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Quantization-Based Adaptive Actor-Critic tracking Control With tracking error constraints

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2018年第4期29卷 970-980页

作者： Fan, Quan-Yong Yang, Guang-Hong Ye, Dan Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

In this paper, the problem of adaptive actorcritic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

关键词： Actor-critic (AC) control input quantization neural network (NN) nonlinear systems tracking error constraints

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Finite-time tracking control of underactuated surface vehicle with tracking error constraints

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INTERNATIONAL JOURNAL OF VEHICLE DESIGN 2020年第1-4期84卷 77-99页

作者： Chen, Huizi Zhang, Dan Zhao, Meijiao Xie, Shaorong Shanghai Univ Sch Mech Engn & Automat 99 Shangda Rd Shanghai 200444 Peoples R China

This paper studies the finite-time tracking control of an underactuated surface vehicle (USV) subject to the lumped uncertainties including actuator faults, external disturbances, and plant uncertainties. A tracking controller with error constraints is given to derive the prescribed tracking performance for the vehicle. Subsequently, the adaptive neural network (NN) is adopted to estimate the lumped uncertainties. Meanwhile, an adaptive switching mechanism is devised to avoid chattering of state output and improve adaptation rate to compensate approximation error. Furthermore, a new performance function is introduced to obtain a clear indication of actual convergence time, and the nonlogarithmic transformation function (NTF) is constructed to solve the potential singularity problem in the logarithmic error mapping function. Some simulations have been presented to prove the excellent tracking performance of the developed method.

关键词： USV underactuated surface vehicle finite-time tracking control terminal hierarchical sliding mode control adaptive NN NTF nonlogarithmic transformation function prescribed performance adaptive switching mechanism actuator faults tracking error constraints

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Decentralized optimal tracking control for large-scale nonlinear systems with tracking error constraints

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2021年第7期35卷 1388-1403页

作者： Wang, Yujia Wang, Tong Yang, Xuebo Yang, Jiae Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150001 Peoples R China

In this article, a decentralized optimal tracking control strategy is proposed for a class of nonlinear systems with tracking error constraints by utilizing adaptive dynamic programming (ADP). It should be noted that ADP technology cannot be directly used to solve decentralized optimal tracking problem of large-scale interconnected nonlinear system with nonzero equilibrium points, since that an infinite domain performance index function may result in an unsolvable solution. In addition, by introducing a smooth function, the constrained tracking error is transformed into an unconstrained one. Then, the error dynamics and a new infinite domain performance index function are designed, such that ADP technology can be used. Following the designed performance index function, the tracking error can be ensured within a small neighborhood of zero. Finally, the feasibility and the effectiveness of the proposed decentralized optimal control scheme are verified through two simulation examples.

关键词： adaptive dynamic programming decentralized optimal tracking control tracking error constraints

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Dynamic learning from adaptive neural control for flexible joint robot with tracking error constraints using high-gain observer

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SYSTEMS SCIENCE & CONTROL ENGINEERING 2018年第3期6卷 177-190页

作者： Chen, Zhiguang Wang, Min Zou, Yongtao South China Univ Technol Sch Automat Sci & Engn Guangzhou Guangdong Peoples R China

This paper presents dynamic learning from adaptive neural control with prescribed tracking error performance for flexible joint robot (FJR) included unknown dynamics. Firstly, a system transformation method is introduced to convert the original FJR system into a normal system. As a result, only one neural network (NN) approximator is used to identify the uncertain system nonlinear dynamics and the verification on the convergence of neural weights is simplified extremely. To further solve the predefined performance issue, a performance function is introduced to describe a tracking error constraint and a error transformation technique is used to convert the constrained tracking control problem into the unconstrained stabilization of error system. By combining a high-gain observer and the backsteppig method, the adaptive neural controller is presented to stabilize the unconstrained error system. Under the satisfaction of the partial persistent excitation condition, the adaptive neural controller is shown to be capable of achieving unknown dynamics acquisition, expression and storage. Furthermore, a neural learning control with using the stored NN weights is proposed for the same or similar control task so that a time-consuming NN online adjustment process can be avoided and a better control performance can be obtained. Simulation results demonstrate the effectiveness of the proposed control method.

