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Five-level rectifiers have received widespread attention because of their excellent performance in high-voltage and high-power applications. Taking a five-level rectifier with only four-IGBT for this study, a sliding mode predictive control (SMPC) algorithm is proposed to solve the problem of poor dynamic performance and poor anti-disturbance ability under the traditional model predictive control with the PI outer loop.

First, mathematical models under the two-phase stationary coordinate system and two-phase synchronous rotating coordinate system are established. Then, the design of the outer-loop sliding mode controller is completed by establishing the sliding mode surface and design approach rate. The design of the inner-loop model predictive controller was completed by discretizing the mathematical model equations. The modulation part uses a space vector modulation technique to generate the PWM wave.

The sliding mode predictive control strategy is compared with the control strategy with a PI outer loop and a model predictive inner loop. The proposed control strategy has a faster dynamic response and stronger anti-interference ability.

For the five-level rectifier, the advantages of fast dynamic influence and parameter insensitivity of sliding mode control are used in the voltage outer loop to replace the traditional PI control, and which is integrated with the model predictive control used in the current inner loop to form a novel control strategy with a faster dynamic response and stronger immunity to disturbances. This novel strategy is called sliding mode predictive control (SMC).

This paper proposes an ANN based adaptive damping control scheme for the unified power flow controller (UPFC) to damp the low frequency electromechanical power oscillations. In this paper a novel damping control strategy based on the time‐domain analysis of system transient energy function (TEF) is proposed and implemented by using well tuned conventional PI controllers to obtain the preliminary training data for the design of the proposed controllers. The multi‐layered feed forward neural network with error back‐propagation training algorithm is employed in this study. Models of UPFC and ANN controllers suitable for incorporating with the transient simulation programs are derived and tested on a revised IEEE nine‐bus test system. Comprehensive simulation results demonstrate the great potential of using UPFC in damping control and the excellent performance of the proposed control scheme.

This paper aims to propose a novel active SLAM framework to realize avoid obstacles and finish the autonomous navigation in indoor environment.

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. The localization of the robot is based on FastSLAM algorithm.

Simulation results of avoiding obstacles using traditional Q-learning algorithm, optimized Q-learning algorithm and FOQL algorithm are compared. The simulation results show that the improved FOQL algorithm has a faster learning speed than other two algorithms. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

The purpose of this paper is to propose a novel self-adjusting proportional integral (SA-PI) controller, for controlling the active and reactive power of permanent magnet synchronous generator (PMSG) when subjected to variable wind speed and parameter variations.

The proportional and integral gains of the proposed SA-PI controller are based on tan-hyperbolic function and adjust themselves automatically within pre-fixed limits according to the error occurring during transient situations.

The proposed SA-PI controller is able to evade the problems usually encountered while using a constant gain PI controller, such as lack of robustness, adaptability and a wide range of operation. It also damps out system oscillations faster with reduced settling time and fewer overshoots.

Simulation results and comparative studies with conventional PI controller and the differential evolution–optimized PI (DE-PI) controller reveal the effectiveness of the proposed control scheme. MATLAB is used to perform the simulation studies.

The purpose of this paper is to improve transient response and dynamic performance of automatic voltage regulator (AVR).

This paper proposes a novel fractional order proportional–integral–derivative plus derivative (PI^λD^µD^µ2) controller called FOPIDD for AVR system. The FOPIDD controller has seven optimization parameters and the equilibrium optimizer algorithm is used for tuning of controller parameters. The utilized objective function is widely preferred in AVR systems and consists of transient response characteristics.

In this study, results of AVR system controlled by FOPIDD is compared with results of proportional–integral–derivative (PID), proportional–integral–derivative acceleration, PID plus second order derivative and fractional order PID controllers. FOPIDD outperforms compared controllers in terms of transient response criteria such as settling time, rise time and overshoot. Then, the frequency domain analysis is performed for the AVR system with FOPIDD controller, and the results are found satisfactory. In addition, robustness test is realized for evaluating performance of FOPIDD controller in perturbed system parameters. In robustness test, FOPIDD controller shows superior control performance.

The FOPIDD controller is introduced for the first time to improve the control performance of the AVR system. The proposed FOPIDD controller has shown superior performance on AVR systems because of having seven optimization parameters and being fractional order based.

The purpose of this paper is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods.

T transformation used for conversion of instantaneous rotor currents electrical circuit representation to space vector components is investigated to apply with closed‐loop modeling algorithm. Evaluation of the algorithm is based on analysis of asymmetry influence to the orthogonal and zero components of space vector representation. Multiscalar model of the machine and selected structures of state observers are used for sensorless control system synthesis. Proposed method of frequency characteristics calculation is used for state observers analysis in open‐loop operation.

New algorithm of applying the T transformation allows for closed‐loop and sensorless control system simulation with asymmetric machine due to broken rotor. Compensating effect of the closed‐loop control system with speed measurements and diagnosis information in control system variables are identified. Proposed frequency analysis of state observers is presented and applied. Variables with amplified characteristic frequency components related to rotor asymmetry are compared for selected structures of state observers and with closed‐loop and open‐loop operation. Method of improving the sensorless system stability is proposed.

In closed‐loop and sensorless control system rotor fault can be diagnosed by using PI output controllers variables. Compensating effect of mechanical variables sets limitation to specified diagnosis methods. Rotor asymmetry affects sensorless control system stability depending on estimator structure.

