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Traditional input–output feedback linearization requires full knowledge of system dynamics and assumes no disturbance at the input channel and no system’s uncertainties. In this paper, a model-free active input–output feedback linearization technique based on an improved active disturbance rejection control paradigm is proposed to design feedback linearization control law for a generalized nonlinear system with a known relative degree. The linearization control law is composed of a scaled generalized disturbance estimated by an improved nonlinear extended state observer with saturation-like behavior and the nominal control signal produced by an improved nonlinear state error feedback. The proposed active input–output feedback linearization cancels in real-time fashion the generalized disturbances which represent all the unwanted dynamics, exogenous disturbances, and system uncertainties and transforms the system into a chain of integrators up to the relative degree of the system, which is the only information required about the nonlinear system. Stability analysis has been conducted based on the Lyapunov functions and revealed the convergence of the improved nonlinear extended state observer and the asymptotic stability of the closed-loop system. Verification of the outcomes has been achieved by applying the proposed active input–output feedback linearization technique on the single-link flexible joint manipulator. The simulations results validated the effectiveness of the proposed active input–output feedback linearization tool based on improved active disturbance rejection control as compared to the conventional active disturbance rejection control–based active input–output feedback linearization and the traditional input–output feedback linearization techniques.

In this paper, a Novel Active Disturbance Rejection Control (N-ADRC) strategy is proposed that replaces the Linear Extended State Observer (LESO) used in Conventional ADRC (C-ADRC) with a nested LESO. In the nested LESO, the inner-loop LESO actively estimates and eliminates the generalized disturbance. Increasing the bandwidth improves the estimation accuracy which may tolerate noise and conflict with H/W limitations and the sampling frequency of the system. Therefore, an alternative scenario is offered without increasing the bandwidth of the inner-loop LESO provided that the rate of change of the generalized disturbance estimation error is upper bounded. This was achieved by the placing of an outer-loop LESO in parallel with the inner one that estimates and eliminates the remaining generalized disturbance originating from the inner-loop LESO due to bandwidth limitations. The stability of LESO and nested LESO was investigated using Lyapunov stability analysis. Simulations on uncertain nonlinear single-input-single-output (SISO) system with time-varying exogenous disturbance revealed that the proposed nested LESO could successfully deal with a generalized disturbance in both noisy and noise-free environments, where the Integral Time Absolute Error (ITAE) of the tracking error for the nested LESO was reduced by 69.87% from that of the LESO.

<p>In this paper, an enhanced stochastic optimization algorithm based on the basic Particle Swarm Optimization (PSO) algorithm is proposed. The basic PSO algorithm is built on the activities of the social feeding of some animals. Its parameters may influence the solution considerably. Moreover, it has a couple of weaknesses, for example, convergence speed and premature convergence. As a way out of the shortcomings of the basic PSO, several enhanced methods for updating the velocity such as Exponential Decay Inertia Weight (EDIW) are proposed in this work to construct an Enhanced PSO (EPSO) algorithm. The suggested algorithm is numerically simulated established on five benchmark functions with regards to the basic PSO approaches. The performance of the EPSO algorithm is analyzed and discussed based on the test results.</p>

Abstract-This paper presents a new strategy for the active disturbance rejection control (ADRC) of a general uncertain system with unknown bounded disturbance based on a nonlinear sliding mode extended state observer (SMESO). Firstly, a nonlinear extended state observer is synthesized using sliding mode technique for a general uncertain system assuming asymptotic stability. Then the convergence characteristics of the estimation error are analyzed by Lyapunov strategy. It revealed that the proposed SMESO is asymptotically stable and accurately estimates the states of the system in addition to estimating the total disturbance. Then, an ADRC is implemented by using a nonlinear state error feedback (NLSEF) controller; that is suggested by J. Han and the proposed SMESO to control and actively reject the total disturbance of a permanent magnet DC (PMDC) motor. These disturbances caused by the unknown exogenous disturbances and the matched uncertainties of the controlled model. The proposed SMESO is compared with the linear extended state observer (LESO). Through digital simulations using MATLAB / SIMULINK, the chattering phenomenon has been reduced dramatically on the control input channel compared to LESO. Finally, the closed-loop system exhibits a high immunity to torque disturbance and quite robustness to matched uncertainties in the system.

A decentralized control scheme is developed in this paper based on an improved active disturbance rejection control (IADRC) for output tracking of square Multi-Input-Multi-Output (MIMO) nonlinear systems and compared with the decoupled control scheme. These nonlinear MIMO systems were subjected to exogenous disturbances and composed of high couplings between subsystems, input couplings, and uncertain elements. In the decentralized control scheme, it was assumed that the input couplings and subsystem couplings were both parts of the generalized disturbance. Moreover, the generalized disturbance included other components, such as exogenous disturbances and system uncertainties, and it was estimated within the context of Active Disturbance rejection Control (ADRC) via a novel nonlinear higher order extended state observer (NHOESO) from the measured output and canceled from the input channel in a real-time fashion. Then, based on the designed NHOESO, a separate feedback control law was developed for each subsystem to achieve accurate output tracking for given reference input. With the proposed decentralized control scheme, the square MIMO nonlinear system was converted into approximately separate linear time invariant Single-Input-Single-Output (SISO) subsystems. Numerical simulations in a MATLAB environment showed the effectiveness of the proposed technique, where it was applied on a hypothetical MIMO nonlinear system with strong couplings and vast uncertainties. The proposed decentralized control scheme reduced the total control signal energy by 20.8% as compared to the decoupled control scheme using Conventional ADRC (CADRC), while the reduction was 27.18% using the IADRC.

Abstract-In this paper an improved nonlinear state error feedback controller (INLSEF) has been proposed for perfect reference tracking and minimum control energy. It consists of a nonlinear tracking differentiator together with nonlinear combinations of the error signal. The tracking differentiator generates a set of reference profile for the input signal, which is the signal itself in addition to its derivatives. On the other hand, the 12-parameters nonlinear combinations of the error signal make the INLSEF controller can handles with time-varying and system's nonlinearity. Digital simulation studies have been conducted for the proposed controller and compared with several works from literature survey on two case studies, mass-springdamper which is a very nonlinear system and nonlinear ball and beam systems. The parameters of the nonlinear combination of the error signal are tuned to satisfy the optimality condition by minimizing the OPI performance index defined in this work. From the simulations results one can conclude that the proposed INLSEF controller performance is better than that of its counterpart in terms of speed and control energy and minimum error. Also, the results showed that the proposed controller is effectively enhancing the stability and performance of the closed loop system.

Abstract-This paper presents a new improved nonlinear tracking differentiator (INTD) with hyperbolic tangent function in the state-space system. The stability and convergence of the INTD are thoroughly investigated and proved. Through the error analysis, the proposed INTD can extract differentiation of any piecewise smooth nonlinear signal to reach a high accuracy. The improved tracking differentiator (INTD) has the required filtering features and can cope with the nonlinearities caused by the noise. Through simulations, the INTD is implemented as a signal's derivative generator for the closedloop feedback control system with a nonlinear PID controller for the nonlinear Mass-Spring-Damper system and showed that it could achieve the signal tracking and differentiation faster with a minimum mean square error.