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1.
This paper studies the consensus problem for a class of nonlinear multi-agent systems with asymmetric time-varying output constraints and completely unknown non-identical control directions. Firstly, in order to deal with the problem of asymmetric time-varying output constraints, the original output-constrained multi-agent systems are transformed into new unconstrained multi-agent systems by constructing the state transformation for each agent. Secondly, the emergence of multiple Nussbaum-type function terms is avoided by introducing novel sliding-mode-esque auxiliary variables and consensus estimate variables, which allows the control directions to be completely unknown non-identical. Thirdly, a novel control strategy is proposed by combining novel variables with state transformation method for the first time, which makes the design of distributed consensus protocol more concise. Through Lyapunov stability analysis, the proposed distributed protocol ensures that the output constraints are never violated and the consensus can be achieved asymptotically. Finally, a practical simulation example is given to demonstrate the effectiveness of the proposed distributed consensus protocol.  相似文献   

2.
A practical finite-time command filtered backstepping control method is proposed in this paper for a microwave plasma chemical vapor deposition (MPCVD) reactor system. The MPCVD reactor system is modeled as a coupled nonlinear system with unknown control direction functions and unknown nonlinearities. To address the unknown nonlinearities, novel practical finite-time command filters are proposed to construct the estimations of such nonlinearities. On the other hand, an equivalent augmented system of the reactor system is proposed to address the design challenges that posed by the system unknown control direction functions. Additionally, it can be concluded that the proposed control method ensures practical finite-time stability of the reactor system tracking errors by using the practical finite-time Lyapunov stability criterion. Finally, the effectiveness of the approach is demonstrated through the simulation results.  相似文献   

3.
In this paper, a novel backstepping-based adaptive dynamic programming (ADP) method is developed to solve the problem of intercepting a maneuver target in the presence of full-state and input constraints. To address state constraints, a barrier Lyapunov function is introduced to every backstepping procedure. An auxiliary design system is employed to compensate the input constraints. Then, an adaptive backstepping feedforward control strategy is designed, by which the tracking problem for strict-feedback systems can be reduced to an equivalence optimal regulation problem for affine nonlinear systems. Secondly, an adaptive optimal controller is developed by using ADP technique, in which a critic network is constructed to approximate the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation. Therefore, the whole control scheme consists of an adaptive feedforward controller and an optimal feedback controller. By utilizing Lyapunov's direct method, all signals in the closed-loop system are guaranteed to be uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed strategy is demonstrated by using a simple nonlinear system and a nonlinear two-dimensional missile-target interception system.  相似文献   

4.
This paper addresses the stabilization issue of linear time delay system with input saturation and distinct input delays via predictor feedback boundary control algorithm by employing transport partial differential equations (PDEs). First, the addressed ordinary differential equation (ODE) system with input delay is equivalently represented as a cascade of an ODE and transport PDEs. Second, by employing the backstepping Volterra integral transformation technique, the equivalent cascade system is transformed into a stable target system, whose kernels are solved by the constraints satisfying transport PDEs. Third, based on the boundary conditions of the obtained invertible transformation, the proposed feedback control law can be formulated. Fourth, by applying semigroup operator theory, the well-posedness of the resulting system is proved and consequently, novel exponential stability conditions of the addressed system are established. Then, the domain of attraction region under the given actuator saturation constraints is estimated with the help of the solution of obtained stability conditions. Finally, a demonstrative simulation example is offered to verify the feasibility and usefulness of the results.  相似文献   

5.
In this paper, a novel adaptive control is investigated for robotic manipulators to unify the study of predefined performance control, input saturation and dynamic uncertainties. The focus is to achieve three user-defined performance indices of the closed-loop system with simultaneous existence of input constraints and model uncertainties, that is overshoot, precision within prescribed finite time and predefined steady-state error. To ensure the performance constraints, an error transformation is constructed for the manipulators by two auxiliary functions and embedded into the barrier Lyapunov function (BLF) in the backstepping analysis. Furthermore, the adaptive control strategies and the adaptive anti-saturation compensator are, respectively, developed to address the dynamics uncertainties and the actuator saturation. The Lyapunov analysis is employed to show that all the closed-loop signals are bounded. Finally, simulation studies and experiments on Baxter robot demonstrate the effectiveness of the proposed method.  相似文献   