This paper concentrates upon sensorless control system operation with machine asymmetry and indicates rotor fault symptoms.

The purpose of this research is to design a robust high-performance nonlinear multi-input multi-output heating, ventilation and air conditioning (HVAC) system controller for temperature and relative humidity regulation. Buildings are complex systems which are subjected to many unknown disturbances. Further complicating the control problem is the fact that, in practice, buildings and their systems have static nonlinearities such as power saturation that make stability difficult to guarantee. Therefore, in order to overcome these issues, a control system must be designed to be robust (performance insensitive) against uncertainties, static nonlinearities and effectively respond to unknown heat load and moisture disturbances.

A state of the art nonlinear inverse dynamics (NID) technique is combined with a genetic algorithm (GA) optimisation scheme in order to improve robustness against uncertainty in the system's modelling assumptions. The parameter uncertainty problem is addressed by optimising the control system parameters over a specified range of uncertainty. The NID control structure provides further robustness with effective disturbance handling and a stability criteria that holds in the presence of actuator saturation.

The proposed method delivers significantly more energy efficient performance whilst achieving improved thermal comfort when compared with a current industry standard HVAC controller design such as proportional-integral-derivative. The expected excellent response to disturbances is also demonstrated.

This method can easily be extended to account for other parameters with a specified uncertainty range.

This research presents a method of optimised NID controller design which can be easily implemented in real HVAC controllers of building energy management systems with a high degree of confidence to provide high levels of thermal comfort whilst significantly reducing energy usage.

A novel HVAC optimised NID control strategy using the robust inverse dynamics estimation feedback control topology with GA optimisation for improved robustness and tuning over a range of parameter uncertainty is described, designed and its performance benefits shown through simulation studies.

The paper has proposed to implement gray wolf optimization (GWO)-based filter-type proportional derivative with (FPD) plus (1+ proportional integral) multistage controller in a three-area integrated source-type interlinked power network for achieving automatic generation control.

For analysis, a three area interconnected power system of which each area comprises three different generating units where thermal and hydro system as common. Micro sources like wind generator, diesel generator and gas unit are integrated with area1, area2 and area3 respectively. For realization of system nonlinearity some physical constraints like generation rate constraint, governor dead band and boiler dynamics are effected in the system.

The supremacy of multistage controller structure over simple proportional integral (PI), proportional integral, derivative (PID) and GWO technique over genetic algorithm, differential evolution techniques has been demonstrated. A comparison is made on performances of different controllers and sensitivity analysis on settling times, overshoots and undershoots of different dynamic responses of system as well as integral based error criteria subsequent a step load perturbation (SLP). Finally, sensitive analysis has been analyzed by varying size of SLP and network parameters in range ±50 per cent from its nominal value.

Design and implementation of a robust FPD plus (1 + PI) controller for AGC of nonlinear power system. The gains of the proposed controller are optimized by the application of GWO algorithm. An investigation has been done on the dynamic performances of the suggested system by conducting a comparative analysis with conventional PID controller tuned by various optimization techniques to verify its supremacy. Establishment of the robustness and sensitiveness of the controller by varying the size and position of the SLP, varying the loading of the system randomly and varying the time constants of the system.

Based on the inverse kinematics and task space dynamic model, this paper aims to design a high-precision trajectory tracking controller for a 2-DoF translational parallel manipulator (TPM) driven by linear motors.

The task space dynamic model of a 2-DoF TPM is derived using Lagrangian equation of the first type. A task space dynamic model-based feedforward controller (MFC) is designed, which is combined with a cascade PID/PI controller and velocity feedforward controller (VFC) to construct a hybrid PID/PI+VFC/MFC controller. The hybrid controller is implemented in MATLAB/dSPACE real-time control platform. Experiment results are given to validate the effectiveness and industrial applicability of the hybrid controller.

The MFC can compensate for the nonlinear dynamic characteristics of a 2-DoF TPM and achieve better tracking performance than the conventional acceleration feedforward controller (AFC).

The task space dynamic model-based hybrid PID/PI+VFC/MFC controller is proposed for a 2-DoF linear-motor-driven TPM, which reduces the tracking error by at least 15 percent compared with conventional hybrid PID/PI+VFC/AFC controller. This control scheme can be extended to high-speed and high-precision trajectory tracking control of other parallel manipulators by reprogramming the feedforward signals of traditional cascade PID/PI controller.

This paper aims to present a hybrid actuator controller to obtain fast and stiff position response without any overshoot by blending input signals of a DC servomotor and a particle brake.

The hybrid actuator controller has a module to estimate instantaneous changes in inertia and a blending algorithm that adjusts input signals to the motor and the brake so that together, as a hybrid actuator, they can achieve a fast, stiff position response without overshoot. The control logic implemented in the controller is derived from the kinematics of the system. For the blending algorithm, two separate cases are explored in which the user has the option to either utilize the full‐braking capacity or specify a safe deceleration limit for the system.

The blending algorithm enables the system to operate nearly twice as fast as the motor‐only case without any overshoot or oscillations. The controller can reject inertial load changes and significant external disturbances.

Such hybrid actuators along with the developed controller can be used in robotics and automation to increase the system accuracy and operational speed resulting in higher production rates. In addition, much stiffer haptic force feedback interfaces for virtual reality applications can be designed with smaller actuators. The blending algorithm provides considerable improvements and uses a physics‐based simple and easy‐to‐implement structure.