关键词： Adaptive neural control neural learning tracking error constraints PE condition flexible joint robot

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Trajectory tracking Control of Underactuated Surface Vessel With Output tracking error constraints 29

Trajectory Tracking Control of Underactuated Surface Vessel ...

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第29届中国控制与决策会议

作者： Shi-Lu Dai Chong Fang Shude He School of Automation Science and Engineering South China University of Technology

ISBN: (纸本)9781509046584

This paper studies the tracking control problem for underactuated surface vessel with unknown time-varying *** avoid the controller singularity problem,the constraints on output tracking errors of underactuated surface vessel are enforced in the control *** the help of error transformation functions,the constrained tracking control of the vessel is converted into the stabilization of the transformed error *** compensate for the effect of the external disturbances,disturbance observers are presented to estimate the unknown time-varying ***,disturbance-observer-based tracking control is developed to steer the vessel along a desired reference trajectory with guaranteeing the tracking errors within certain predefined *** performance of the proposed tracking control is demonstrated through simulation results.

关键词： Trajectory tracking underactuated vessels tracking error constraints time-varying disturbances

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Platoon Formation Control of USVs With Output tracking error constraints 8

Platoon Formation Control of USVs With Output Tracking Error...

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IEEE 8th International Conference on Underwater System Technology - Theory and Applications (USYS)

作者： Ye, Qingzhao He, Shude Dai, Shi-Lu South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China

ISBN: (纸本)9781538694053

In this paper, we investigate the platoon formation control problem for a group of unmanned surface vehicles exposed to external time-varying disturbances with output tracking error constraints, where the topology of the communication network is described by a spanning directed tree. To guarantee that the follower could preserve within the communication range between the follower and its predecessor while avoiding the collision with its predecessor, the line-of-sight (LOS) range is required to be constrained. By introducing a desired distance, the constraints on connectivity preserving and collision avoidance could be transformed into the constraints of LOS range error, i.e., the LOS range error is required to stay within a prescribed region composed of two constant bounds. To quantify the transient and steady-state performances of the orientation error and LOS range error, the tan-type barrier Lyapunov functions with exponential decaying boundary functions are employed to guarantee the satisfaction of the prescribed tracking error constraints. Since the vehicle system is exposed to the time-varying disturbances, the disturbance observers are incorporated into the controller such that the robustness of the control system is improved. Based on backstepping procedure, barrier Lyapunov functions, and disturbance observers, robust formation controller is proposed to ensure the prescribed tracking error constraints, i.e., the connectivity preserving as well as the collision avoidance constraints between the follower and its predecessor are also satisfied. Simulation results demonstrate the efficacy of the proposed control scheme.

关键词： Unmanned surface vehicles platoon formation control prescribed performance tracking error constraints

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Nonsingular finite-time heading tracking control of marine vehicles with tracking error constraints

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第6期361卷

作者： Liu, Yanli Sun, Yihua Hao, Li-Ying Dalian Maritime Univ Sch Marine Elect Engn Dalian 116026 Liaoning Peoples R China

This brief copes with the finite -time heading tracking control for marine vehicles. The tracking error constraints, stochastic disturbance and dead -zone output are simultaneously taken into consideration in the controlled systems. To manage the dead -zone output issue, a smooth approximation model is brought in to offset the nondifferentiable phenomena during the control, besides, the adaptive technique and the Nussbaum function are simultaneously integrated into the design. For the tracking error constraints, the prescribed performance functions (PPF) with error transformations are designed, and novel stochastic Barrier Lyapunov functions are constructed accordingly depending on the newly tracking errors to deal with the constrained tracking control issue. To avert the "differential explosion"issue in the backstepping, the improved first -order filter technique is invoked. The proposed finite -time heading tracking control tactic renders that all variables are bounded, meanwhile, the tracking errors are kept in the pregiven boundaries. The effectiveness of theory results is substantiated via simulations.

