CONTROLLABILITY CANONICAL FORM FOR NONLINEAR CONTROL SYSTEMS

General nonlinear control systems are studied in this paper with the goal to transform them into the so-called controllability canonteal form via state transformation only. The conditions of transformability are given for both single input and multiple input cases. Besides, by an algebraic approach the procedure for constructing the state transformation is established. This paper is formulated in the framework of calculus rather than differential geometry approach.

ABSOLUTE OBSERVABILITIES OF NONLINEAR CONTROL SYSTEMS AND THEIR NORMAL FORMS

In this paper the concept of absolute observability of nonlinear control systems is advanced.Different from the linear time-invariant version, there are different definitions of absolute observability for nonlinear control systems.Two algorithms for maximal absolutely observable subsystems are given.Correspondingly,there are two relevant normal forms.The relations with the largest controlled invariant distribution contained in kerdh,zero dynamics etc.,are discussed from the view point of maximal absolute observabilities.

Nonlinear adaptive switching control for a class of non-affine nonlinear systems

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.

Combined indirect and direct method for adaptive fuzzy output feedback control of nonlinear system

A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.

Hierarchical Control for Large-Scale Systems

A class of large-scale systems, where the overall objective function is a nonlinear function of performance index of each subsystem, is investigated in this paper. This type of large-scale control problem is non-separable in the sense of conventional hierarchical control. Hierarchical control is extended in the paper to large-scale non-separable control problems, where multiobjective optimization is used as separation strategy. The large-scale non-separable control problem is embedded, under certain conditions, into a family of the weighted Lagrangian formulation. The weighted Lagrangian formulation is separable with respect to subsystems and can be effectively solved using the interaction balance approach at the two lower levels in the proposed three-level solution structure. At the third level, the weighting vector for the weighted Lagrangian formulation is adjusted iteratively to search the optimal weighting vector with which the optimal of the original large-scale non-separable control problem is obtained. Theoretical base of the algorithm is established. Simulation shows that the algorithm is effective.

Adaptive security control of time-varying constraints nonlinear cyber-physical systems with false data injection attacks

In this article,an adaptive security control scheme is presented for cyber-physical systems(CPSs)suffering from false data injection(FDI)attacks and time-varying state constraints.Firstly,an adaptive bound estimation mechanism is introduced in the backstepping control design to mitigate the effect of FDI attacks.Secondly,to solve the unknown sign time-varying statefeedback gains aroused by the FDI attacks,a type of Nussbaum function is employed in the adaptive security control.Then,by constructing a barrier Lyapunov function,it can be ensured that all signals of controlled system are bounded and the time-varying state constraints are not transgressed.Finally,the provided simulation examples demonstrate the effectiveness of the proposed controller.

Robust fault detection for a class of nonlinear network control system with communication delay

To investigate a class of nonlinear network control system, a robust fault diagnosis method is presented based on the robust state observer. To access the objective that the designed robust filter is maximally tolerant to disturbances and sensitive to fault, the robustness and stability properties of the fault diagnosis scheme are established rigorously. Using the residual vector, a fault tolerant controller is established in order to guarantee the stability of the closed-loop system, and the controller law can be obtained by solving a set of linear matrix inequalities. Then, some relevant sufficient conditions for the existence of a solution are given by applying Lyapunov stability theory. Finally, a simulation example is performed to show the effectiveness of the proposed approach.

Robust Controller Design for Satellite Attitude Tracking System

The attitude tracking control problem for a satellite with parameter uncertainties and external disturbances is considered in this paper. For this class of multi-input multi-output uncertain nonlinear systems, a design method of robust output tracking controllers is proposed based on the upper-bounds of the uncertainties. Using the input/output feedback linearization approach and Lyapunov method, a control law is designed, which guarantees that the system output exponentially tracks the given desired output. The proposed controller is easy to compute and complement. Simulation results show that, in the closed-loop system, precise attitude control is accomplished in spite of the uncertainties in the system.

Robust Attitude Control for Reusable Launch Vehicles Based on Fractional Calculus and Pigeon-inspired Optimization

In this paper, a robust attitude control system based on fractional order sliding mode control and dynamic inversion approach is presented for the reusable launch vehicle RLV during the reentry phase. By introducing the fractional order sliding surface to replace the integer order one, we design robust outer loop controller to compensate the error introduced by inner loop controller designed by dynamic inversion approach. To take the uncertainties of aerodynamic parameters into account, stochastic robustness design approach based on the Monte Carlo simulation and Pigeon-inspired optimization is established to increase the robustness of the controller. Some simulation results are given out which indicate the reliability and effectiveness of the attitude control system. © 2014 Chinese Association of Automation.

Terminal sliding mode control based on super-twisting algorithm

An improved non-singular terminal sliding mode control based on the super-twisting algorithm is proposed for a class of second-order uncertain nonlinear systems. This method can effectively avoid the singularity problem and obviously reduce the chattering phenomenon. The stability of the proposed procedure is proven to be finite-time convergence using the Lyapunov theory against uncertain unmodeled dynamic and external disturbances. An example is given to show the proposed improved non-singular terminal sliding mode control (SMC) law effectively. © 1990-2011 Beijing Institute of Aerospace Information.

Neuro-Optimal Guidance Control for Lunar Soft Landing

Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.

NECESSARY AND SUFFICIENT CRITERIA FOR ABSOLUTE STABILITY OF THE DIRECT CONTROL SYSTEM

Some necessary and sufficient conditions for absolute stability of several classes of direct control system were given, and two simplified forms of the control systems obtained twice were discussed. The results improve those of previous works.

