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1.
This paper studies the event-triggered model predictive control (MPC) of a stabilizable linear continuous-time system. The optimization problem associated with the proposed MPC strategy is formulated exploiting newly designed control constraints. Compared with the conventional tube-based MPC, where the constant tightened control constraints are employed, the proposed MPC strategy exploits the time-varying control constraints, which allows the control signal to take larger values in the beginning along the prediction horizon, resulting in potentially improved system performance. The re-computation of the control signal is triggered by the deviation of the predicted system state and the real system state. Furthermore, conditions are derived based on which the design parameters can be tuned to ensure the recursive feasibility of the optimization and the stability of the closed-loop system. Finally, the effectiveness of the proposed MPC strategy is verified using a numerical example.  相似文献   

2.
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   

3.
In this paper, a self-triggered model predictive control (MPC) strategy is developed for discrete-time semi-Markov jump linear systems to achieve a desired finite-time performance. To obtain the multi-step predictive states when system mode jumping is subject to the semi-Markov chain, the concept of multi-step semi-Markov kernel is addressed. Meanwhile, a self-triggered scheme is formulated to predict sampling instants automatically and to reduce the computational burden of the on-line solving of MPC. Furthermore, the co-design of the self-triggered scheme and the MPC approach is adjusted to design the control input when keeping the state trajectories within a pre-specified bound over a given time interval. Finally, a numerical example and a population ecological system are introduced to evaluate the effectiveness of the proposed control.  相似文献   

4.
In this work, a new design method of model predictive control (MPC) is proposed for uncertain systems with input constraints. By using a new method to deal with actuator constraints, our method can reduce the conservativeness. For the design of the robust MPC controllers, a sequence of feedback control laws is used and a parameter-dependent Lyapunov function is chosen to further reduce the conservativeness. The effectiveness and performance of our MPC design method are demonstrated by an example.  相似文献   

5.
A fault tolerant control scheme for actuator and sensor faults is proposed for a tilt-rotor unmanned aerial vehicle (UAV) system. The tilt-rotor UAV has a vertically take-off and landing (VTOL) capability like a helicopter during the take-off & landing while it could cruise with a high speed as a conventional airplane flight mode. A dual system in the flight control computer (FCC) and the sensor is proposed in this study. To achieve a high reliability, a fault tolerant flight control system is required for the case of actuator or sensor fault. For the actuator fault, the fault tolerant control scheme based on model error control synthesis is presented. A designed fault tolerant control scheme does not require system identification process and it provides an effective reconfigurability without fault detection and isolation (FDI) process. For the sensor fault, the fault tolerant federated Kalman filter is designed for the tilt-rotor UAV system. An FDI algorithm is applied to the federated Kalman filter in order to improve the accuracy of the state estimation even when the sensor fails. For a linearized six-degree-of-freedom linear model and nonlinear model of the tilt-rotor UAV, numerical simulation and process-in-the-loop simulation (PILS) are performed to demonstrate the performance of the proposed fault tolerant control scheme.  相似文献   

6.
This paper presents an integrated and practical control strategy to solve the leader–follower quadcopter formation flight control problem. To be specific, this control strategy is designed for the follower quadcopter to keep the specified formation shape and avoid the obstacles during flight. The proposed control scheme uses a hierarchical approach consisting of model predictive controller (MPC) in the upper layer with a robust feedback linearization controller in the bottom layer. The MPC controller generates the optimized collision-free state reference trajectory which satisfies all relevant constraints and robust to the input disturbances, while the robust feedback linearization controller tracks the optimal state reference and suppresses any tracking errors during the MPC update interval. In the top-layer MPC, two modifications, i.e. the control input hold and variable prediction horizon, are made and combined to allow for the practical online formation flight implementation. Furthermore, the existing MPC obstacle avoidance scheme has been extended to account for small non-apriorily known obstacles. The whole system is proved to be stable, computationally feasible and able to reach the desired formation configuration in finite time. Formation flight experiments are set up in Vicon motion-capture environment and the flight results demonstrate the effectiveness of the proposed formation flight architecture.  相似文献   

7.
This paper is concerned with integrated event-triggered fault estimation (FE) and sliding mode fault-tolerant control (FTC) for a class of discrete-time Lipschtiz nonlinear networked control systems (NCSs) subject to actuator fault and disturbance. First, an event-triggered fault/state observer is designed to estimate the system state and actuator fault simultaneously. And then, a discrete-time sliding surface is constructed in state-estimation space. By the use of a reformulated Lipschitz property and delay system analysis method, the sliding mode dynamics and state/fault error dynamics are converted into a unified linear parameter varying (LPV) networked system model by taking into account the event-triggered scheme, actuator fault, external disturbance and network-induced delay. Based on this model and with the aid of Lyapunov–Krasovskii functional method, a delay-dependent sufficient condition is derived to guarantee the stability of the resulting closed-loop system with prescribed H∞ performance. Furthermore, an observed-based sliding mode FTC law is synthesized to make sure the reachability of the sliding surface. Finally, simulation results are conducted to verify the effectiveness of the proposed method.  相似文献   

