Showing papers in "Journal of Control, Automation and Electrical Systems in 2017"

Optimization of Fractional Order PID Controller Using Grey Wolf Optimizer

Abstract: This paper presents a novel evolutionary technique to optimize the parameters of fractional order controller for controlling two classes of systems: time-delay and higher-order system. The evolutionary technique known as grey wolf optimizer is used to tune both integer and fractional order controllers. The grey wolf optimizer searches for the optimum solution in the following manner, i.e. encircling, hunting, attacking the prey and finally search for the new prey consecutively if exists. To certify these various procedure, the performance indices like integral square error, integral absolute error, integral time-weighted square error, and integral time-weighted absolute error are minimized for the authenticity. Moreover, the proposed algorithm is validated and compared with well-established techniques.

Sensorless SVM-Direct Torque Control for Induction Motor Drive Using Sliding Mode Observers

Abstract: This paper presents an improved direct torque control strategy (DTC) for induction motor drive. The conventional DTC suffers from high torque ripples and variable switching frequency due to utilizing hysteresis comparators. The presented technique uses the space vector modulation in order to cover DTC drawbacks and reduce high torque and flux ripples by maintaining a fixed switching frequency. An anti-windup proportional integral controller is considered for the outer speed loop. Furthermore, the control design is combined with dual sliding mode observers for speed/flux and load torque estimation in order to improve the control performances and reduce different uncertainties. Moreover, they minimize the number of sensors to decrease the cost and increase the reliability of the system. The effectiveness of the sensorless method has been investigated by simulation and experimental validation using MATLAB/Simulink software with real time interface based on dSpace 1104 bored.

Design of the PI–UPFC–POD and PSS Damping Controllers Using an Artificial Bee Colony Algorithm

Abstract: This paper presents two variations of the artificial bee colony (ABC) algorithm, the classical and a modified version, called GBest, for the design of the proportional–integral and supplementary damping controllers: power system stabilizers and the unified power flow controller (UPFC)–power oscillation damping set. The objective is to insert additional damping to the low-frequency oscillation modes present in multimachine electrical power systems, to guarantee the small-signal stability of the system considering different loading conditions. A new current injection formulation for the UPFC is proposed and incorporated into the current sensitivity model used to represent the dynamical operation of the electric power system. Static and dynamical analysis were performed for the New England system to validate the proposed formulation and to evaluate the performance of the optimization algorithms. The results indicate that the modified version of the ABC algorithm has superior performance for this problem, providing robust solutions, that ensure the stability of the system even when small variations of the load are considered.

Assessment of the Impact of Microgrid Control Strategies in the Power Distribution Reliability Indices

Abstract: This paper proposes a probabilistic methodology to assess the impact of the microgrid control strategies in distribution network reliability. This assessment is carried out considering the primary and secondary controls of the microgrid in the islanded operation mode. The sequential Monte Carlo simulation was used to select the system scenarios resulting in uncertainties associated with: load fluctuations, load forecasting errors, distributed generation unavailability and intermittence of renewable energy resources. The proposed methodology can estimate the impact of the islanded operation of a microgrid on the load point and system indices related to yearly frequency and duration of interruptions. Furthermore, the proposed approach evaluates well-being indices to analyze the efficiency of the primary and secondary controls. The results in a host distribution network, with a microgrid of 38 buses, demonstrate that the islanded operation causes reductions of about 24 and 29% in the ASIFI and ASIDI indices, respectively.

Model Reduction by New Clustering Method and Frequency Response Matching

Abstract: In this paper, mixed method of linear, time-invariant system model reduction method is suggested. A novel clustering algorithm based on Lehmer measure is utilized in the proposed method to obtain the reduced-order denominator polynomial. The selection of poles to form cluster center is based on the viewpoint of important poles contributing to the system is preserved by dominant pole algorithm. Having obtained the denominator polynomial of the reduced model, the coefficient of the numerator is found using the frequency response matching method. The reduction algorithm is fully computer oriented. The reduced model is stable if the original model is stable. Moreover, this method gives a good quality approximation in both the transient and the steady-state responses of the original system.

