Legendre wavelet method for solving variable-order nonlinear fractional optimal control problems with variable-order fractional Bolza cost

This paper deals with a numerical method for solving variable-order fractional optimal control problem with a fractional Bolza cost composed as the aggregate of a standard Mayer cost and a fractional Lagrange cost given by a variable-order Riemann–Liouville fractional integral. Using the integration by part formula and the calculus of variations, the necessary optimality conditions are derived in terms of two-point variable-order boundary value problem. Operational matrices of variable-order right and left Riemann–Liouville integration are derived, and by using them, the two-point boundary value problem is reduced into the system of algebraic equations. Additionally, the convergence analysis of the proposed method has been considered. Moreover, illustrative examples are given to demonstrate the applicability of the proposed method.     

A new Wavelet Method for Variable‐Order Fractional Optimal Control Problems

In this paper, a new computational method based on the Legendre wavelets (LWs) is proposed for solving a class of variable‐order fractional optimal control problems (V‐FOCPs). To do this, a new operational matrix of variable‐order fractional integration (OMV‐FI) in the Riemann‐Liouville sense for the LWs is derived and used to obtain an approximate solution for the problem under study. Along the way the hat functions (HFs) are introduced and employed to derive a general procedure to compute this matrix. In the proposed method, the variable‐order fractional dynamical system is transformed to an equivalent variable‐order fractional integro‐differential dynamical system, at first. Then, the highest integer order of the derivative of the state variable and the control variable are expanded by the LWs with unknown coefficients. Next, the OMV‐FI in the the Riemann‐Liouville sense together with some properties of the LWs are employed to achieve a nonlinear algebraic equation in place of the performance index and a nonlinear system of algebraic equations in place of 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 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, the efficiency and accuracy of the proposed method are demonstrated for some concrete examples. The obtained results show that the proposed method is very efficient and accurate.     

A numerical technique for solving fractional optimal control problems

This paper presents a numerical method for solving a class of fractional optimal control problems (FOCPs). The fractional derivative in these problems is in the Caputo sense. The method is based upon the Legendre orthonormal polynomial basis. The operational matrices of fractional Riemann-Liouville integration and multiplication, along with the Lagrange multiplier method for the constrained extremum are considered. By this method, the given optimization problem reduces to the problem of solving a system of algebraic equations. By solving this system, we achieve the solution of the FOCP. Illustrative examples are included to demonstrate the validity and applicability of the new technique.     

Piecewise fractional Legendre functions for nonlinear fractional optimal control problems with ABC fractional derivative and non-smooth solutions

In this study, to solve fractional problems with non-smooth solutions (which include some terms in the form of piecewise or fractional powers), a new category of basis functions called the orthonormal piecewise fractional Legendre functions is introduced. The upper bound of the error of the series expansion of these functions is obtained. Two explicit formulas for computing the Riemann–Liouville and Atangana–Baleanu fractional integrals of these functions are derived. A direct method based on these functions and their fractional integral is proposed to solve a family of optimal control problems involving the ABC fractional differentiation whose solutions are non-smooth in the above expressed forms. By the proposed technique, solving the original fractional problem turns into solving an equivalent system of algebraic equations. The established method accuracy is studied by solving some examples.     

Necessary conditions of fractional optimal control problems with state constraints in the sense of Riemann‐Liouville

This paper is devoted to the optimal control problem of a fractional dynamic system with state constraints in the sense of Riemann‐Liouville. By means of the needle variation, we establish the Pontryagin's maximum principle for the optimal control problem. Moreover, when such a necessary condition is singular in some sense, we investigate the “second‐order” necessary conditions accordingly. As an application, two examples are presented to demonstrate the accuracy and efficiency of the result.     

Active disturbance rejection control for nonlinear fractional‐order systems

This paper investigates active disturbance rejection control involving the fractional‐order tracking differentiator, the fractional‐order PID controller with compensation and the fractional‐order extended state observer for nonlinear fractional‐order systems. Firstly, the fractional‐order optimal‐time control scheme is studied to propose the fractional‐order tracking differentiator by the Hamilton function and fractional‐order optimal conditions. Secondly, the linear fractional‐order extend state observer is offered to acquire the estimated value of the sum of nonlinear functions and disturbances existing in the investigated nonlinear fractional‐order plant. For the disturbance existing in the feedback output, the effect of the disturbance is discussed to choose a reasonable parameter in fractional‐order extended state observer. Thirdly, by this observed value, the nonlinear fractional‐order plant is converted into a linear fractional‐order plant by adding the compensation in the controller. With the aid of real root boundary, complex root boundary, and imaginary boot boundary, the approximate stabilizing boundary with respect to the integral and differential coefficients is determined for the given proportional coefficient, integral order and differential order. By choosing the suitable parameters, the fractional‐order active disturbance rejection control scheme can deal with the unknown nonlinear functions and disturbances. Finally, the illustrative examples are given to verify the effectiveness of fractional‐order active disturbance rejection control scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

