Tracking Control Technique Research Articles

Real-Time Implementation of the MPPT Control Algorithms of a Wind Energy Conversion System by the Digital Simulator OPAL_RT

This paper presents a comparative study between two algorithms for controlling the Wind Turbine (WT) using real time platforms: RT-Lab. The Maximum Power Point Tracking (MPPT) control technique is implemented for extracting the maximum energy from the wind. The first control consists in taking as a reference strategy the electromagnetic torque associated with the maximum power curve. This controller is known as Indirect Speed Control (ISC). The second one, based on the measured wind speed, is called Direct Speed Control (DSC). In this second controller, the effectiveness of the controllers was evaluated with a PI controller and a Fuzzy Logic (FL) controller. The performances are analyzed and compared on the OPAL-RT digital simulator, which is based on the RT-LAB platform with the model, and its control built in Simulink. The results of the simulations clearly show that algorithm based on fuzzy controllers gives better performance in terms of monitoring the maximum power coefficient and optimal speed compared to conventional algorithms.

Tracking control with aperiodic sampling over networks with delay and dropout

This paper introduces a discrete-time technique for output feedback tracking control with aperiodic sampling over networks suffering delay and dropout. Introducing the concept of pseudo sampling, NCS is modelled as a linear parameter varying (LPV) system. Two methods are explained to obtain a convex approximation of the uncertainty region. It is clarified how to perform the approximation to have the uncertainty space as small as possible. Using this uncertainty space, a polytopic approximation is obtained for the LPV model. The approximated model is used to synthesise a controller for set-point tracking and disturbance rejection. An observer is also synthesised based on this model. The simplicity of the model together with a small uncertainty space, results in less conservative LMI conditions. Compared to the existing results, an improved tracking performance is obtained. The final value theorem for discrete-time LTI systems with constant sampling period is extended to time varying sampling periods. This theorem is used to design a feedforward gain for zero steady-state tracking of staircase reference signals.

Adaptive Path Following Control of Unmanned Surface Vehicles Considering Environmental Disturbances and System Constraints

The current maritime applications have yielded strong demands for the development of advanced unmanned surface vehicles (USVs) with more reliable path following capabilities to greatly extend mission durations and enhance accommodative capabilities of USVs to more hazardous and dynamic environments. This paper presents an adaptive path following control method using a retrofit adaptive tracking control technique with application to a USV with consideration of environmental disturbances (like winds, waves, and currents), while taking into account of the system constraints of USVs, including both turning features (turning rate limit and turning dynamics) and rudder operation constraints (rudder deflection and rate saturation, and its dynamics). In order to guarantee the satisfactory performance of the USV operating in a calm environment, a baseline state feedback tracking controller considering the characteristics of yaw rate and rudder operations, and USV steering and actuator dynamics is first designed. In the presence of time-varying environmental disturbances, a retrofit adaptive disturbance compensating control mechanism is then developed based on the disturbance amplitude estimated from an indirect adaptive disturbance estimator. Finally, a reconfigurable adaptive path following controller is synthesized by combining the baseline controller and the adaptive disturbance compensating mechanism for the proper operation of the USV in the presence of environmental disturbances, while the desired path is successfully followed by the USV within an acceptable deviation boundary and without violating constraints of turning rates as well as amplitude and rate of rudder deflections. To evaluate the effectiveness of the proposed path following control methodology, both numerical simulations on a nonlinear USV model and field experiments on a real-size USV are conducted.

MPC based compound flight control strategy for a ducted fan aircraft

This paper proposes an MPC based compound flight control technique for trajectory tracking and attitude control for a ducted fan aircraft subject to different uncertainties and external disturbances. This approach aims to ensure flight robustness and achieves adequate tracking without sacrificing nominal performance while satisfying constraints under external disturbances and various uncertainties. A nonlinear ducted fan aircraft with non-minimum phase behavior is considered. By unifying a nonlinear disturbance observer with MPC, a compound flight controller is constructed. The recursive feasibility of the optimization problem for the compound controller is guaranteed, and the closed-loop stability is ensured. To demonstrate the effectiveness of the developed scheme, a robust MPC framework is employed for comparative analysis. Finally, numerical simulations and discussions are provided to corroborate the performance of both compound strategies.