8.
The main results of this paper are concentrated on the nonlinear model predictive control (MPC) tracking optimization based on high-order fully actuated (HOFA) system approaches. The proposed HOFA MPC strategy makes full use of full-actuation property to eliminate the nonlinear dynamics of the system, and then the nonlinear optimization problem is equivalently transformed into a series of easy-solve linear convex optimization problems. Different from general nonlinear MPC methods and the current optimal control of the HOFA system approach, an analytical controller with smooth and less energy is obtained by the moving horizon optimization. And it is proven that the proposed controller can stabilize the corresponding tracking error closed-loop system. Finally, not limited to FA systems, as examples, a nonlinear numerical under-actuated model in the mathematical sense and a benchmark nonlinear under-actuated mechanical system are transformed into corresponding equivalent HOFA systems, the simulation results are given to verify the effectiveness of the proposed strategy.  相似文献   

9.
In this paper, a novel event-triggered adaptive fault-tolerant control scheme is proposed for a class of nonlinear systems with unknown actuator faults. Multiplicative faults and additive faults are taken into account simultaneously, both of which may vary with time. Different from existing results, our controller fuses static reliability information and dynamic online information, which is helpful to enhance the fault-tolerant capability. With the aid of an event-triggering mechanism, an actuator switching strategy and a bound estimation approach, the communication burden is significantly reduced and the impacts of the actuator faults as well as the network-induced error are effectively compensated for. Moreover, by employing the prescribed performance control technique, the system tracking error can converge to a predefined arbitrarily small residual set with prescribed convergence rate and maximum overshoot, which implies that the proposed scheme is able to ensure rapid and accurate tracking. Simulation results are presented to illustrate the effectiveness of the proposed scheme.  相似文献   

10.
This article studies adaptive prescribed performance tracking control problem for a class of strict-feedback nonlinear systems with parametric uncertainties and actuator failures. Firstly, in order to compensate the multiple uncertainties and eliminate the influence of actuator failure, a new adaptive tracking controller based on first-order filter technology will be proposed, which simplifies the algorithm design process. Then, by introducing an asymmetric state transition function, the transient and steady performances of the output tracking error are both constrained such that the predetermined performance control goal is achieved. Moreover, to reduce the communication burden from the controller to the actuator, the event-triggered mechanism is designed, and there will be no Zeno phenomenon. Based on Lyapunov stability theory, it is strictly proved that output signal can track the reference signal and all the signals of the closed-loop system are bounded. Finally, a simulation example is performed and the results demonstrate effectiveness of the proposed strategy.  相似文献   

11.
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12.
In this paper, a two-layer model predictive control (MPC) hierarchical architecture of dynamic economic optimization (DEO) and reference tracking (RT) is proposed for non-Gaussian stochastic process in the framework of statistical information. In the upper layer, with state feedback and dynamic economic information, the economically optimal trajectories are estimated by entropy and mean based dynamic economic MPC, which uses the nonlinear dynamic model instead of the steady-state model. These estimated optimal trajectories from the upper layer are then employed as the reference trajectories of the lower layer control system. A survival information potential based MPC algorithm is used to maintain the controlled variables at their reference trajectories in the nonlinear system with non-Gaussian disturbances. The stability condition of closed-loop system dynamics is proved using the statistical linearization method. Finally, a numerical example and a continuous stirred-tank reactor are used to illustrate the merits of the proposed economic optimization and control method.  相似文献   

13.
In this paper, a method is proposed to reject disturbances in the model predictive control (MPC) strategy. In addition, uncertainties in the system parameters (i.e., internal disturbances) are considered as well. To achieve these goals, adaptive neural networks are designed as the predictor model and as the nonlinear disturbance observer, respectively. The disturbances are rejected via the optimization problem of the MPC. Stability of the closed-loop system is studied based on the Input-to-State Stability method. The proposed method is applied to the pH neutralization process and CSTR system and its effectiveness in optimal rejection of the disturbances and satisfying the system constrains is compared with the feed-forward control method.  相似文献   

14.
This paper is concerned with the adaptive control problem for a class of linear discrete-time systems with unknown parameters based on the distributed model predictive control (MPC) method. Instead of using the system state, the state estimate is employed to model the distributed state estimation system. In this way, the system state does not have to be measurable. Furthermore, in order to improve the system performance, both the output error and its estimation are considered. Moreover, a novel Lyapunov functional, comprised of a series of distributed traces of estimation errors and their transposes, has been presented. Then, sufficient conditions are obtained to guarantee the exponential ultimate boundedness of the system as well as the asymptotic stability of the error system by solving a nonlinear programming (NP) problem subject to input constraints. Finally, the simulation examples is given to illustrate the effectiveness and the validity of the proposed technique.  相似文献   

15.
In this paper, a robust actuator fault diagnosis scheme is investigated for satellite attitude control systems subject to model uncertainties, space disturbance torques and gyro drifts. A nonlinear unknown input observer is designed to detect the occurrence of any actuator fault. Subsequently, a bank of adaptive unknown input observers activated by the detection results are designed to isolate which actuator is faulty and then estimate of the fault parameter. Fault isolation is achieved based on the well known generalized observer strategy. The simulation on a closed-loop satellite control system with time-varying or constant actuator faults in the form of additive and multiplicative unknown dynamics demonstrates the effectiveness of the proposed robust fault diagnosis strategy.  相似文献   

