Prescribed Tracking Performance Research Articles

Adaptive prescribed performance tracking control of high‐order uncertain nonlinear systems under full‐state time‐varying constraints

AbstractIn this article, the adaptive finite time prescribed performance tracking control problem of a class of high‐order uncertain nonlinear systems under full state time‐varying constraints is addressed. By using the logarithmic function based nonlinear mapping technique rather than the barrier Lyapunov function based method, the obstacle of the full‐state constraints is resolved, and the undesired “feasibility conditions” in controller design are eliminated. By improving the prescribed performance control method, the initial value problem is overcome, and the finite‐time convergence of the tracking error can be ensured. Then, with the aid of the adding a power integrator method, an adaptive finite time prescribed performance tracking controller is designed, not only the tracking error but also the full states can be guaranteed to converge to a predefined constraint region in the predetermined time. Simulation examples are given to show the validness of the proposed control strategy.

Low-Complexity Control for Uncertain SbW Systems with Time-Varying Nonlinearity and Prescribed Tracking Performance

Low-Complexity Control for Uncertain SbW Systems with Time-Varying Nonlinearity and Prescribed Tracking Performance

Prescribed performance tracking control of multi-link robotic manipulator with uncertainties

<p style='text-indent:20px;'>This paper addresses the trajectory tracking problem with prescribed performance for a multi-link robotic manipulator subject to unknown dynamics and external disturbances. A predefined performance function is adopted to describe tracking errors' desired transient and steady-state performance. Then, the output error dynamics with performance constraints are transformed into an equivalent unconstrained system, whose stabilization is sufficient to guarantee the prescribed performance of the original system. An extended state observer with a friction model is designed to approximate unknown dynamics together with the unmeasurable velocity state, which extends the applicability of the proposed controller to manipulators with only position signals available. The friction model is lumped into it to improve the precision and velocity of estimation. It is proved via Lyapunov analysis that the proposed controller can theoretically guarantee the satisfaction of prescribed performance in the presence of uncertainties. The simulation results verify the reliability and effectiveness of the proposed method.</p>

Prescribed Performance Tracking Control for Nonlinear Multiagent Systems With Distributed Observation Errors Compensation

Prescribed Performance Tracking Control for Nonlinear Multiagent Systems With Distributed Observation Errors Compensation

Prescribed Performance Tracking for Uncertain MIMO Pure-feedback Systems with Unknown and Partially Non-constant Control Directions

Prescribed Performance Tracking for Uncertain MIMO Pure-feedback Systems with Unknown and Partially Non-constant Control Directions

Precise Tracking Control for Articulating Crane: Prescribed Performance, Adaptation, and Fuzzy Optimality by Nash Game.

Articulating crane (AC) is used in various industrial activities. The articulated multisection arm exacerbates nonlinearities and uncertainties, making the precise tracking control challenging. This study proposes an adaptive prescribed performance tracking control (APPTC) for AC to robustly fulfill the task of precise tracking control, with adaptation to resist time-variant uncertainties, whose bounds are unknown but lie in prescribed fuzzy sets. Particularly, a state transformation is applied to simultaneously track the desired trajectory and satisfy the prescribed performance. Adopting the fuzzy set theory to describe uncertainties, APPTC does not invoke any IF-THEN fuzzy rules. There is no linearizations, or nonlinear cancelation for APPTC, thus making it approximation free. The performance of the controlled AC is twofold. First, deterministic performance in fulfilling the control task is ensured by the Lyapunov analysis using uniform boundedness and uniform ultimate boundedness. Second, fuzzy-based performance is further improved by an optimal design, which seeks the optima of control parameters by formulating a two-player Nash game. The existence of Nash equilibrium is theoretically proved, and its acquisition process is given. The simulation results are provided for validations. This is the first endeavor that explores the precise tracking control for fuzzy AC.

Event‐triggered adaptive tracking control for nonlinear systems with input saturation and unknown control directions

AbstractThis article is concerned with event‐triggered adaptive tracking control design of strict‐feedback nonlinear systems, which are subject to input saturation and unknown control directions. In the design procedure, a smooth nonlinear function is employed to approximate the saturation function so that the controller can be designed under the framework of backstepping. The Nussbaum gain technique is employed to address the issue of the unknown control directions. A predetermined time convergent performance function and a nonlinear mapping technique are introduced to guarantee that the tracking error can converge in the predetermined time with a fast convergence rate and a high accuracy. Then the event‐triggered adaptive prescribed performance tracking control strategy is proposed, which not only ensures the boundedness of all the closed‐loop signals and the convergence of tracking error but also reduces the communication burden from the controller to the actuator. At last, the simulation study further tests the availability of the proposed control strategy.