Solving a category of two-dimensional fractional optimal control problems using discrete Legendre polynomials

In this paper, we formulate a numerical method to approximate the solution of two-dimensional optimal control problem with a fractional parabolic partial differential equation (PDE) constraint in the Caputo type. First, the optimal conditions of the optimal control problems are derived. Then, we discretize the spatial derivatives and time derivatives terms in the optimal conditions by using shifted discrete Legendre polynomials and collocations method. The main idea is simplifying the optimal conditions to a system of algebraic equations. In fact, the main privilege of this new type of discretization is that the numerical solution is directly and globally obtained by solving one efficient algebraic system rather than step-by-step process which avoids accumulation and propagation of error. Several examples are tested and numerical results show a good agreement between exact and approximate solutions.     

A symplectic local pseudospectral method for solving nonlinear state‐delayed optimal control problems with inequality constraints

In this paper, a symplectic local pseudospectral (PS) method for solving nonlinear state‐delayed optimal control problems with inequality constraints is proposed. We first convert the original nonlinear problem into a sequence of linear quadratic optimal control problems using quasi‐linearization techniques. Then, based on local Legendre‐Gauss‐Lobatto PS methods and the dual variational principle, a PS method to solve these converted linear quadratic constrained optimal control problems is developed. The developed method transforms the converted problems into a coupling of a system of linear algebraic equations and a linear complementarity problem. The coefficient matrix involved is sparse and symmetric due to the benefit of the dual variational principle. Converged solutions can be obtained with few iterations because of the local PS method and quasi‐linearization techniques are used. The proposed method can be applied to problems with fixed terminal states or free terminal states, and the boundary conditions and constraints are strictly satisfied. Numerical simulations show that the developed method is highly efficient and accurate.     

Stability analysis of interconnected nonlinear fractional‐order systems via a single‐state variable control

This paper is devoted to investigating the stability of interconnected nonlinear fractional‐order systems via a single‐state variable control. First of all, based on stability theory, the Grönwall‐Bellman lemma and the Mittag‐Leffler function, the relevant stability results are derived. The obtained results are general and can further extend the application range. Meanwhile, an improved single‐state variable control method is introduced. The control scheme only needs to control some state variable of the system or some subsystem(s) to realize and any additional restrictions are not added. Finally, the effectiveness of the obtained results is demonstrated by several typical examples. Besides, by comparison, simulation results show that the proposed control method can indeed decrease the design and control cost and improve flexibility of control.     

A computational method for solving optimal control and parameter estimation of linear systems using Haar wavelets

In this article, a computational method based on Haar wavelet in time-domain for solving the problem of optimal control of the linear time invariant systems for any finite time interval is proposed. Haar wavelet integral operational matrix and the properties of Kronecker product are utilized to find the approximated optimal trajectory and optimal control law of the linear systems with respect to a quadratic cost function by solving only the linear algebraic equations. It is shown that parameter estimation of linear system can be done easily using the idea proposed. On the basis of Haar function properties, the results of the article, which include the time information, are illustrated in two examples.     

Practical adaptive fractional‐order nonsingular terminal sliding mode control for a cable‐driven manipulator

For the high precise tracking control purpose of a cable‐driven manipulator under lumped uncertainties, a novel adaptive fractional‐order nonsingular terminal sliding mode control scheme based on time delay estimation (TDE) is proposed and investigated in this paper. The proposed control scheme mainly has three elements, ie, a TDE element applied to properly compensate the lumped unknown dynamics of the system resulting in a fascinating model‐free feature; a fractional‐order nonsingular terminal sliding mode (FONTSM) surface element used to ensure high precision in the steady phase; and a combined reaching law with adaptive technique adopted to obtain fast convergence and high precision and chatter reduction under complex lumped disturbance. Stability of the closed‐loop control system is analyzed with the Lyapunov stability theory. Comparative simulations and experiments were performed to demonstrate the effectiveness of our proposed control scheme using 2‐DOF (degree of freedom) of a cable‐driven manipulator named Polaris‐I. Corresponding results show that our proposed method can ensure faster convergence, higher precision, and better robustness against complex lumped disturbance than the existing TDE‐based FONTSM and continuous FONTSM control schemes.     