Study of Electricity Theft Impact on the Economy of a Regulated Electricity Company

Abstract: The electricity theft is an economic issue for the electricity company due to unbilled revenue of consumers who commit such action. In a regulated scenario, the company needs to fit within the laws of a regulatory agency (ANEEL in Brazil) and the loss of revenue is a problem that can compromise the compliance with regulatory targets and business efficiency. The objective of this article is to analyze how the energy theft impacts on the economy of the regulated company, consumers and society as a whole. Through the economic model TAROT (optimized tariff), it was possible through a concise and comprehensive manner to analyze the regulated electricity market using simulations and discover in which points the company operates regulated and through it to determine the economic indicators.

MIMO Uncertain Nonlinear System Control via Adaptive High-Order Super Twisting Sliding Mode and its Application to Robotic Manipulator

Abstract: This paper presents a robust, continuous, finite-time convergent, adaptive, high-order super twisting sliding mode controller for a class of multi input–multi output uncertain nonlinear system and its application to robotic manipulator. The limitation on conventional super twisting control (STC) algorithm application only to relative degree one system is eliminated by using a novel homogeneous nonlinear sliding manifold. Moreover, the proposed controller gains are selected by using an adaptive estimation mechanism to tackle the gain overestimation problem. It is ensured that the tracking errors will converge to zero in finite time and the actual control signal is smooth and free from chattering phenomenon, a major known limitation of the conventional sliding mode control and STC. The rejection of the parametric uncertainties and external disturbances is improved due to an extra integration of discontinuous control. The finite-time convergence and stability of the proposed controller is analyzed with the help of homogeneous Lyapunov stability theory. The effectiveness and application feasibility of the proposed controller is revealed by the simulation results obtained from the MATLAB software. Finally, a real-time implementation strategy for the realization of the proposed controller, using MATLAB–Simulink platform and Speedgoat hardware, is also given for robotic manipulator control.

A Novel Optimal Control and Management Strategy of Stand-Alone Hybrid PV/Wind/Diesel Power System

Abstract: This paper presents a new control and management strategy of a stand-alone hybrid photovoltaic/wind/diesel power system. The model is considered as a one multi-input single-output system, where both controllers of the wind and the solar systems are tuned simultaneously by the resolution of a multi-objective optimization problem using genetic algorithm. The produced energy is managed over a switching method to meet the consumer demand. The proposed approach permits advantageous energy optimization of the hybrid system and gives better performances compared to the traditional decentralized control methods. The control and management strategy is applied to design a hybrid power system for a farm located in Skikda Algeria, with a load demand of 27.4 kWh/day. The simulation results prove the effectiveness of the presented approach compared to conventional one.

A Discrete-Time Robust Adaptive Controller Applied to Grid-Connected Converters with LCL Filter

Abstract: This paper proposes a novel discrete-time robust model reference adaptive controller based on a modified recursive least squares applied to grid-connected converter with LCL filter. This controller uses an input–output approach to reduce the number of sensors, and it is robust to additive and multiplicative unmodeled dynamics and sinusoidal disturbances. Experimental results are presented in order to verify the performance of proposed control strategy.

A Meteorological–Statistic Model for Short-Term Wind Power Forecasting

Abstract: The problem of wind power forecasting is addressed in this work, considering a combination of a numerical weather prediction model (NWP) and statistical models. Brazilian developments on the Regional Atmospheric Modeling System is employed in two different areas in Brazil to simulate forecasts of 72 h ahead of the wind speed, at each 10 min. In one of the areas studied, the wind speed is converted into wind power. Different conversion methods are employed and discussed. Kalman filtering techniques are employed to reduce systematic error of the forecasts, both wind and generation. Each 72-h period of the NWP simulations had a computational time of approximately 60–70 min using indicating that the proposed method can be applied in real time for power system operation. The results obtained are very encouraging for further investigation to achieve more accurate wind power researches.

A Novel Model Order Reduction Technique for Linear Continuous-Time Systems Using PSO-DV Algorithm

Abstract: In this paper a new frequency-domain model order reduction method is proposed for the reduction of higher-order linear continuous-time single input single output systems using a recent hybrid evolutionary algorithm. The hybrid evolutionary algorithm is developed from the mutual synergism of particle swarm optimization and differential evolution algorithm. The objective of the proposed method is to determine an optimal reduced-order model for the given original higher-order linear continuous-time system by minimizing the integral square error (ISE) between their step responses. The method has significant features like easy implementation, good performance, numerically stable and fast convergence. Applicability and efficacy of the method are shown by illustrating an IEEE type-1 DC excitation system, and by a typical ninth-order system taken from the literature. The results obtained from the proposed algorithm are compared with many familiar and recent reduction techniques that are available in the literature, in terms of step ISE values and impulse response energies of the models. Furthermore step and frequency responses are also plotted.