Robust adaptive flexible prescribed performance tracking and vibration control for rigid–flexible coupled robotic systems with input quantization

Robust adaptive flexible prescribed performance tracking and vibration control for rigid–flexible coupled robotic systems with input quantization

Event-triggered dynamic prescribed performance control for oxygen stoichiometry and stack temperature in PEM fuel cell systems with actuators faults

Oxygen stoichiometry (OS) and stack temperature (ST) significantly affect the output performance and durability of proton exchange membrane fuel cells. This paper investigates the prescribed performance tracking control strategy of OS and ST under external disturbances, modeling errors, actuators faults and limited communication resources. The total disturbances are compensated by a variable-bandwidth extended state observer to simplify the control design and enhance the system robustness. To tolerate excessive disturbances and relax the strict requirement on the initial conditions, a new event-triggered adaptive sliding mode controller that integrates modified dynamic performance constraints and nonsingular error transformation is developed to ensure the user-designed transient and steady-state performance constraints, while saving the communication costs and avoiding the chattering and jump in control signals. The numerical validation results under combined working scenarios indicate that the proposed controller always ensures the preset error constraints and possesses superior performance in tracking the optimal OS value 2 and the optimal ST value 353.15K than other three representative controllers, with the integral absolute errors of 0.732 for OS tracking and 12.94 for ST tracking; besides, it achieves satisfactory robustness to uncertain model parameters and relatively large initial tracking errors.

A novel network-based adaptive fault-tolerant control of switched nonlinear systems subject to multiple faults under prescribed performance

It is the first report about fault-tolerant-based prescribed performance control of switched nonlinear systems under multiple faults. The concerned faults include not only external faults but also actuator faults. In the process of backstepping control design, prescribed performance control is fully considered, and the combination of unknown nonlinear functions is estimated by multi-dimensional Taylor network. Finally, the developed adaptive fault-tolerant control strategy guarantees the boundedness of all controlled signals while prescribed tracking performance is satisfied. In an effort to further manifest the validity of the fault-tolerant controller, a numerical simulation and a practical simulation are introduced.

Finite-time prescribed performance tracking control of seeker stabilized platform in the discrete-time domain

Current prescribed performance control (PPC) focuses on continuous-time systems, while this article proposes a novel discrete-time version of PPC for finite-time tracking of seeker stabilized platform in the discrete-time domain. Firstly, the newly developed performance functions are employed to impose finite-time prescribed performance on tracking errors. After that, a type of stabilization functions with respect to transformed errors are constructed for back-stepping controllers designing. On this basis, transformed errors are indirectly stabilized, and thus the pursued prescribed transient and steady-state behaviors are ensured for tracking errors via Lyapunov synthesis. Different from existing sliding-mode-control based discrete-time PPC, the addressed approach eliminates the sliding-mode structure and hence avoids high frequency chattering caused by such framework. Finally, compared simulations validate the superiority over existing methods.

Optimized Adaptive Fuzzy Security Control of Nonlinear Systems With Prescribed Tracking Performance.

This article studies the optimized fuzzy prescribed performance control problem for nonlinear nonstrict-feedback systems under denial-of-service (DoS) attacks. A fuzzy estimator is delicately designed to model the immeasurable system states in the presence of DoS attacks. To achieve the preset tracking performance, a simper prescribed performance error transformation is constructed considering the characteristics of DoS attacks, which helps obtain a novel Hamilton-Jacobi-Bellman equation to derive the optimized prescribed performance controller. Furthermore, the fuzzy-logic system, combined with the reinforcement learning (RL) technique, is employed to approximate the unknown nonlinearity existing in the prescribed performance controller design process. An optimized adaptive fuzzy security control law is then proposed for the considered nonlinear nonstrict-feedback systems subject to DoS attacks. Through the Lyapunov stability analysis, the tracking error is proved to approach the predefined region by the preset finite time, even in the presence of DoS attacks. Meanwhile, the consumed control resources are minimized due to the RL-based optimized algorithm. Finally, an actual example with comparisons verifies the effectiveness of the proposed control algorithm.

Neuroadaptive Performance Guaranteed Control for Multiagent Systems With Power Integrators and Unknown Measurement Sensitivity.

This article investigates the adaptive performance guaranteed tracking control problem for multiagent systems (MASs) with power integrators and measurement sensitivity. Different from the structural characteristics of existing results, the dynamic of each agent is a power exponential function. A method called adding a power integrator technique is introduced to guarantee that the consensus is achieved of the MASs with power integrators. Different from existing prescribed performance tracking control results for MASs, a new performance guaranteed control approach is proposed in this article, which can guarantee that the relative position error between neighboring agents can converge into the prescribed boundary within preassigned finite time. By utilizing the Nussbaum gain technique and neural networks, a novel control scheme is proposed to solve the unknown measurement sensitivity on the sensor, which successfully relaxes the restrictive condition that the unknown measurement sensitivity must be within a specific range. Based on the Lyapunov functional method, it is proven that the relative position error between neighboring agents can converge into the prescribed boundary within preassigned finite time. Finally, a simulation example is proposed to verify the availability of the control strategy.