关键词： Heading tracking Finite-time control Performance function tracking error constraints Dead-zone output

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Finite Time Optimal Preactuation for Non-Minimum Phase Systems Considering Control Input and tracking error constraints

Finite Time Optimal Preactuation for Non-Minimum Phase Syste...

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IEEE Conference on Control Technology and Applications

作者： Wataru Ohnishi Thomas Beauduin Hiroshi Fujimoto The University of Tokyo Kashiwa Chiba Japan

To achieve perfect reference trajectory tracking, a plant with continuous time unstable zeros requires an infinite time preactuation. Albeit, this is practically infeasible, as typical high-precision motion systems target a short time finite preactuation. Truncating the control input to a limited time preactuation leads to undesirable tracking errors. This paper, thus, proposes a finite time preactuation method with an optimized state trajectory considering control input and tracking error constraints. The proposed method generates an optimal state trajectory for a given reference and finite time while explicitly considering the actuator, i.e. peak force, and stroke, i.e. maximum undershoot, limitations of the system. A multirate feedforward scheme is subsequently presented to obtain a discretized control input that perfectly tracks the designed optimal state trajectory. In comparison to conventional finite preactuation methods, the proposed approach reaches an order of magnitude lower tracking error bounds. Additionally, this finite time procedure attains, in contrast to conventional optimization approaches, through a multirate feedforward formulation, perfect tracking during the main motion after preactuation.

关键词： tracking error constraints contrast conventional optimization approaches

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Neural Control of Robotic Manipulator with Guaranteed tracking Precision and Velocity constraints 36

Neural Control of Robotic Manipulator with Guaranteed Tracki...

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第36届中国控制会议

作者： Min Wang Yanwen Zhang School of Automation Science and Engineering Guangzhou Key Laboratory of Brain Computer Interaction and ApplicationsSouth China University of Technology

ISBN: (纸本)9781538629185

This paper focuses on adaptive neural control design for n-link robot manipulator systems in the presence of tracking error and velocity state constraints.A performance function is utilized to characterize the prescribed performance of the tracking error.A new transformed function is used to guarantee that tracking errors satisfy the prescribed performance and the velocity states are not to violate their *** designed transformed function is not only of simple structure,but also overcomes the possible high-gain control problem caused by the existing transformed ***,a novel adaptive neural control scheme is proposed by combining independently Lyapunov functions *** proposed scheme guarantees all closed-loop signals are uniformly ultimately bounded,the output tracking errors satisfy the prescribed transient and steady-state tracking performances,and the velocity states are ensured to remain in the predefined bounded *** studies on a 2-link robot are performed and the effectiveness of the proposed scheme is illustrated by simulation results.

关键词： Adaptive Neural Control tracking error constraints State constraints Performance Transformation Robot Manipulators

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Delegated asset management, investment mandates, and capital immobility

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JOURNAL OF FINANCIAL ECONOMICS 2013年第2期107卷 239-258页

作者： He, Zhiguo Xiong, Wei Univ Chicago Booth Sch Business Chicago IL 60637 USA NBER Cambridge MA 02138 USA Princeton Univ Princeton NJ 08540 USA

This paper develops a model to explain the widely used investment mandates in the institutional asset management industry based on two insights: first, giving a manager more investment flexibility weakens the link between fund performance and his effort in the designated market, and thus increases agency cost. Second, the presence of outside assets with negatively skewed returns can further increase the agency cost if the manager is incentivized to pursue outside opportunities. These effects motivate narrow mandates and tight tracking error constraints to most fund managers except those with exceptional talents. Our model sheds light on capital immobility and market segmentation that are widely observed in financial markets, and highlights important effects of negatively skewed risk on institutional incentive structures. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Institutional frictions Negatively skewed risk tracking error constraints Market segmentation

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