A new direct method based on the Chebyshev cardinal functions for variable-order fractional optimal control problems

In this paper, a new direct method based on the Chebyshev cardinal functions is proposed to solve a class of variable-order fractional optimal control problems (V-OFOCPs). To this end, a new operational matrix (OM) of variable-order (V-O) fractional derivative in the Caputo sense is derived for these basis functions and is used to obtain an approximate solution for the problem under study. In the proposed method, the state and the control variables are expanded in terms of the Chebyshev cardinal functions with unknown coefficients, at first. Then, the OM of V-O fractional derivative and some properties of the Chebyshev cardinal functions are employed to achieve a nonlinear algebraic equation corresponding to the performance index and a nonlinear system of algebraic equations corresponding to the dynamical system in terms of the unknown coefficients. Finally, the method of constrained extremum is applied, which consists of adjoining the constraint equations derived from the given dynamical system and the initial conditions to the performance index by a set of undetermined Lagrange multipliers. As a result, the necessary conditions of optimality are derived as a system of algebraic equations in the unknown coefficients of the state variable, control variable, and Lagrange multipliers. Furthermore, some numerical examples of different types are demonstrated with their approximate solutions for confirming the high accuracy and applicability of the proposed method.     

Direct solution of nonlinear optimal control problems using quasilinearization and Chebyshev polynomials

In this paper, a numerical method to solve nonlinear optimal control problems with terminal state constraints, control inequality constraints and simple bounds on the state variables, is presented. The method converts the optimal control problem into a sequence of quadratic programming problems. To this end, the quasilinearization method is used to replace the nonlinear optimal control problem with a sequence of constrained linear-quadratic optimal control problems, then each of the state variables is approximated by a finite length Chebyshev series with unknown parameters. The method gives the information of the quadratic programming problem explicitly (The Hessian, the gradient of the cost function and the Jacobian of the constraints). To show the effectiveness of the proposed method, the simulation results of two constrained nonlinear optimal control problems are presented.     

Solution of delay fractional optimal control problems using a hybrid of block-pulse functions and orthonormal Taylor polynomials

This paper introduces an efficient direct approach for solving delay fractional optimal control problems. The concepts of the fractional integral and the fractional derivative are considered in the Riemann–Liouville sense and the Caputo sense, respectively. The suggested framework is based on a hybrid of block-pulse functions and orthonormal Taylor polynomials. The convergence of the proposed hybrid functions with respect to the L²-norm is demonstrated. The operational matrix of fractional integration associated with the hybrid functions is constructed by using the Laplace transform method. The problem under consideration is transformed into a mathematical programming one. The method of Lagrange multipliers is then implemented for solving the resulting optimization problem. The performance and computational efficiency of the developed numerical scheme are assessed through various types of delay fractional optimal control problems. Our numerical findings are compared with either exact solutions or the existing results in the literature.     

Observer based fault-tolerant control for a class of nonlinear networked control systems

In this paper, we present a fault-tolerant control (FTC) framework for a class of nonlinear networked control systems (NCSs). Firstly, the plant is transformed into two subsystems with one of them decoupled from the system fault. Then, the nonlinear observer is designed to provide the estimation of unmeasurable state and modelling uncertainty, which are used to construct fault estimation algorithm. Considering the sampling intervals occurred by net, a fault-tolerant control method is proposed for such nonlinear NCSs using the impulsive system techniques. The controller gain and the maximum sampling interval, which make the faulty system stable are given. An example is included to show the efficiency of the proposed method.     

A novel direct torque control method for brushless DC motors based on duty ratio control

Conventional direct torque control (DTC) suffers from large torque ripple and nonconstant switching frequency, which are caused by the hysteresis band amplitude and the motor speed. Many methods have been proposed to tackle these problems. However, these methods are usually complicated and parameter dependent. A novel DTC method for brushless DC motors based on duty ratio control is proposed to reduce torque ripple and maintain a constant switching frequency. During each switching period, an active voltage vector and a zero voltage vector are applied. A simple and effective method implemented to calculate the duty ratio relies only on the torque error, reducing the parameter dependence. The proposed method has the advantages of conventional DTC and effectively reduces torque ripple, which improves the performance of conventional DTC. Simulation and experimental results are given to confirm the method’s validity.     

A new singular system approach to output feedback sliding mode control for fractional order nonlinear systems

This paper studies the problem of output feedback sliding mode control (OFSMC) for fractional order nonlinear systems. A necessary and sufficient condition for the existence of a sliding surface is obtained by a new singular system approach and a linear matrix equality (LMI), which reduces the conservativeness of the system. Then an OFSMC law is designed based on a fractional order Lyapunov method, which ensures that the resulting fractional closed-loop system is asymptotically stable and the states of the fractional closed-loop system converge to the sliding surface in finite time. A fractional electrical circuit is discussed to illustrate the effectiveness of the proposed approach.     

