time-varying systems with constraints and data losses. We take the polytopic uncertainties into account to describe the uncertain systems. First, we design a robust state observer by using the linear matrix inequality (LMI) constraints so that the original system state can be tracked. Second, the MPC gain is calculated by minimizing the upper bound of infinite horizon robust performance objective in terms of linear matrix inequality conditions. The method of robust MPC and state observer design is illustrated by a numerical example.
Current-based technique is an economic solution to detect bearing faults in drive-trains. Localized faults produce characteristic vibration frequencies. When an electric motor is supplied by a frequency-converter, the current response includes not only the fundamental and fault related frequencies but also higher harmonics from the inverter. This paper introduces a resonant filter to pick up frequency components caused by the localized faults. The bearing fault frequencies are calculated by bearing geometry and motor speeds. The filter frequencies are selected as a function of motor speeds. The filter is independent of the load condition, so it can work at different motor operating points to detect the localized bearing faults. Simulation results will verify the effectiveness of the proposed method.
In this article, the ultrafast tracking control for high-order discrete-time multiagent networks is investigated based on the predictive ability of agents. First, in view of the evolution of the original network dynamics, a distributed multistep prediction algorithm is established. Further, a control strategy containing predictive information is presented to achieve the ultrafast tracking control. Second, the problem of ultrafast tracking control with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> performance specification is dealt with. The obtained result indicates that the robustness of the whole multiagent network can be converted into the robustness of multiple separable subsystems. Finally, the optimal ultrafast static tracking control design is provided for the single-integrator network with sampled dynamics. Two simulation cases are carried out to verify the correctness of the obtained theoretical results.
This chapter examines the concept of the leader–follower formation for fractional-order multi-agent systems (FO-MASs) by utilizing dynamic event-triggered sliding mode control (SMC) method. First, a dynamic event-triggered mechanism (DETM) is designed relying on the combined measurement vector, in which an auxiliary variable is introduced to dynamically adjust the threshold for each fractional-order agent system. Unlike most existing event-triggered communication mechanisms, whose threshold parameters are always fixed, the threshold parameters in our designed event-triggered conditions can be dynamically adjusted according to the fractional-order dynamic rule. Numerical results show that the proposed DETM can achieve a better system performance in reducing the sampling frequency and the expected formation performance. Second, the leader–follower formation control problem is transformed into checking the asymptotic stability problem of the closed-loop system. In addition, due to the memorability of fractional calculus operators, a distinctive condition is established to avoid the occurrence of Zeno behavior reported in existing dynamic event-triggered schemes. Finally, a simulation example is presented to illustrate the effectiveness and feasibility of the dynamic event-triggered SMC method proposed in this chapter.
This paper considers the problem of robust stabilization and disturbance attenuation for a class of uncertain singularly perturbed systems with norm-bounded nonlinear uncertainties. It is shown that the state feedback gain matrices can be determined to guarantee the stability of the closed-loop system for all ε ϵ(0,∞). Based on this key result and some standard Riccati inequality approaches for robust control of singularly perturbed systems, a constructive design procedure is developed. For simplicity, the results are presented on the two-time-scale case; the extension of the results to multiple-time-scale is, however, straightforward.