The Use of the Ritz Method and Laplace Transform for Solving 2D Fractional‐Order Optimal Control Problems Described by the Roesser Model

In this article a numerical solution is presented for a class of two‐dimensional fractional‐order optimal control problems (2D‐FOOCPs) with one input and two outputs. To implement the numerical method, the Legendre polynomial basis is used with the aid of the Ritz method and the Laplace transform. By taking the Ritz method as a basic scheme into account and applying a new constructed fractional operational matrix to estimate the fractional and integer order derivatives of the basis, the given 2D‐FOOCP is reduced to a system of algebraic equations. One of the advantages of the proposed method is that it provides greater flexibility in which the given initial and boundary conditions of the problem are imposed. Moreover, satisfactory results are obtained in just a small number of polynomials order. The convergence of the method is extensively investigated and finally two illustrative examples are included to show the validity and applicability of the novel proposed technique in the current work.     

Modified bang‐bang controller for maximal and minimal time optimal control problems

Recently, there have been a series of results regarding two time optimal control problems for a class of linear and nonlinear systems ‐ one is to keep the system states within certain bound for the longest time during feedback disruption and the other is to derive the system states to near the origin as fast as possible after feedback recovery, both under bounded control inputs. These are called maximal and minimal time optimal control problems, respectively. In the existing results, a bang‐bang controller has been commonly suggested as the actual implementation of the optimal controller. In this paper, we suggest a modified version of the bang‐bang controller which can also serve as an approximate optimal controller. Our proposed controller provides the (near) optimal performance with (i) possible reduction of a number of switchings; (ii) possible reduction of control input magnitude.     

External stability of Caputo fractional‐order nonlinear control systems

This paper investigates external stability of Caputo fractional‐order nonlinear control systems. Following the idea of a traditional Lyapunov function method, we point out the problems that would appear when applying it for fractional external stability. These problems are shown to be solvable by employing results on smoothness of solutions, but this method generalized for Caputo fractional‐order nonlinear control systems requires strong conditions to be imposed on vector field functions and inputs. To further explore the fractional external stability, diffusive realizations and Lyapunov‐like functions are taken into consideration. Specifically, a Caputo fractional‐order nonlinear control system with certain assumptions proves to be equivalent to its diffusive realization; a Lyapunov‐like function based on the realization exhibits properties useful to prove the external stability. As expected, this Lyapunov‐like method has weaker requirements. Finally, it is applied to the external stabilization of a Caputo fractional‐order Chua's circuits with inputs.     

Iterative learning control design with high‐order internal model for discrete‐time nonlinear systems

In this paper, a high‐order internal model (HOIM)‐based iterative learning control (ILC) scheme is proposed for discrete‐time nonlinear systems to tackle the tracking problem under iteration‐varying desired trajectories. By incorporating the HOIM that is utilized to describe the variation of desired trajectories in the iteration domain into the ILC design, it is shown that the system output can converge to the desired trajectory along the iteration axis within arbitrarily small error. Furthermore, the learning property in the presence of state disturbances and output noise is discussed under HOIM‐based ILC with an integrator in the iteration axis. Two simulation examples are given to demonstrate the effectiveness of the proposed control method. Copyright © 2016 John Wiley & Sons, Ltd.     

Multi‐objective robust fuzzy fractional order proportional–integral–derivative controller design for nonlinear hydraulic turbine governing system using evolutionary computation techniques

The present paper proposes a novel multi‐objective robust fuzzy fractional order proportional–integral–derivative (PID) controller design for nonlinear hydraulic turbine governing system (HTGS) by using evolutionary computation techniques. The fuzzy fractional order PID (FOPID) controller takes closed loop error and its fractional derivative as inputs and performs fuzzy logic operations. Then, it produces the output through the fractional order integrator. The predominant advantages of the proposed controller are its capability to handle complex nonlinear processes like HTGS in heuristic manner, due to fuzzy incorporation and extending an additional flexibility in tuning the order of fractional derivative/integral terms to enhance the closed loop performance. The present work formulates the optimal tuning problem of fuzzy FOPID controller for HTGS as a multi‐objective one instead of a traditional single‐objective one towards satisfying the conflicting criteria such as less settling time and minimum damped oscillations simultaneously to ensure the improved dynamic performance of HTGS. The multi‐objective evolutionary computation techniques such as non‐dominated sorting genetic algorithm‐II (NSGA‐II) and modified NSGA‐II have been utilized to find the optimal input/output scaling factors of the proposed controller along with the order of fractional derivative/integral terms for HTGS system under no load and load turbulence conditions. The performance of the proposed fuzzy FOPID controller is compared with PID and FOPID controllers. The simulations have been conducted to test the tracking capability and robust performance of HTGS during dynamic set point changes for a wide range of operating conditions and model parameter variations, respectively. The proposed robust fuzzy FOPID controller has ensured better fitness value and better time domain specifications than the PID and FOPID controllers, during optimization towards satisfying the conflicting objectives such as less settling time and minimum damped oscillations simultaneously, due to its special inheritance of fuzzy and FOPID properties.     