A direct approach using the finite element method for the solution of the linear optimal control problem with a quadratic criterion

The present paper proposes a numerical approach to a linear optimal control problem with a quadratic performance index. In this technique, the time interval is divided into a number of time segments and all of the unknown functions which appear in the performance index are either interpolated linearly with respect to time or assumed to be constant in each time segment. The augmented performance index is discretized within each time element through the ordinary finite element technique.The main advantage of the present method is as follows: all of the necessary conditions for the performance index to be stationary can be expressed in the form of algebraic equations and the performance sequence of the state variables can be eliminated. As a result, the optimal control problem is reduced to the simple one of finding the sequence of control variables alone, which minimizes the quadratic performance index.A general formulation of the method is given and simple numerical examples are shown to demonstrate the effectiveness of the technique.     

Tracking control based on adaptive Bernstein polynomial approximation for a class of unknown nonlinear dynamic systems

In this article, an adaptive tracking control approach using Bernstein polynomial approximation is firstly proposed for an unknown nonlinear dynamic system. Bernstein polynomial approximation aims to compensate the unknown nonlinear dynamic function. However, if Bernstein theorem is directly used, the Bernstein polynomial's coefficients need to be derived from the system dynamic function. Nevertheless, the dynamic function is presumed to be unknown, hence the polynomial approximation still cannot be used for designing this control. In order to obtain the available function approximation, adaptive strategy is considered to estimate these coefficients. Finally, by learning from the classical adaptive algorithm, the undetermined coefficient problem is addressed, so that the valid tracking control is found for the unknown nonlinear dynamic system. According to Lyapunov stability analysis and simulation experiment, it is concluded that the new adaptive scheme can realize the control objective.     

A composite pseudospectral method for solving multi-delay optimal control problems involving piecewise constant delay functions

An adaptive numerical method for solving multi-delay optimal control problems with piecewise constant delay functions is introduced. The proposed method is based on composite pseudospectral method using the well-known Legendre–Gauss–Lobatto points. In this approach, the main problem converts to a mathematical optimization problem whose solution is much more easier than the original one. The necessary conditions of optimality associated to nonlinear piecewise constant delay systems are derived. The method is easy to implement and provides very accurate results.     

A PI controller configuration for robust control of a class of nonlinear systems

The PI control configuration for stabilization and signal tracking of nonlinear systems is investigated. Semiglobal asymptotic stability and semiglobal practical signal tracking of the controlled system are proven using results from the theory of nonlinear singularly perturbed systems.     

Adaptive disturbance attenuation for a class of uncertain nonlinear systems: A double-gain nonlinear observer method

This paper is concerned with the problem of adaptive disturbance attenuation for a class of nonlinear systems. The traditional adaptive methods are almost impossible to compensate the time-varying unknown disturbance by designing parameter adaptive laws without a priori knowledge about the bounds of external disturbances. To solve the problem, a new strategy is proposed by constructing an augmented system where the external disturbance is considered as another component of the augmented state vector. Based on this, a double-gain nonlinear observer is employed to estimate the state of the augmented nonlinear system. Further, an output feedback control strategy is designed, and it is proved that the proposed strategy ensures that all the signals are bounded and the tracking error exponentially converges to an adjustable compact set. Finally, an example is performed to demonstrate the validity of the proposed scheme.     

Robust adaptive finite-time stabilization control for a class of nonlinear switched systems based on finite-time disturbance observer

The problem of adaptive global finite-time stabilization control for a class of nonlinear switched systems in the presence of external perturbations and arbitrary switchings has been addressed in this research study. The proposed scheme has been designed based on a finite-time estimation technique in which during the control procedure, unknown imposed perturbations are accurately estimated by means of the designed finite-time disturbance observer (FTDO). Due to the exact estimation of the external disturbances within a given finite time, the encountered complications and adversities from loss of information in the Lyapunov parameter estimation (LPE) methods have been solved which are caused by the persistent switchings in the system. Furthermore, a new solution for the problem of chattering phenomenon in nonlinear switched systems has been presented by utilizing the designed FTDO, which can counteract the malfunctioning responses of the system caused by external disturbances and unmodeled dynamics. In this paper, an acknowledged class of nonlinear switched systems has been taken into account which is in the general form of canonical structure. In addition, the established design strategy is formulated for the control of perturbed nonlinear switched systems with one and only input and assures that the system states through the finite-time convergence characteristic, reach the equilibrium point of origin. Finally, numerical simulations are carried out on a mass-spring-damper (MSD) dynamical system to indicate advantages and superior efficiency of the suggested method.     