Detecting Inter-Turn Short-Circuit Fault in Induction Machine Using High-Order Sliding Mode Observer: Simulation and Experimental Verification

Abstract: In this article, a fault detection method is proposed for induction machine which suffers from inter-turn short-circuit fault. An induction machine mathematical model with considered fault is developed to study the fault impact. A high-order sliding mode observer is used to estimate rotor flux and three-phase stator current under healthy and faulty conditions. Based on measured and estimated three-phase stator currents comparison, a fault detection method is designed. This comparison produces sets of residuals sensitive to fault. The analysis of these residual signals is used to detect the stator windings damages. Simulation and experimental results are presented to validate the proposed fault detection scheme.

Practically Implementable Model Predictive Controller for a Twin Rotor Multi-Input Multi-Output System

Abstract: Model Predictive Control (MPC) is a well-established control strategy for the optimal control of constrained multivariable systems. Twin Rotor Multi-Input Multi-Output System (TRMS) is a nonlinear system with significant cross-coupling between the horizontal and vertical axes presenting formidable challenges in modelling and control design. There are instances when a theoretical design may pose problems when it comes to practical implementation, particularly when the design is for nonlinear systems. In this context, this paper presents a practically implementable MPC design for TRMS which has been implemented successfully on a laboratory TRMS test-rig. The presented design is more suited for TRMS because it can handle the control constraints associated with the system through the optimization algorithm underlying the MPC scheme. From the view point of the system, all the control objectives are addressed, viz., stabilizing the system in a coupled condition and making its beam to track a specified reference trajectory or reach desired positions in 2DOF (two degrees of freedom) without violating the control input constraints. The design also incorporates the disturbance rejection requirement. Both simulation and experimental results are presented to show that the results from practical implementation are in accordance with the simulated results.

Modelling and Control of Transformer-less Universal Power Quality Conditioner (TUnPQC): An Effective Solution for Power Quality Enhancement in Distribution System

Abstract: This paper presents a custom power device, named as Transformer-less Universal Power Quality Conditioner (TUnPQC), for load compensation applications in three-phase system. The TUnPQC consists of shunt and series compensators without a common DC link. The shunt compensator prevalently known as distribution static compensator (DSTATCOM) eliminates the current harmonics instigating from the nonlinear loads. The series compensator of the proposed system, also known as transformer-less dynamic voltage restorer, eliminates voltage-related power quality problems without using any injecting transformer. The proposed configuration is more appropriate for the applications where size and weight are critical decisive factors. The switching scheme of TUnPQC utilizes the discrete model of the system for generation of pulses. Functionalities of TUnPQC-connected system are analysed and tested through MATLAB/Simulink. The results demonstrate the efficacy of TUnPQC in mitigating the effects of voltage sag/swell and also in suppressing the load current harmonics.

Robust $$H_{\infty }$$ H ∞ Filters for Uncertain Systems with Finite Frequency Specifications

Abstract: This paper deals with $$H_{\infty }$$ filtering problem of linear discrete-time uncertain systems with finite frequency input signals. The uncertain parameters are supposed to reside in a polytope. By applying the generalized Kalman–Yakubovich–Popov lemma, polynomially parameter-dependent Lyapunov function and some key matrices to eliminate the product terms between the filter parameters and the Lyapunov matrices, an improved condition is obtained for analyzing the $$H_{\infty }$$ performance of the filtering error system. Then sufficient condition in terms of linear matrix inequality is established for designing filters with a guaranteed $$H_{\infty }$$ filtering performance level. Finally, a numerical examples are used to demonstrate the effectiveness of the proposed method.

State Feedback Decoupling Control of a Control Moment Gyroscope

Abstract: Control moment gyroscope (CMG) is an actuator commonly used in attitude control of satellites and spacecrafts, as well as in stabilization of marine vessels and unmanned vehicles. It is a nonlinear multivariable system and presents considerable coupling depending on the chosen operating point, i.e., the gyroscope gimbals angles. First, the complete modeling of a CMG with four degrees of freedom is shown using the Lagrangian dynamic formulation, resulting in a set of four nonlinear equations. Further, the system is linearized around an equilibrium point, resulting in a coupled two-input two-output system. Next, the application of a linear state feedback decoupling control to this linearized system is developed based on the classical Falb–Wolovich method. Aiming to deal with stationary errors, simple decentralized proportional-integral controllers are designed for each channel. Simulation and practical results with a didactic control moment gyroscope are presented in order to validate the methodology. The resulting system has good decoupling characteristics and presents satisfactory responses in terms of setpoint tracking and disturbance rejection.