Frequency-Modulated Phase Shift Keying Communication for MEPT Control of Wireless Power Transfer

The closed-loop control of wireless power transfer (WPT) systems requires a communication link between the power transmitter and the power receiver for dual-side cooperation. Near-field communication techniques that utilize the power link are preferred for this purpose due to high reliability and security. In this letter, we propose a frequency-modulated phase shift keying (FMPSK) communication technique for the closed-loop maximum efficiency point tracking (MEPT) control of WPT. The technique uses very shallow phase modulation depth to minimize the disturbance on power flow and reduce the efficiency drop caused by the PSK. Meanwhile, it ensures the signal accuracy and precision by multiple methods and precise frequency modulation and demodulation. In experiment, we obtained 82%-85% system efficiency with a 25-125 W load over a distance equal to the coil diameter, and 93% efficiency over a distance equal to the coil radius. The efficiency drop caused by FMPSK was less than 1%. The dynamic processes of voltage regulation and MEPT took only about 1 ms and 10 ms, respectively.

Path tracking control of electromechanical micro-positioner by considering control effort of the system

Position controlling with less overshoot and control effort is a fundamental issue in the design and application of micro-actuators such as micro-positioner. Also, tracking a considered path is very crucial for some particular applications of micro-actuators such as surgeon robots. Herein, a proportional–integral–derivative controller is designed using a feedback linearization technique for path tracking control of a cantilever electromechanical micro-positioner. The micro-positioner is simulated based on a 1-degree-of-freedom lumped-parameter model. Three different paths are considered, and the capability of the designed controller on the path tracking with lower error and control effort is investigated. The obtained results demonstrate the efficiency of the designed proportional–integral–derivative controller not only for reducing the tracking error but also for decreasing the control effort.

Finite-time fault tolerant attitude tracking control of spacecraft using robust nonlinear disturbance observer with anti-unwinding approach

This paper investigates the composite control scheme of robust nonlinear disturbance observer (RNDO) with adaptive non-singular fast terminal sliding mode control (NSFTSMC) technique for the attitude tracking of rigid spacecraft. The spacecraft is subjected to the parametric uncertainties, external disturbances, and actuator faults. The proposed RNDO estimates the overall lumped disturbance (combination of faults and disturbances) in finite-time. Moreover, it improves the disturbance rejection property of the composite control by feedforward compensation. An adaptive law is also employed in the composite control to enhance the robustness against the cases where RNDO takes some time for estimation, e.g., when there is a sudden change in the lumped disturbance. Further, the proposed controller is also enriched with anti-unwinding property to tackle the problem of unwinding in the quaternion based attitude representation. The stability analysis of the closed-loop system under the composite control scheme guarantees the finite-time convergence of relative state variables using the Lyapunov stability theory. The simulation analysis with the comparative study illustrates the effectiveness of the proposed strategy in terms of better disturbance rejection ability, higher accuracy, faster convergence, and better steady-state performance.

Fuzzy Adaptive Fixed-time Sliding Mode Control with State Observer for A Class of High-order Mismatched Uncertain Systems

Using state observer has attracted a notable interest of researchers in control community to provide an on-line state estimator for control systems instead of measuring them physically by sensors which is costly, inaccurate, and easy to contaminate by noise. Some challenges ahead to design state observer in control systems are using estimated data by observer in the designed controller as well as the system stability analysis by using controller and observer simultaneously. This paper proposes Fuzzy Adaptive Fixed-time Sliding Mode Control (FAFSMC) technique for trajectory tracking of a class of high-order nonlinear systems with mismatched external disturbances and uncertainties. Meanwhile, the fixed-time state observer is proposed to incorporate with the controller for estimating the unmeasured even states (velocity) and providing on-line data in the controller. A proper candidate Lyapunov function is defined to verify the system global fixed-time stability by considering designed control law, state observer term, and adaptive law, simultaneously. The simulation results of three simulation examples, ship course system, two-link robotic manipulator, and three-link robotic manipulator, are carried out in Simulink/MATLAB to reveal the effectiveness of the proposed FAFSMC scheme compared with the other three conventional methods for solving trajectory tracking problem. Two performance criteria, Integral of the Square Value (ISV) and Integral of the Absolute value of the Error (IAE), are used to make a comprehensive comparison among the proposed FAFSMC method with state observer and the other three methods.