Finite-time robust control of a class of nonlinear time-delay systems via Lyapunov functional method

This paper investigates the finite-time robust control problem of a class of nonlinear time-delay systems with general form, and proposes some new delay-independent and delay-dependent conditions on the issue. First, by developing an equivalent form, the paper studies finite-time stabilization problem, and presents some delay-dependent stabilization results by constructing suitable Lyapunov functionals. Then, based on the stabilization results, we study the finite-time robust control problem for the systems, and give a robust control design procedure. Finally, the study of two illustrative examples shows that the results obtained of the paper work well in the finite-time stabilization and robust stabilization for the systems. It is shown that, by using the method in the paper, the obtained results do not contain delay terms, which can avoid solving nonlinear mixed matrix inequalities and reduce effectively computational burden. Moreover, different from existing finite-time results, the paper also presents delay-dependent sufficient conditions on the finite-time control problem for the systems.     

Probability-constrained tracking control for a class of time-varying nonlinear stochastic systems

This paper is concerned with the probability-constrained tracking control problem for a class of time-varying systems with stochastic nonlinearities, stochastic noises and successively packet loss. The main purpose of this paper is to design a time-varying observer and tracking controller such that (1) the probabilities of both the estimation error and tracking error confined to given ellipsoidal sets are larger than prescribed constants, and (2) the ellipsoids are minimized in the sense of matrix norm at each time point. By using a stochastic analysis method, the probability constrained tracking control problem is solved and sufficient conditions are obtained in terms of recursive linear matrix inequalities. A recursive optimization algorithm is developed to design the observer and tracking controller such that not only the addressed probability constrained aim is satisfied, but also the ellipsoidal sets are minimized. At last, a simulation example is given to illustrate the effectiveness and applicability of the developed approach.     

Finite-time state-feedback control for a class of stochastic constrained nonlinear systems

In this article, the finite-time stability problem is investigated for a kind of stochastic nonlinear systems subject to asymmetric output constraints. Firstly, a new asymmetric barrier Lyapunov function (BLF) is introduced to deal with the constraint on output variable. Further, through incorporating the proposed BLF into the adding a power integrator technique, a state-feedback controller is explicitly designed. With the help of the stochastic Lyapunov stability theory, it is then proved that the origins of the considered systems are finite-time stable in probability under the designed controller. Meanwhile, the proposed control scheme also guarantees that the pre-given output constraint is not violated in the almost sure sense. Finally, the simulation results of an example are provided to demonstrate the derived theoretical conclusion.     

A new type of transitional filter based on summation of polynomials

A new transitional filter based on the sum of filter polynomials is proposed and discussed. It shall be shown that the approach allows for greater flexibility in adjusting passband and stopband gain shapes. The sensitivity of the filter transfer function is analyzed and related to the approximation problem. Some new modified classical filters are also derived including maximally flat (Butterworth) and equiripple (Chebyshev) types. Several examples of combining Butterworth, Chebyshev and sync-tuned filters are presented and compared to those obtained using the conventional product method. The new transitional filter provides an alternative to other forms and provides a means for isolating the effects of non-uniformly distributed pole angles.     

Fuzzy observer-based sampled-data control for a class of pure-feedback nonlinear systems

This paper aims at the sampled-data control problem for a class of pure-feedback nonlinear systems. A fuzzy state observer is constructed to evaluate the unavailable states. In this process, fuzzy logic systems are applied to approximate the uncertain nonlinear functions. Based on the new designed state observer, a sampled-data control scheme for the pure-feedback nonlinear systems is proposed. The designed sampled-data controller ensures the boundedness of the nonlinear systems. Finally, two numerical examples are used to demonstrate that the proposed method is efficient.     

Stabilization for a class of strict-feedback nonlinear systems via the PWM control law

This paper studies the PWM control problem of a class of nonlinear systems. During a modulation period, the PWM control signal maintains a pulse waveform with tunable width and fixed magnitude. The PWM control only possesses finite states, and has relatively limited control capability. This causes the degradation of system performance, and even the instability when implementing into a nonlinear system. We will introduce a novel method to design both the state feedback stabilizer and the output feedback stabilizer for strict-feedback nonlinear systems via the PWM control. The system performance is analyzed in a novel framework and the stability criteria is derived to ensure the system convergence. At last, two examples are considered to illustrate the effectiveness of our proposed method.     

Sampled-data stabilization of a class of lower-order nonlinear systems with input delays based on a multi-rate control scheme

This paper focuses on the problem of sampled-data stabilization for a class of low-order lower-triangular nonlinear systems with large input delays. A new predictor-based multi-rate sampled-data control scheme is proposed to guarantee that the resulting system is globally strongly stable under some assumptions. Compared with the existing methods, the present strategy just needs to know the approximate prediction of state variables, and the stabilizing performance of a given continuous-time feedback controller can be preserved at the sampling instants. It is noted that the proposed controller takes the form of a power series. Its truncation at a finite order is regarded as approximate controller which is proved to be effective in the practical implementation. Two simulation examples are finally given to illustrate the advantages and effectiveness of the proposed control scheme.