Application of Robust Optimization Approach to Determine Optimal Retail Electricity Price in Presence of Intermittent and Conventional Distributed Generation Considering Demand Response

Abstract: In this paper, a robust optimization approach is proposed to determine selling electricity price for a retailer who procures its obligated energy through two different resources: (1) wholesale market and (2) self-generation facilities. Regarding the self-generation facilities, two different kinds of distributed resources, including gas turbine units (GT) and roof-top photovoltaic sites (RPV) with considering energy storage systems (ESS), are addressed as the deterministic and intermittent power resources. Considering the wholesale market, the retailer can procure some parts of its obligated energy through bilateral contracts and day-ahead market. To overcome the uncertainties associated with power output forecasting of solar sites, a new statistical approach is used considering the dependency of power output to the weather issues, such as irradiation, temperature and wind speed. The problem is formulated by using a robust mixed-integer quadratic program considering a confidence bound for the wholesale electricity price uncertainty. To determine the optimal selling price, a successive algorithm is developed through two iterative optimizations, including inner and outer iterative procedures. Regarding the outer optimization, the confidence bound of wholesale electricity price is portioned into subintervals to evaluate the impacts of each robust subregion of wholesale price on the offered retail selling price. Through the inner optimization, the consumers’ response to the offered price is evaluated using a complete demand function model. Finally, a case study containing the bilateral contracts, wholesale market, RPV units, GT units, ESS, flexible demands and the retailer providing demand response is considered to demonstrate the proficiency of the proposed approach.

Modeling, Design and Control of a Solar Array Simulator Based on Two-Stage Converters

Abstract: Power inverters for photovoltaic (PV) applications must be tested according to standards in order to be certified and commercialized. A common practice to test PV inverters is the utilization of solar array simulators (SAS). This paper presents a SAS topology based on a double-stage structure: The first stage is based on a three-phase PWM rectifier, and the second stage is based on a bidirectional buck converter. This structure is responsible to emulate the photovoltaic array behavior. A methodology to design the SAS components and control system parameters is presented. This methodology considers a range of operation points of the SAS. Additionally, it is verified that the dc-link capacitance of the inverter under test can affect the SAS dynamic behavior and its output current ripple. The results are divided into two parts: resistive loads and commercial inverters. Firstly, the SAS steady-state operation following the solar array I–V curve is demonstrated through simulation and experimental results, using resistive loads. In the second part, two commercial inverters with different nominal power and dc-link capacitance are considered. Using the proposed design methodology, the SAS topology operates correctly and the maximum power point tracker of the inverter under test is not affected if its input capacitance is within the design limits.

FPGA-Based Reconfigurable PWM Generator for Power Electronic Converter Applications

Abstract: Application of digital hardware based on FPGA in power electronic converters control systems has grew up in recent years One of the most important issues in hardware implementation of power converters controller systems is the PWM signal generation This issue is more important in case of multi-level converters with several carries Implementation of these types of PWM strategies with conventional PWM peripherals in existing DSPs and microcontroller is very complicated and sometimes impossible, because existing PWM generation peripherals are based on single carrier and optimized for two-level inverter applications This paper presents a multi-carrier-based generalized reconfigurable PWM generator hardware that can be used in power electronic converters control systems The proposed hardware can be implemented on both FPGA and ASIC as a peripheral for a main processor The proposed architecture can be easily configured to support several PWM strategies including conventional single-carrier and novel multi-carrier PWM techniques The proposed hardware includes output control and programmable dead-band generator module as well The system function selection and other configurations can be carried out using dedicated control and configuration registers Whole architecture and internal modules are designed and implemented in Verilog HDL and simulated then synthesized and tested successfully on Altera Cyclone II FPGA using FPGA development board and laboratory prototypes Simulation and experimental results for various types of modulation strategies are presented verifying generality and reconfigurability of the proposed hardware

Performance Analysis of Profibus DP and Profinet in a Motion Control Application

Abstract: This work proposes a performance analysis of industrial communication networks applied in a widely used motion control application of an electric AC motor. It compares Profinet and Profibus DP technologies. Performance is evaluated from technical specifications of both protocols and practical experiments for data collection and analysis of the following indicators: cycle time and jitter. As these protocols are used in the loop control, another indicator is used from the control engineer point of view, the settling time of motor position control. Conclusions show that Profibus DPV0 is faster; however, Profinet version IRT has higher determinism. Both achieved settling time that could accomplish the application.