6.
The optimal control strategy constructed in the form of a state feedback is effective for small state perturbations caused by changes in modeling uncertainty. In this paper, we investigate a robust suboptimal feedback control (RSPFC) problem governed by a nonlinear time-delayed switched system with uncertain time delay arising in a 1,3-propanediol (1,3-PD) microbial fed-batch process. The feedback control strategy is designed based on the radial basis function to balance the two (possibly competing) objectives: (i) the system performance (concentration of 1,3-PD at the terminal time of the fermentation) is to be optimal; and (ii) the system sensitivity (the system performance with respect to the uncertainty of the time-delay) is to be minimized. The RSPFC problem is subject to the continuous state inequality constraints. An exact penalty method and a novel time scaling transformation approach are used to transform the RSPFC problem into the one subject only to box constraints. The resulting problem is solved by a hybrid optimization algorithm based on a filled function method and a gradient-based algorithm. Numerical results are given to verify the effectiveness of the developed hybrid optimization algorithm.  相似文献   

7.
In this paper we investigate the observation and stabilization problems of a linear plant subject to network constraints and partial state knowledge, making use of the event-triggered technique. In order to address these problems, an impulsive observer is designed. Sufficient conditions are given to ensure a milder version of separation principle for linear systems controlled via an event-triggered controller. The proposed observer ensures practical state estimation, while the corresponding dynamic controller ensures practical stabilization. The sampling and the transmission of the output and the input are done asynchronously. The dynamic controller is tested in simulation on the linearized inverted pendulum.  相似文献   

8.
This paper presents a novel approach to address the decentralized fault tolerant model predictive control of discrete-time interconnected nonlinear systems. The overall system is composed of a number of discrete-time interconnected nonlinear subsystems at the presence of multiple faults occurring at unknown time-instants. In order to deal with the unknown interconnection effects and changes in model dynamics due to multiple faults, both passive and active fault tolerant control design are considered. In the Active fault tolerant case an online approximation algorithm is applied to estimate the unknown interconnection effects and changes in model dynamics due to multiple faults. Besides, the decentralized control strategy is implemented for each subsystem with the model predictive control algorithm subject to some constraints. It is showed that the proposed method guarantees input-to-state stability characterization for both local subsystems and the global system under some predetermined assumptions. The simulation results are exploited to illustrate the applicability of the proposed method.  相似文献   

9.
This paper deals with the output consensus problem for uncertain nonstrict-feedback leader-follower multi-agent systems with predefined performance. A distributed event-triggered control strategy with dynamic threshold is proposed to update the actual control input and alleviate the computation burden of the communication procedure effectively. The unknown nonstrict-feedback structures are addressed by using the property of radial basis function neural networks. It is worth noting that in practical applications, the predefined performance often alternates between constrained and unconstrained cases in some extreme situations. To overcome this challenge, a novel coordinate transformation technique is incorporated to tackle both the two cases with and without performance constraint in a unified manner. As a result, the proposed event-triggered control approach ensures that the output consensus errors converge to zero asymptotically, and all the signals in the closed-loop system are bounded. Finally, the effectiveness of the proposed protocol is demonstrated by the simulation results.  相似文献   

10.
This paper investigates the tracking control problem for output constrained stochastic nonlinear systems under quantized input. The main challenge of considering such dynamics lies in the fact that theirs have both input and output constraints, making the standard backstepping technique fail. To address this challenge, the introduction of nonlinear mapping transforms the constrained nonlinear systems into unconstrained nonlinear systems, which not only avoids the emergence of feasibility conditions but also simplifies the structure of designed controller. The obstacle caused by quantized input is successfully resolved by exploiting the decomposition of hysteresis quantizer. Additionally, the uncertain nonlinearities are approximated by fuzzy logic systems during the control design process. Under the proposed quantized tracking control scheme, the output tracking error converges to an arbitrarily small neighborhood of origin and all signals in the closed-loop system remain bounded in probability. Simultaneously, it can make sure that the output constraint isn’t violated. Ultimately, both a numerical example and a practical example are provided to clarify the effectiveness of the control strategy.  相似文献   