Nonlinear adaptive flight control system:Performance enhancement and validation

The problem of decreasing stability margins in L1 adaptive control systems is discussed and an out-of-loop L1 adaptive control scheme based on Lyapunov’s stability theorem is proposed.This scheme enhances the effectiveness of the adaptation,which ensures that the system has suffi-cient stability margins to achieve the desired performance under parametric uncertainty,additional delays,and actuator faults.The stability of the developed control system is demonstrated through a series of simulations.Compared with an existing control scheme,the constant adjustment of the sta-bility margins by the proposed adaptive scheme allows their range to be extended by a factor of 4–5,bringing the stability margin close to that of variable gain PD control with adaptively scheduled gains.The engineered practicability of adaptive technology is verified.A series of flight tests verify the practicability of the designed adaptive technology.The results of these tests demonstrate the enhanced performance of the proposed control scheme with nonlinear parameter estimations under insufficient stability margins and validate its robustness in the event of actuator failures.

The Monotone Method for Controllability of the Nonlinear Evolution Systems

In this paper, we study the controllability of the nonlinear evolution systems. We establish the controllability results by using the monotone operator theory. No compactness assumptions are imposed in the main results. We present an example to illustrate our results.

Transient Performance Improvement in Tracking Control for a Class of Nonlinear Systems with Input Saturation

This paper addresses the composite nonlinear feedback（CNF） control for a class of singleinput single-output nonlinear systems with input saturation to track a time varying reference target with good transient performance. The CNF control law consists of a tracking control law and a performance compensator. The tracking control law is designed to drive the output of the system to track the time varying reference target rapidly, while the performance compensator is used to reduce the overshoot caused by the tracking control law. The stability of the closed-loop system is established. The design procedure and the improvement of transient performance of the closed-loop system are illustrated with a numerical example and the controlled Van del Pol oscillator.

NEW DELAY-DEPENDENT STABILITY CRITERIA AND ROBUST CONTROL OF NONLINEAR TIME-DELAY SYSTEMS

This paper investigates the stability analysis and H_∞ control for a class of nonlinear timedelay systems,and proposes a number of new results.Firstly,an equivalent form is given for this class of systems by means of coordinate transformation and orthogonal decomposition of vector fields.Then,based on the equivalent form,some delay-dependent results are derived for the stability analysis of the systems by constructing a novel Lyapunov functional.Thirdly,the authors use the equivalent form and the obtained stability results to investigate the H_∞ control problem for a class of nonhnear time-delay control systems,and present a control design procedure.Finally,an illustrative example is given to show the effectiveness of the results obtained in this paper.It is shown that the main results of this paper are easier to check than some existing ones,and have less conservatism.

Finite-time Consensus for Multi-agent Systems via Nonlinear Control Protocols

This paper investigates the fnite-time consensus problem of multi-agent systems with single and double integrator dynamics,respectively.Some novel nonlinear protocols are constructed for frst-order and second-order leader-follower multi-agent systems,respectively.Based on the fnite-time control technique,the graph theory and Lyapunov direct method,some theoretical results are proposed to ensure that the states of all the follower agents can converge to its leader agent s state in fnite time.Finally,some simulation results are presented to illustrate the efectiveness of our theoretical results.

NN-based Output Tracking for More General Stochastic Nonlinear Systems with Unknown Control Coefficients

This paper considers the output tracking problem for more general classes of stochastic nonlinear systems with unknown control coefficients and driven by noise of unknown covariance. By utilizing the radial basis function neural network approximation method and backstepping technique, we successfully construct a controller to guarantee the solution process to be bounded in probability.The tracking error signal is 4th-moment semi-globally uniformly ultimately bounded（SGUUB） and can be regulated into a small neighborhood of the origin in probability. A simulation example is given to demonstrate the effectiveness of the control scheme.

A Novel Training Algorithm of Genetic Neural Networks and Its Application to Classification

First of all, this paper discusses the drawbacks of multilayer perceptron (MLP), which is trained by the traditional back propagation (BP) algorithm and used in a special classification problem. A new training algorithm for neural networks based on genetic algorithm and BP algorithm is developed. The difference between the new training algorithm and BP algorithm in the ability of nonlinear approaching is expressed through an example, and the application foreground is illustrated by an example.

An Energy-based Nonlinear Coupling Control for Offshore Ship-mounted Cranes

This paper proposes a novel nonlinear energy-based coupling control for an underactuated offshore ship-mounted crane,which guarantees both precise trolley positioning and payload swing suppressing performances under external sea wave disturbance. In addition to having such typical nonlinear underactuated property, as it is well known, an offshore ship-mounted crane also suffers from much unexpected persistent disturbances induced by sea waves or currents, which, essentially different from an overhead crane fixed on land, cause much difficulty in modeling and controller design. Inspired by the desire to achieve appropriate control performance against those challenging factors, in this paper, through carefully analyzing the inherent mechanism of the nonlinear dynamics, we first construct a new composite signal to enhance the coupling behavior of the trolley motion as well as the payload swing in the presence of ship′s roll motion disturbance. Based on which, an energy-based coupling control law is presented to achieve asymptotic stability of the crane control system′s equilibrium point. Without any linearization of the complex nonlinear dynamics, unlike traditional feedback controllers, the proposed control law takes a much simpler structure independent of the system parameters. To support the theoretical derivations and to further verify the actual control performance, Lyapunov-based mathematical analysis as well as numerical simulation/experimental results are carried out, which clarify the feasibility and superior performance of the proposed method over complicated disturbances.