Design of non‐fragile guaranteed‐cost repetitive‐control system based on two‐dimensional model

This paper concerns a new method of repetitive control based on two‐dimensional (2D) system theory. First, a 2D model is presented that enables the independent adjustment of control, which happens within a repetition period, and learning, which happens between periods. Next, the problem of designing a repetitive‐control law is formulated as a state‐feedback design problem for the 2D model. An existence condition and a method of designing a robust repetitive‐control law for a plant containing time‐invariant structured uncertainties are established by combining 2D system theory with linear matrix inequalities. Then, based on those results, a non‐fragile guaranteed‐cost repetitive‐control law is derived. The controller gain to be designed is assumed to have additive gain variations. It guarantees that the value of a quadratic performance function is less than a specified upper bound for all admissible uncertainties. The main feature of this approach is that it enables the control action and the learning process to be adjusted independently by the direct tuning of the weighting matrices in the quadratic cost function. Finally, a numerical example demonstrates the validity of this approach. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Low dimensional disturbance observer‐based control for nonlinear parabolic PDE systems with spatio‐temporal disturbances

In this paper, a design problem of low dimensional disturbance observer‐based control (DOBC) is considered for a class of nonlinear parabolic partial differential equation (PDE) systems with the spatio‐temporal disturbance modeled by an infinite dimensional exosystem of parabolic PDE. Motivated by the fact that the dominant structure of the parabolic PDE is usually characterized by a finite number of degrees of freedom, the modal decomposition method is initially applied to both the PDE system and the PDE exosystem to derive a low dimensional slow system and a low dimensional slow exosystem, which accurately capture the dominant dynamics of the PDE system and the PDE exosystem, respectively. Then, the definition of input‐to‐state stability for the PDE system with the spatio‐temporal disturbance is given to formulate the design objective. Subsequently, based on the derived slow system and slow exosystem, a low dimensional disturbance observer (DO) is constructed to estimate the state of the slow exosystem, and then a low dimensional DOBC is given to compensate the effect of the slow exosystem in order to reject approximately the spatio‐temporal disturbance. Then, a design method of low dimensional DOBC is developed in terms of linear matrix inequality to guarantee that not only the closed‐loop slow system is exponentially stable in the presence of the slow exosystem but also the closed‐loop PDE system is input‐to‐state stable in the presence of the spatio‐temporal disturbance. Finally, simulation results on the control of temperature profile for catalytic rod demonstrate the effectiveness of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

Mittag‐Leffler stabilization for an unstable time‐fractional anomalous diffusion equation with boundary control matched disturbance

This paper addresses the Mittag‐Leffler stabilization for an unstable time‐fractional anomalous diffusion equation with boundary control subject to the control matched disturbance. The active disturbance rejection control (ADRC) approach is adopted for developing the control law. A state‐feedback scheme is designed to estimate the disturbance by constructing two auxiliary systems: One is to separate the disturbance from the original system to a Mittag‐Leffler stable system and the other is to estimate the disturbance finally. The proposed control law compensates the disturbance using its estimation and stabilizes system asymptotically. The closed‐loop system is shown to be Mittag‐Leffler stable and the constructed auxiliary systems in the closed loop are proved to be bounded. This is the first time for ADRC to be applied to a system described by the fractional partial differential system without using the high gain.     

State‐feedback stabilization for stochastic high‐order nonlinear systems with SISS inverse dynamics

This paper investigates the problem of state‐feedback control for a class of stochastic high‐order nonlinear systems with stochastic inverse dynamics. Under the assumption that the inverse dynamics of the subsystem are stochastic input‐to‐state stable (SISS), by extending through adding a power integrator technique, choosing an appropriate Lyapunov function and using the idea of changing supply function, a smooth state‐feedback controller is explicitly constructed to render the system globally asymptotically stable in probability and the states can be regulated to the origin. A simulation example is provided to show the effectiveness of the proposed scheme. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society