11.
This paper presents a fixed-time composite neural learning control scheme for nonlinear strict-feedback systems subject to unknown dynamics and state constraints. To address the problem of state constraints, a new unified universal barrier Lyapunov function is proposed to convert the constrained system into an unconstrained one. Taking the unconstrained system, a modified fixed-time convergence state predictor is explored, enabling the prediction error for compensating the neural adaptive law to be obtained and improving the learning ability of online neural networks (NNs). Without employing fractional power terms or a complicated switching strategy to build the control law, a new method of constructing a smooth fixed-time dynamic surface control scheme is proposed. This overcomes the potential singularity problem and the explosion of complexity often encountered in fixed-time back-stepping designs. The representative features of our design are threefold. First, it is free of the fractional power terms, yet offers fixed-time convergence. Second, it addresses the state constraint problem without requiring a feasibility check. Third, it constructs a new state-predictor and enhances the approximation accuracy of NNs. The stability of the proposed control scheme is analyzed using the Lyapunov technique. Simulation results are presented to illustrate the effectiveness of the proposed controller.  相似文献   

12.
The main objective of this paper is to present a non-predictive method in the design of nonlinear multi-input multi-output (MIMO) control systems with the presence of constraints that are determinant in practical conditions, namely, the frequency bandwidth limitation of the actuation system and saturation boundaries in control commands. If these constraints are applied in the non-predictive control design problem, it is not possible to simultaneously satisfy Lyapunov stability and actuation constraints, analytically. Instead of model-predictive-based algorithms, which in most cases are computationally expensive, this paper proposes an algorithm based on synthetic Lyapunov stability. In this technique, by defining an intelligent filter applied to the system desired trajectories, defining intelligent proximity coefficients in decoupled inequalities resulting from Lyapunov stability, and determining the admissible boundaries of control commands, a space of regulatory parameters is generated. By appropriately adjusting these parameters based on statistical analysis conducted on the overall dynamics of the system, the Lyapunov stability is guaranteed, and the mentioned control constraints are not violated. In summary, the proposed control algorithm includes the formulation of discrete-time dynamics of sliding functions, the presentation of the procedure of defining and adjusting the control algorithm parameters with the proposed synthetic stability criterion, and the calculation of control inputs based on constraints imposed on the problem. Finally, the algorithm is applied to a cart moving in the X-Y plane, including two rigid cooperative arms that are carrying a load. The most important features of synthetic Lyapunov stability compared to the model predictive-based method are its small computational load and its acceptable performance in satisfying both the Lyapunov stability conditions and determinant control constraints in more realistic situations.  相似文献   

13.
This article studies the neuroadaptive full-state constraints control problem for a class of electromagnetic active suspension systems (EASSs). First, the original constraint system with arbitrary initial values is transformed into a new constraint system with zero initial values by using the shift function method. Then, a new kind of cotangent-type nonlinear state-dependent transition function is constructed to solve the asymmetric time-varying full-state constraints control problem, which eliminates the limitation that the virtual controller needs to satisfy the feasibility conditions in the previous full-state constraints control based on Barrier Lyapunov Function (BLF) and Integral BLF. Furthermore, the neural networks (NNs) are used as nonlinear function approximators to deal with the unknown nonlinear dynamics of EASSs, a neuroadaptive full-state constraints control design method is proposed under the Backstepping recursive design framework. Finally, the effectiveness of the proposed method is verified by a simulation of EASSs with road disturbances.  相似文献   

14.
This study proposes two novel prescribed performance terminal sliding surfaces (PPTSSs) to address the fixed time stable bilateral teleoperation issue for a class of underwater manipulators with error constraints and input saturation. A general mathematical definition of the PPTSS method is first introduced, which can predetermine the convergence rate, steady-state error, and maximum overshoot. Moreover, the system settling time would have a fixed upper bound once the PPTSS is reached. An auxiliary system for saturation compensation is utilized to overcome the difficulties caused by actuator saturation. Moreover, two control schemes based on PPTSSs are proposed to handle error constraints and ensure the bound of global settling time is fixed. Finally, numerical simulation results are presented to demonstrate the effectiveness of the developed algorithms.  相似文献   