16.
This article considers the nonlinear time-delay system with full-state constrains and actuator hysteresis. Compared with the previous research on input hysteresis phenomenon, all states in the system are required to be constrained in a bounded compact set and the direction of hysteresis is unknown. Thus, the system is difficult to be stabilized and get perfect error tracking performance, and the design procedure is more complicated. By combining barrier Lyapunov functions (BLFs) and Nussbaum functions, a new virtual controller is designed, which combines the properties of Nussbaum function with fuzzy logic systems (FLSs). Furthermore, considering that the rate-dependent characteristic of actuator hysteresis will adversely affect the stability of networked control systems (NCSs), a first-order filter is used to solve the problem, but it brings challenges to the design of Lyapunov–Krasovskii functions (KLFs). Thus, a new LKFs is constructed to compensate for the adverse effects of state delay on the nonlinear system. What’s more, this article propose event-triggered technique to solve the coupling effect of the system communication resource constrains. The proposed adaptive control strategy ensures the boundedness of all signals and does not violate the state constraints, and the controller avoids Zeno behavior, and the tracking error fluctuates around zero in a predetermined compression range. Finally, two simulations results verify the effectiveness of the adaptive control strategy.  相似文献   

17.
In the present study, a novel technique is suggested for the adaptive non-linear model predictive control based on the fuzzy approach in three stages. In the presented approach, in the first stage, the prediction and control horizons are obtained from a fuzzy system in each control step. Another fuzzy system is employed to determine the weight factors before the optimization stage of developing new controller. The proposed controller gives the parameters of the model predictive control (MPC) in each control step in order to improve the performance of nonlinear systems. The proposed control scheme is compared with the traditional MPC and Generic Model Control for controlling MED-TVC process. The performances of the three proposed controllers have been investigated in the absence and presence of disturbance in order to evaluate the stability and robustness of the proposed controllers. The results reveal that the novel adaptive controller based on fuzzy approach performs better than the two other controllers in set-point tracking and disturbance rejection with lower IAE criteria. In addition, the average computational time for the adaptive MPC exhibits a decline of 34% in comparison with the traditional MPC.  相似文献   

18.
Many control problems in process systems feature multi-objective optimization problems that involve several and often conflicting objective functions, such as economic profit and environmental concerns. In this paper, we consider a class of multi-objective model predictive control (MO-MPC) problems where nonlinear systems are subject to state and control constraints and multiple economic criteria are conflicting. Using the lexicographic optimization, we propose a prioritized MO-MPC scheme with guaranteed stability for economic optimization. At each sampling time, the MPC action is computed by solving a set of sequentially ordered single objective optimized control problems. Some sufficient conditions are established to ensure recursive feasibility and asymptotic stability of the MO-MPC in the context of economic criteria optimization. Two examples of multi-objective control of a coupled-tank system and a free-radical polymerization process are exploited to illustrate the effectiveness of the proposed MPC scheme and to evaluate the performance by some comparison experiments.  相似文献   

19.
In this paper, an active fault tolerant control (AFTC) scheme is proposed for more electric aircraft (MEA) equipped with dissimilar redundant actuation system (DRAS). The effect of various fault/failure of hydraulic actuator (HA) on the system performance is analyzed in this work. In nominal condition, the state feedback control law is designed for primary control surfaces. In the presence of fault/failure of certain HA, control allocation (CA) scheme together with integral sliding mode controller (ISMC) is retrofitted with existing control law and engaged the secondary (redundant) actuators into the loop. A modified recursive least square (RLS) algorithm is proposed to identify the parametric faults in HA and to measure the effectiveness level of the actuator. In an event of failure of all HA’s in the system, electro hydraulic actuators (EHA) are taken in loop to bring the system back to its nominal operation. In order to stabilize the closed-loop dynamics of HA and EHA, fractional order controllers are designed separately for each actuator. Simulations on the lateral directional model of aircraft demonstrated the effectiveness of the proposed scheme as compared to the existing methods in the literature.  相似文献   

20.
This paper mainly studies the design of iterative learning constrained model predictive fault–tolerant control for batch processes accompanied by multi–delays, interference and actuator failures. Firstly, an equivalent 2D–Roesser model with multi–delays is established. The definition of invariant set is proposed. The sufficient conditions with invariant set characteristics are established. After that the predictive fault-tolerant controller is designed with terminal constraints against external disturbances. In this paper, Lyapunov–Razumikhin Function (LRF) is used to form Lyapunov–Krasovskii Function (LKF) to construct the sufficient condition for the predictive control system that satisfies the terminal constraint condition. Moreover, the system state still remains invariant set characteristics. This method has certain advantages in controller design and calculation. In addition, it has the characteristics of simple design and small computation, and is especially suitable for small delay systems. Finally, a simulation experiment in the nonlinear batch reactor is carried out. Compared with the traditional one-dimensional (1D) method, the presented strategy has better performance through simulation experiment.  相似文献   

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