ANN-Based SVC Tuning for Voltage and Harmonics Control in Microgrids

Abstract: A method for tuning a static var compensator for voltage control and reduction of harmonic distortion in a microgrid is presented in this paper. Electrical power distribution systems face a new scenario with an increasing number of distributed generation sources, nonlinear loads and more strict power quality requirements. In addition, it can be observed that there is a tendency for power systems to operate within the context of smartgrids. Consequently, the operation of such systems become more complex and, therefore, requires a power quality conditioning technique able to adapt itself to the grid. The application of a static var compensator with an additional filtering function at the point of common coupling of a power system with a microgrid is a possible solution. In this context, the proposed approach is based on artificial neural networks to determine the static var compensator tuning in order to recognize the loading and distributed generation steady-state conditions. Simulation results show that this approach provides the control system with more intelligence and the capability of adapting to different operating conditions.

Effects of Electronic Loads on Electrical Measurements, Power Quality and Billing

Abstract: This paper presents results from experimental studies carried out using an electronic device called a Dimmer Flex, developed at the Federal University of Mato Grosso, Brazil. The Dimmer Flex is able to evaluate the effects of electronically switched loads regarding electrical measurements, especially focusing on billing. It can be concluded from the studies that, depending on the switching characteristics, a switched load can be “transformed” to the meter in a load with inductive or capacitive behavior, therefore “absorbing or injecting” reactive power to the system it is connected to. This finding shows that electronically switched loads can interfere in electrical measurements and consequently may affect the billing process, underlining the need to evaluate, discuss and even review current measurement and billing methods.

Extended State Observer-Based Sliding Mode Control for Multi-input Multi-output System with Multiple Disturbances

Abstract: This paper proposes a generalized design procedure for the extended state observer-based sliding mode control for multi-input multi-output linear systems with multiple disturbances (matched and/or mismatched) using an extended state observer. First, the system is transferred to a regular form to decouple the states having matched and mismatched uncertainties; then, a novel sliding surface is designed based on the state and disturbance estimation obtained through extended state observer (ESO). The proposed generalized ESO-based sliding mode controller (SMC) is designed to counteract the effect of matched and/or mismatched disturbances which are bounded, while the classical SMC fails to provide the desired performance in the presence of mismatched disturbance. This paper develops a simple method for the design of sliding surface coefficients and the selection of switching gain. The proposed control strategy is validated through numerical simulations, and the comparison with ESO-based state feedback control shows a reduced-order closed-loop dynamics and better transient performance.

Combined Discrete-time Sliding Mode and Disturbance Observer for Current Control of Induction Motors

Abstract: This paper proposes a composite control strategy which combines a discrete-time sliding mode controller with a disturbance observer aiming to decouple current control of vector oriented induction motor drives. The stator current control is carried out through an indirect field orientation in a dq reference frame rotating at synchronous speed. The cross-coupling variables of the induction motor stator currents at synchronous reference frame are modeled as disturbances, and these values are estimated using a discrete-time disturbance observer. The digital implementation delay was included in the plant model formulation, resulting in a control law suitable to direct implementation in microcontrollers and digital signal processors. Then, the nominal and decoupled part of the induction machine model is used for the design of the sliding mode controller, and the additional variables are modeled as disturbances. The cross-coupling variables are observed and used in the control law. The convergence analysis is presented in discrete-time domain. Simulation and experimental results are presented to validate the theoretical analysis, and they show the good performance of the proposed method.

Synchrophasors-Based Transmission Line Protection in the Presence of STATCOM

Abstract: Distance relay identifies the type and location of fault by measuring the transmission line impedance. However, any other factors that cause miscalculating the measured impedance make the relay detect the fault in incorrect location or do not detect the fault at all. One of the important factors which directly increases the measured impedance by the relay is fault resistance. Another factor that indirectly changes the impedance of the transmission line is static synchronous compensator (STATCOM). When a fault occurs, measured signals by the relay change due to the variation of current injected by the STATCOM and it makes the calculated impedance to be incorrect. This paper provides a method based on the combination of distance and differential protection. At first, faulty transmission line is detected according to the current data of buses. After that the fault location is calculated using the proposed algorithm on the transmission line. This algorithm is based on active power calculation of the buses. Fault resistance is calculated from the active powers, and its effect will be deducted from calculated impedance by the algorithm. Furthermore, by choosing the appropriate data bus, the effect of STATCOM is eliminated and fault location will be detected.