15.
This paper proposes a new adaptive region tacking control scheme with nonlinear error transformation for underwater vehicles based on barrier Lyapunov functions. In the new scheme, a redefinition of the tracking error is given by introducing nonlinear error transformation in prescribed performance control. Although the results created by the new scheme indicate a slight decrease in the tracking precision, the real tracking error will be still kept within the prescribed performance functions, while the control signals also become smoother, compared with the original prescribed performance control scheme. Then an approximation form of the control input with constraints, together with an improved Nussbaum function, is designed to derive the control law for underwater vehicles with thruster saturation and dead zone. Furthermore, a new velocity error variable is given by introducing an auxiliary variable to compensate the effect from thruster saturation. Finally, it is proved that the nonlinear system is semi-global practical finite-time stable and the tracking error is always kept within the prescribed boundaries. The effectiveness of the proposed region tracking control scheme is validated through simulation-based case studies on an underwater vehicle with measurement noise.  相似文献   

16.
The integral control is an effective way to track non-zero constant reference. In this paper, to utilize a robust predictive integral control strategy in the output-feedback case, the control requirement and the goals are formulated in a suitable form. Then, by introducing a novel matrix transformation, the controller designing issue is translated into an optimization problem subjected to some constraints. Such constraints are represented in terms of linear matrix inequality (LMI). By solving a minimization problem, the gains of the integral controller are determined and updated at some time instants. Finally, several numerical simulations are given to evaluate the advantages of the suggested robust control method over similar ones. The outcomes confirm the superiority of the proposed idea compared to the existing approach.  相似文献   

17.
In this paper, a stable model predictive control approach is proposed for constrained highly nonlinear systems. The technique is a modification of the multistep Newton-type control strategy, which was introduced by Li and Biegler. The proposed control technique is applied on a constrained highly nonlinear aerodynamic test bed, the twin rotor MIMO system (TRMS) to show the efficacy of the control technique. Since the accuracy of the plant model is vital in MPC techniques, the nonlinear state space equations of the system are derived considering all possible effective components. The nonlinear model is adaptively linearized during the prediction horizon. The linearized models of the system are employed to form a linear quadratic objective function subject to a set of inequality constraints due to the system input/output limits. The stability of the control system is guaranteed using the terminal equality constraints technique. The satisfactory performance of the proposed control algorithm on the TRMS validates the effectiveness and the reliability of the approach.  相似文献   

18.
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19.
This paper considers the topic of adaptive leader-following fault-tolerant tracking control for a class of non-strict feedback nonlinear multi-agent systems with or without state constraints in a unified solution. Through the use of certain transformation techniques, the original constraint system is recast as a new completely unconstrained system. Compared with the existing results, the limitation that the constraint functions need upper bound is relaxed. By employing radial basis function neural networks (RBFNNs) to approximate the unknown functions. A novel adaptive fault-tolerant consensus tracking control (CTC) manner is raised with command filtered backstepping design. Then, through the Lyapunov stability analysis, the proposed scheme can ensure all signals in the closed-loop system are cooperative semi-globally uniformly ultimately bounded (SGUUB). Finally, simulation example confirms the efficiency of the proposed method.  相似文献   

20.
This paper studies the issue of finite-time performance guaranteed event-triggered (ET) adaptive neural tracking control for strict-feedback nonlinear systems with unknown control direction. A novel finite-time performance function is first constructed to describe the prescribed tracking performance, and then a new lemma is given to show the differentiability and boundedness of the performance function, which is important for the verification of the closed-loop system stability. Furthermore, with the help of the error transformation technique, the origin constrained tracking error is transformed into an equivalent unconstrained one. By utilizing the first-order sliding mode differentiator, the issue of “explosion of complexity” caused by the backstepping design is adequately addressed. Subsequently, an ingenious adaptive updated law is given to co-design the controller and the ET mechanism by the combination of the Nussbaum-type function, thus effectively handling the influences of the measurement error resulted from the ET mechanism and the challenge of the controller design caused by the unknown control direction. The presented event-triggered control scheme can not only guarantee the prescribed tracking performance, but also alleviate the communication burden simultaneously. Finally, numerical and practical examples are provided to demonstrate the validity of the proposed control strategy.  相似文献   

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