Contractively invariant ellipsoids have been extensively used as estimates of the domain of attraction of a linear system under a saturated linear feedback. For a discrete-time linear system with a single input subjec...
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ISBN:
(纸本)9781467360890
Contractively invariant ellipsoids have been extensively used as estimates of the domain of attraction of a linear system under a saturated linear feedback. For a discrete-time linear system with a single input subject to actuator saturation, based on a convex hull representation of the saturated linear feedback, a necessary and sufficient condition for an ellipsoid to be contractively invariant was previously established. Based on this condition, the determination of the maximal contractively invariant ellipsoid can be formulated and solved as an LMI problem. In this paper, we develop a criterion to determine if a contractively invariant ellipsoid is the maximal one for discrete-time saturated linear systems with multiple inputs. This criterion is based on the solution of an LMI problem, which involves a generalized convex hull representation of saturated linear feedbacks, and includes the existing result for discrete-time saturated linear systems with a single input as a special case. Simulation results demonstrate the effectiveness of our results.
In controlling biological diseases, it is often more potent to use a combination of agents than using individual ones. However, the number of possible combinations increases exponentially with the number of agents and...
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In controlling biological diseases, it is often more potent to use a combination of agents than using individual ones. However, the number of possible combinations increases exponentially with the number of agents and their concentrations. It is prohibitive to search for effective agent combinations by trial and error as biological systems are complex and their responses to agents are often a slow process. This motivates to build a suitable model to describe the biological systems and help reduce the number of experiments. In this paper, we consider the use of fungicides to inhibit Bipolarismaydis and construct models that describe the responses to fungicide combinations. Three data-driven modeling methods, the polynomial regression, the artificial neural network and the support vector regression, are compared based on the experimental data of the inhibition rates of the southern corn leaf blight with different fungicide combinations. The analysis of the results demonstrates that the support vector regression is best suited to the construction of the response model in terms of achieving better prediction with fewer experiments.
In this paper,we consider the same class of systems in a previous paper,i.e.a class of parametric strict-feedback nonlinear systems with additive *** using the backstepping technique,adaptive control algorithm is deve...
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ISBN:
(纸本)9781479900305
In this paper,we consider the same class of systems in a previous paper,i.e.a class of parametric strict-feedback nonlinear systems with additive *** using the backstepping technique,adaptive control algorithm is developed. Unlike the exiting control schemes for systems with additive disturbance,no knowledge is assumed on two time continuous differentiability of the ***,the developed backstepping controller does not require that the uncertain parameters is restricted within a known ***,overestimation of the system parameters is removed by employing the tuning functions *** is shown that the proposed controller not only guarantees global stability,but also asymptotic tracking.
An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection control(ADRC) mech...
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ISBN:
(纸本)9781479947249
An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection control(ADRC) mechanism, to deal with the input saturation nonlinearity and meanwhile reject the disturbance automatically by using Extended State Observer(ESO). The output of anti-windup compensator is treated as a part of unknown disturbances and is introduced into the ESO, which can online observe both internal and external disturbances(parameter uncertainties and model mismatches). The controller input is yielded by using a nonlinear feedback combination, and it is used to compensate the integrator windup caused by the saturation nonlinearity element. On the other hand, in order to determine the parameters of the ESO and the anti-windup compensator feedback gain, the L2 gain is adopted. The effectiveness and the robustness against model and parameter uncertainties of the proposed method is verified by an example of the seeker platform.
This paper studies semi-global leader-following output consensus of a multi-agent system. Each follower agent in the system, described by a general linear system subject to external disturbances and actuator saturatio...
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This paper studies semi-global leader-following output consensus of a multi-agent system. Each follower agent in the system, described by a general linear system subject to external disturbances and actuator saturation, is to track the leader agent. Conditions on the agent dynamics are identified under which a low gain feedback based linear state control algorithm is constructed for each follower agent such that the leader-following output consensus is achieved when the communication topology among the agents is a directed graph that contains no loop and the leader is globally reachable. In addition, discussions and simulations are also provided for the output consensus in the presence of actuator saturation.
Electromagnetism based detection has advanced rapidly in recent years because of its characteristics of non-contact and non-invasion nature. An electromagnetic measurement system for monitoring the crack of conductivi...
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Improving the use of energy resources has been a great challenge in the last years. A new complex scenario involving a decentralized bidirectional communication between energy suppliers, distribution system and consum...
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Improving the use of energy resources has been a great challenge in the last years. A new complex scenario involving a decentralized bidirectional communication between energy suppliers, distribution system and consumption is nowadays becoming reality. Sometimes cited as the largest and most complex machine ever built, Electric Grids (EG) are been transformed into Smart Grids (SG). Hence, the load forecasting problem has become more difficulty and more autonomous load predictors are needed in this new conjecture. In this paper a novel method, so-called MSES, bio-inspired by Evolution Strategies (ES) combined with Multi-Start (MS) procedure is described. This procedure is mainly based on a self-adaptive algorithm to calibrate the parameters of the fuzzy rules. MSES was implemented in C++ via OptFrame framework. Our main goal is to evaluate the performance of this algorithm in a grid environment. Real data from an electric utility have been used in order to test the proposed methodology. The obtained results are fully described and analyzed.
This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom （DOF） laboratory helicopter system by using a nonlinear robust feedback and a neural network （NN） feedforw...
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This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom （DOF） laboratory helicopter system by using a nonlinear robust feedback and a neural network （NN） feedforward term. The nonlinear robust control law is developed through a modified inner-outer loop approach. The application of the NN-based feedforward is to compensate for the system uncertainties. The proposed control design strategy requires very limited knowledge of the system dynamic model, and achieves good robustness with respect to system parametric uncertainties. A Lyapunov-based stability analysis shows that the proposed algorithms can ensure asymptotic tracking of the helicopter＇s elevation and travel motion, while keeping the stability of the closed-loop system. Real-time experiment results demonstrate that the controller has achieved good tracking performance.
In this paper,we present a model predictive control algorithm for input-saturated systems by a saturation-dependent Lyapunov function *** saturation-dependent Lyapunov function captures the real-time information on th...
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ISBN:
(纸本)9781479900305
In this paper,we present a model predictive control algorithm for input-saturated systems by a saturation-dependent Lyapunov function *** saturation-dependent Lyapunov function captures the real-time information on the severity of saturation and thus leads to less conservative results in controller design.A set invariance condition for the systems with input saturation is presented.A min-max MPC algorithm is proposed for the linear parameter-varying(LPV) systems based on the invariant *** MPC controller is determined by solving a linear matrix inequality(LMI) optimization *** example demonstrates the effectiveness of the proposed algorithm.
This paper is concerned with the stability and stabilizability problems of networked controlsystems（NCSs） with partly quantized *** precisely,the remote state variables transported from other sub-systems experience...
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ISBN:
(纸本)9781479900305
This paper is concerned with the stability and stabilizability problems of networked controlsystems（NCSs） with partly quantized *** precisely,the remote state variables transported from other sub-systems experience quantization errors,while the local state variables do *** consideration is much more natural in NCSs due to the distributive nature of *** errors are represented as convex poly-topic *** on the Lyapunov-Krasovskii （L-K） functional approach,sufficient conditions for the existence of a quantized robust Hstate feedback controller for NCSs are *** conditions are obtained in terms of bilinear matrix inequalities（BMIs）.Furthermore,a cone complementarity algorithm is utilized to convert these BMIs into a convex optimization ***,a simulation example is provided to demonstrate the efficiency of proposed theorems.
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