Necessity to Design a Controller for PV Module

Solar power is future of our planet due to the depletion of non-renewable sources of energy. We all are directly dependent on non-renewable source which will only last for 1 or 2 decades. The PV cell exhibit non linear I-V and P-V characteristics. In this paper it is discussed about the factors which will affect the PV module performance. Some factors will decrease the solar cell performance while some factors will improve the efficiency and increase its output power. The performance characteristics of PV module are modeled mathematically and simulated under different atmospheric conditions. The simulation model is obtained using MATLAB software and stimulated under different values of input parameters of PV module that include irradiance and temperature. The variations of these parameters were recorded under different atmospheric conditions. The input parameters of solar cell like solar irradiance and ambient temperature was evaluated. It observed that the maximum power produced fluctuates with both irradiance and temperature. Since the conversion efficiency of PV array is exceptionally low, it requires maximum power point tracking (MPPT) control techniques. The MPPT is the programmed controlled method used to guide the solar cell to achieve the maximum power output, during minute to minute variations of atmospheric changes like irradiance and temperature. The MPPT controller is used to provide maximum power output from PV module against changes in temperature and irradiance. Results obtain by simulation are presented and discussed.

Output tracking control with preview action for a class of continuous-time Lipschitz nonlinear systems and its applications

This article presents a novel tracking control technique with preview action for a class of continuous-time Lipschitz nonlinear systems. First, by using the differentiation approach, the considered Lipschitz nonlinear system is formally transformed into a quasi-linear parameter varying system. Then, with the aid of the lifting method along with some special mathematical manipulations, an augmented error system with the known future reference knowledge is successfully constructed. The tracking problem is, thereby, reduced into a standard H∞ control problem. To guarantee that the closed-loop system remains asymptotically stable and satisfies acceptable H∞ performance, a suitable state feedback controller is established through testing the feasibility of given linear matrix inequality. Based on this, an innovative tracking control law composed of state feedback control action, integral control action, and preview action of the reference signal is proposed for the first time. Simulation results demonstrate that the suggested controller leads to the superior improvement on the tracking performance than the existing control scheme.

A Computational Analysis of Interfacing Converters with Advanced Control Methodologies for Microgrid Application

Power electronics converter and inverter systems for microgrid operations are always stochastic. When the system is operating in grid-tied mode, the attached load is not constant, so the current which drawn from the DC grid also varies leads to a voltage drop and that causes steady-state error in between the actual and desired output voltage in microgrid. DC-DC bidirectional converters are widely used in microgrid application that facilitates bidirectional energy convertion which having boost mode operation in one direction and bucking mode in other operation. The Interfacing converter is controlled by using the Maximum Power Point Tracking (MPPT) control technique for obtaining maximum power during different atmospheric conditions. In this work, a Model Predictive Control (MPC) strategy is proposed which having an improved cost function, single prediction horizon, and an observer to keep tracking the output voltage. Here, MPC is proposed for cumulative control in between the DC grid side converters and AC grid side inverter, and for improving the power quality and reliability of the utility grid. Both continuous time and discrete time domain models are formed for the whole system for applying different control strategies. Along with MPC, the system has been controlled by using other controllers like as PI controller, Sliding Mode Controller (SMC). Luenberger observer is used to check the DC grid voltage when disturbances are implemented. Here, all the computational results are compared for justifying and validate a better controlling method for microgrid application. These kind of work is first time reported in this manuscript.