Adaptive Iterative Learning Control of Nonlinearly Parameterized Pure Feedback Nonlinear Systems

Abstract: In this work, an adaptive iterative learning control scheme is proposed to deal with nonlinearly parameterized and completely non-affine pure feedback nonlinear systems. The considered systems are assumed to perform the same operation repeatedly under alignment condition. To overcome the design difficulty from non-affine structure of pure feedback system, mean value theorem is exploited to deduce affine appearance of state variables to be used as virtual controls and actual control. The nonlinearly connected parameters are separated from the local Lipschitz continuous nonlinear functions, and then iterative learning laws and adaptive iterative learning laws are designed. Lyapunov functional stability analysis method has been used to prove the stability of the closed-loop control system and the convergence of tracking error to zero as iteration goes to infinity. Simulation results are provided to illustrate the performance of the proposed scheme.

Adaptive Neuro-Fuzzy Black-Box Modeling Based on Instrumental Variable Evolving Algorithm

Abstract: In this paper, an online identification algorithm for instrumental variable-based evolving neuro-fuzzy modeling applied to dynamic systems in noisy environment is proposed. The adopted methodology is based on neuro-fuzzy inference system with Takagi–Sugeno evolving structure, which employs an adaptive distance norm based on the maximum likelihood criterion with instrumental variable recursive parameter estimation. The application and performance analysis of the proposed algorithm is based on black-box modeling of a 2DOF Helicopter with errors in variables.

Evaluation of Nonlinear Model-Based Predictive Control Approaches Using Derivative-Free Optimization and FCC Neural Networks

Abstract: Nonlinear control methods have been researched with the objective of improving performance of control loop systems. Among such control methods, nonlinear model-based predictive control (NMPC) strategies present significant importance, mainly due to explicit performance optimization and constraint handling. NMPC depends on a representative nonlinear model of the process to be controlled and an adequate optimization method. This work focuses on these two aspects. Simulation tests with a wastewater treatment process model are presented, to evaluate the use of two optimization methods, differential evolution and bound optimization by quadratic approximation (BOBYQA), under different conditions. Experimental results using BOBYQA and a fully connected cascade artificial neural network in a pressure process are presented, showing a performance improvement comparing to a linear model predictive controller.

Adaptive Fuzzy Logic Control for a Class of Unknown Nonlinear Dynamic Systems with Guaranteed Stability

Abstract: In this paper, a stability analysis is suggested for adaptive fuzzy logic systems (FLSs) without the requirement of states measurement or estimation. Fuzzy logic is viewed as a powerful tool in providing accurate approximation of systems with uncertainties. The proposed methodology exploits the power of adaptive control theory to find a Lyapunov-based adaptation law for FLSs. As such, both stability and tracking problems are addressed for a class of nonlinear dynamic systems. The proposed method yields reduced complexity with respect to many adaptive FLSs available in the literature. In addition, the use of an observer to estimate immeasurable states is not required as in other methods. First, a stability analysis is presented for adaptive control. Then, results are extended to adaptive FLSs with unknown dynamics. A numeric illustrative example highlights the implementation details and the performance of the suggested scheme.

Robust Stabilization of Inverted Pendulum Using ALQR Augmented by Second-Order Sliding Mode Control

Abstract: In this paper, a robust nonlinear control design strategy to solve the stabilization problem of an inverted pendulum system subject to parametric uncertainties and unmodeled dynamics is proposed. The control strategy is based on the combination of Amplified Linear Quadratic Regulator (ALQR) control with a high-order sliding mode algorithm. Differently from the standard ALQR controller, parametric uncertainties are considered in the design process. Linear matrix inequality conditions are provided to deal with the computational issues arising with the inclusion of this feature. A sliding mode term is added to the ALQR control law to mitigate the effect of unmodeled dynamics, such as dry friction, neglected in the system model. In order to prevent the occurrence of chattering, a high-order sliding mode approach was used, namely the second-order super-twisting algorithm. The effectiveness of the proposed strategy is evaluated through a real experiment performed using the Quanser inverted pendulum plant.