Observer-Based Sensor Fault-Tolerant Control With Prescribed Tracking Performance for a Class of Nonlinear Systems

Observer-Based Sensor Fault-Tolerant Control With Prescribed Tracking Performance for a Class of Nonlinear Systems

Adaptive predefined-time fault-tolerant attitude tracking control for rigid spacecraft with guaranteed performance

In this article, the attitude tracking problem for rigid spacecraft systems with the consideration of actuator fault, input saturation, inertia uncertainties. and external disturbances is investigated. By introducing a shifting function, the requirement for accurate values of the initial tracking errors has been removed. A novel adaptive prescribed performance function is developed to enable the relaxation and recovery of the performance bounds under the different conditions of the shifted tracking error. Then, an error transformation is employed to convert the problem of prescribed performance tracking into the stabilization problem of a new system. Subsequently, an adaptive controller is designed based on a nonsingular predefined-time sliding mode manifold and an auxiliary system. The proposed controller ensures a predefined-time convergence with prescribed static and transient performance for the tracking error. The stability analysis of the proposed attitude controller is rigorously established using Lyapunov methods. Finally, numerical simulations are conducted to exhibit the efficacy and superiority of the propounded scheme.

Adaptive finite-time prescribed performance tracking control for hydraulic servo systems with friction compensation

Hydraulic systems present numerous challenges in the development of high-performance tracking controllers due to their highly nonlinear characteristics and heavy modeling uncertainties. Addressing this issue, this paper presents a friction compensation-based finite-time tracking control strategy with prescribed performance constraints. The system model is first derived, taking into consideration the nonlinear behaviors and potential uncertainties encountered in practical scenarios. Then, an adaptive finite-time prescribed performance controller is synthesized based on the backstepping framework. A novel form of finite-time performance function is introduced to constrain the tracking error, which provides the closed-loop system with a less complex guarantee of finite-time convergence and can also deliver the required transient performance and steady-state accuracy. Additionally, given the impact of uncertainty terms and the difficulty in obtaining the virtual command derivative, we employ neural networks (NNs) to estimate unknown dynamics and introduce command filters to acquire the intermediate signals, simplifying the backstepping control design process. Theoretical analysis indicates that the proposed control strategy can achieve the desired tracking performance and ensure the stability of the entire closed-loop system. Comparative numerical simulations are presented to confirm the usefulness of the suggested approach.

Prescribed Performance Tracking Control Under Uncertain Initial Conditions: A Neuroadaptive Output Feedback Approach.

This work is concerned with the prescribed performance tracking control for a family of nonlinear nontriangular structure systems under uncertain initial conditions and partial measurable states. By combining neural network and variable separation technique, a state observer with a simple structure is constructed for output-based finite-time tracking control, wherein the issue of algebraic loop arising from a nontriangular structure is circumvented. Meanwhile, by using an error transformation, the developed control scheme is able to ensure tracking with a prescribed accuracy within a pregiven time at a preassigned convergence rate under any bounded initial condition, eliminating the long-standing initial condition dependence issue inherited with conventional prescribed performance control methods, and guaranteeing the predeterminability of convergence time simultaneously. Two simulation examples also demonstrate the effectiveness of the presented control strategy.

Low-complexity prescribed performance tracking control for uncertain high-order nonlinear systems considering input quantization

Low-complexity prescribed performance tracking control for uncertain high-order nonlinear systems considering input quantization

Event-triggered adaptive prescribed performance tracking for nonlinear time-varying systems with unknown control directions

This article deals with the adaptive prescribed performance tracking for nonlinear time-varying systems. To handle multiple unknown control directions, a novel lemma is established by using a general class of Nussbaum functions. To handle unknown time-varying parameters, the congelation of variables method is employed. Different novel functions are introduced to achieve prescribed performance tracking and finite-time prescribed performance tracking, respectively. Meanwhile, the problem of explosion of complexity is avoided by utilizing the command filter and the compensation mechanism. For reasons of saving network resources and reducing communication burden, a new event-triggered mechanism is proposed, which can circumvent the Zeno behavior. Then, an event-triggered adaptive prescribed performance tracking control scheme is constructed and is extended to event-triggered finite-time adaptive prescribed performance tracking, both of which guarantee that all closed-loop signals are bounded and the trajectory of the tracking error can be limited to the prescribed region. Finally, the availability of the control scheme is demonstrated by two examples.

Global Consensus Tracking Control for High-Order Nonlinear Multiagent Systems With Prescribed Performance.

In this article, we investigate the prescribed performance tracking control problem for high-order nonlinear multiagent systems (MASs) under directed communication topology and unknown control directions. Different from most existing prescribed performance consensus control methods where certain initial conditions are needed to be satisfied, here the restriction related to the initial conditions is removed and global tracking result irrespective of initial condition is established. Furthermore, output consensus tracking is achieved asymptotically with arbitrarily prescribed transient performance in spite of the directed topology and unknown control directions. Our development benefits from the performance function and prescribed-time observer. Both theoretical analysis and numerical simulation confirm the validity of the developed control scheme.