Modified extreme learning machine based motion control of robotic manipulators

Precise trajectory tracking is a difficult task due to partially known and unknown dynamics and the disturbances present in the system. For improving the tracking performance of the robotic manipulator, this work proposes a novel PSO optimized kernel based Extreme Learning Machine (PSO-KELM) learning algorithm in which PSO is used to get the optimal values of the free kernel-parameters in KELM. The simulation results represent the good generalized performance and PSO-KELM outperforms the KELM and ELM based control techniques for the manipulator trajectory tracking. Comparative analysis of the proposed control schemes have been done with NN and SVM based controllers and various ELM based variants for the trajectory tracking problem in robotic manipulator.

Optimal Fractional-Order Fuzzy-MPPT for solar water pumping system

This paper seeks to improve the efficiency of photovoltaic (PV) water pumping system using Fractional-order Fuzzy Maximum Power Point Tracking (FoF-MPPT) control and Gray Wolf Optimization (GWO) technique. The fractional calculus has been used to provide an enhanced model of PV water pumping system to, accurately, describe its nonlinear characteristics. Moreover, three metaheuristic optimizers are applied to tune the parameters of the proposed FoF-MPPT, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and the GWO. The FoF-MPPT is intensively tested and compared to the Perturb and Observe (PO), the Incremental Conductance (INC) and the FL-MPPT controllers. A MATLAB-Simscape based physical model of the PV water pumping system has been developed and simulated for different control techniques with the proposed optimization algorithms. The response of the PV water pumping systems is evaluated under rapidly changing weather conditions to prove the effectiveness of the optimized FoF-MPPT compared to the conventional algorithms. The reliability of the comparative study has been emphasized in terms of several transient tracking and steady- state performance indices under different operating conditions. The simulation results show the effective performance of the proposed metaheuristic optimized FL-MPPT and FoF-MPPT control under different climatic conditions with disturbance rejection and robustness analysis.

Neural Networks-Based Adaptive Exponential Quasi-Passification and Output Tracking Control for Uncertain Switched Nonlinear Systems

In this paper, we mainly study the adaptive exponential quasi-passivity and adaptive tracking control of lower triangular uncertain switched nonlinear systems, even though the adaptive output tracking control problem of individual subsystem is unsolvable. First, the exponential quasipassivity concept is proposed to describe the energy changing of the overall switched nonlinear systems without the exponential quasi-passivity property of all the subsystems. Then, for switched nonlinear systems, the semiglobally uniformly ultimate boundedness is achieved by using exponential quasipassivity. Second, this result is applied to solve adaptive tracking control problem uncertain switched nonlinear systems in lower-triangular form. A new adaptive tracking control technique is developed by combining quasi-passification methods with adaptive backstepping techniques. The unknown nonlinear functions are approximated by the radial basis function neural networks. In contrast to the existing results, the multiple storage functions method reduces the conservativeness caused by a common Lyapunov function for all subsystems. Finally, the effectiveness of the proposed method is verified by an example.

Photovoltaic Maximum Power Point Technique based on Incremental Conductance (InCon) Control Algorithm

Maximum output power status can significantly improve the deployment rate of solar energy system. In order to get the maximum power output, issue of tracking maximum power point (MPP), reduced harmonics around MPP and improve efficiency of the solar power energy system, this paper presents the improved maximum power point tracking (MPPT) control technique algorithm on the basis of traditional Incremental Conductance (InCon) method. Nonlinear engineering model of solar cells is built in the “MATLAB/Simulink”, simulation software. Analyze the basic working principle of maximum power point control technology. Design the simulation model of conventional Incremental conductance method and compares the results with modified method. The main circuit of the system consist on DC Boost Converter. The simulation results illustrate that, the modified Incremental conductance (InCon) MPPT algorithm is realistic, fast tracking accuracy, efficient and the stability of output power are superior.

Adaptive Microtracking Control for an Underwater IPMC Actuator Using New Hyperplane-Based Sliding Mode

The ionic polymer metal composite (IPMC) actuator is one of the most promising smart actuators that possesses unique advantages and is suitable for underwater applications. However, there are challenges to employ it directly in such applications for precise tracking. The IPMC suffers from high nonlinearity due to the existence of inherent creep and hysteresis phenomena. Furthermore, the IPMC actuator is always subject to uncertainty and external disturbance due to the working environment. Therefore, to cope with the aforementioned restrictions and to make the IPMC applicable for real-life applications, designing a high-accuracy tracking control technique is an urgent demand. In this article, a new integral nonlinear hyperplane-based sliding mode controller is dedicated for an underwater IPMC actuator. The proposed controller employs an adaptive tuning law in the discontinuous part to overcome any prerequisite for knowing the upper bound of the model uncertainty and external disturbance. Extensive experiments have been carried out to verify practical effectiveness of the proposed controller in comparison with conventional nonsingular terminal sliding mode in terms of fast convergence, accurate tracking, and the robust performance.

Decentralized Finite-time [formula omitted] tracking control for a class of interconnected Markovian jump system with actuator saturation

An observer-based decentralized tracking control technique is developed for a saturated interconnected Markovian jump system in the sense of finite-time stability (FTS). To improve tracking performances, a L2−L∞ performance criterion which is relevant to both estimated error and estimated tracking error is proposed. A sufficient condition for finite-time bounded (FTB) is established. In view of the obtained condition, a method with the one-step procedure to seek the gains of observer and controller is investigated. By virtue of this procedure, the problem of the decentralized tracking stabilization is transformed into a convex optimization problem subject to constraints in the form of linear matrix inequalities (LMIs). Furthermore, the tracking control problem of interconnected Markovian jump system without saturation is also investigated, and the results are obtained directly to avoid taking congruent transformation. Simulation is presented to show the effectiveness and applicability of the obtained results.

A Robust Online Adaptive B-Spline MPPT Control of Three-Phase Grid-Coupled Photovoltaic Systems Under Real Partial Shading Condition

This work contributes to the research on three-phase photovoltaic systems via a new more robust online adaptive neuro-fuzzy maximum power point tracking (MPPT) control technique considering real partial shading and load conditions. The trapping in local minima and high computational cost in the existing neuro-fuzzy structure are addressed by incorporating B-spline function in the proposed control method. The system parameters are adjusted online via an adaptive neuro-fuzzy inference system rules acquired from the MPPT error. The optimization part of the proposed control law is performed through an online learning gradient-descent back-propagation algorithm. The superiority of the proposed control in terms of energy conversion efficiency, MPPT error, and output power is checked under the same operating conditions with well-known used traditional and intelligent MPPT control algorithms. Finally, the robustness of the proposed control is confirmed through a complete day simulation and comparison indexes.

Fuzzy cognitive network-based maximum power point tracking using a self-tuned adaptive gain scheduled fuzzy proportional integral derivative controller and improved artificial neural network-based particle swarm optimization

The increased demand for electrical energy has driven the development of renewable energy sources. In particular, the conversion of solar energy into electrical energy using photovoltaic (PV) systems has become popular because of its simplicity and low cost. However, the nonlinear characteristics and power fluctuations due to changes in the temperature and irradiation hinder the maximum utilization of the power with a PV system. Thus, the maximum power point tracking (MPPT) control technique is used to extract the maximum available power from PV arrays. Due to insolation and variations in temperature in a PV system, the conventional MPPT techniques are readily trapped by local maxima to significantly reduce the conversion efficiency. In order to overcome this issue, we developed a novel perturb and observe algorithm based on an adaptive fuzzy PID controller with an improved artificial neural network-based particle swarm optimization method for tracking the maximum power point with high tracking speed as well as maintaining the system's stability. In addition, we used a fuzzy cognitive network to maintain the equilibrium state, which is essential for improving the conversion efficiency. Simulation results and performance evaluations using our proposed method demonstrated its suitability for applications in PV systems.

An Extension of Computed-Torque Control for Parallel Robots in Ankle Reeducation

Abstract This paper extends the well-known computed-torque control technique for trajectory tracking in parallel robotic manipulators, which belong to the class of nonlinear systems under algebraic restrictions. The proposed methodology is based on Euler-Lagrange modelling which, once the closed-loop kinematic chain is taken into account, leads to a system of differential algebraic equations requiring proper initialisation while controlled. The control scheme is illustrated for an ankle therapy device known as the motoBOTTE, where post-stroke patients are subject to reeducation routines corresponding to different trajectories of the parallel manipulator.