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Aiming at the problem of optimal design of the controller of electromagnetic levitation system, this paper proposes a gradient estimator-based controller design and optimization structure suitable for electromagnetic levitation system. The structure consists of a nominal controller, a residual generator, and a dynamic compensator. The controller structure can further improve the anti-disturbance and robustness of the electromagnetic levitation system on the premise of ensuring the stability and reliability. Considering the generality of electromagnetic levitation system, the proportional–integral–derivative (PID) controller is selected as the nominal controller, and the robustness of the system is improved by the dynamic compensator based on the residual generator. The parameter design and update strategy of dynamic compensator based on gradient estimator are proposed, and the expression of gradient estimator is designed and deduced. Taking the single-degree-freedom electromagnetic levitation experimental platform as an example, the simulation and experimental results show that the structure has strong robustness to shock disturbances. Compared with the PID controller, the range of the gap fluctuation is smaller after the instantaneous impact interference, and the anti-interference capability of the electromagnetic levitation system is improved. [ABSTRACT FROM AUTHOR]

The response-based design approach is a straightforward method for proportional–integral–derivative (PID) controller tuning. In this method, an open-loop process response is used to tune the PID controller for fixed robustness. In this article, new response-based PID tuning rules are proposed with adjustable robustness and response. Instead of three PID variables, the proposed PID tuning method allows the user to adjust the process response with a single variable (ψ). The range of constant (ψ) is provided for ensuring the stability of the process. Three MATLAB/SIMULINK examples and one temperature controller experiment are used to validate the proposed controller performance. The simulation result is also compared with three well-known response-based PID tuning rules Z-N, Cohen-Coon, Astrom et al., and with a model-based PID tuning proposed by Wang et al. Moreover, the proposed tuning provides lesser IAE, ITAE, ISE, and ITSE values than the existing methods. [ABSTRACT FROM AUTHOR]

In this article, a new multiobjective particle swarm optimization (MOPSO) algorithm is introduced to improve the performance of a sliding mode based robust fuzzy proportional–integral–derivative (PID) controller. In this regard, the non-dominated solution having minimum number of neighbors is considered as the global best position, while the sigma values of the members are employed to determine the personal best position. A modified multiple-crossover operator is combined with the operators of the particle swarm optimization to significantly increase the convergence speed of the algorithm. To limit the size of the archive, a dynamical elimination scheme defined in the Euclidean space is introduced. Besides, iteration-based linear relations are implemented to adaptively compute the inertia weight and learning coefficients. To evaluate the effectiveness of the introduced MOPSO algorithm, the requirements are conducted by means of three benchmark functions with regard to generational distance, spacing, and maximum spread metrics. This analysis demonstrates that the proposed algorithm operates better through comparison with well-known elitist multiobjective evolutionary algorithms. Moreover, the MOPSO algorithm is applied for optimal design of a hybrid robust fuzzy PID controller for a pneumatic system with two bellows. Conflicting objective functions are considered as the normalized values of overshoot and settling time of the displacement between the bellows that should be simultaneously minimized. The feasibility and efficiency of the strategy are assessed in comparison with the conventional controllers. [ABSTRACT FROM AUTHOR]

Allowing for a "virtual" full actuation of a rotary inverted pendulum (RIP) system with only a single physical actuator has been a challenging problem. In this paper, a hybrid control scheme that involves a pole-placement feedback controller and an optimal proportional–integral–derivative (PID) or fractional-order PID (FOPID) controller is proposed to simultaneously enable the tracking control of the rotary arm and the stabilization of the pendulum arm in an input–output feedback linearized RIP system. The PID controller is optimized first with the particle swarm optimization (PSO) to obtain three optimal gains, and then the other two parameters of the FOPID controller are optimized with the PSO. Compared to the optimized PID controller, the optimized FOPID controller improves the tracking and stabilizing accuracy by 53% and 29%, respectively, and demonstrates better adaptability for tracking different reference signals. Moreover, the hybrid FOPID controller exhibits 74.8% and 53% higher tracking accuracy than previous optimized model reference adaptive control PID (MRAC-PID) and linear–quadratic regulator (LQR) controllers, respectively. The proposed hybrid controllers are also digitized with different rules and sampling times, showing a closer performance between the discrete-time and continuous-time hybrid controllers under smaller sampling times. [ABSTRACT FROM AUTHOR]

The search for a better approach to design a convenient controlling scheme is one of the main challenges of the research field related to power converters. This paper brings forward a significant contribution as part of this challenge. In this regard, novel approaches have been proposed for both controller scheme and tuning algorithm. In terms of controlling scheme, a fractional-order proportional–integral–derivative (FOPID) controller was used alongside the Bode's ideal transfer function to achieve optimum performance of a buck converter system. To achieve a greater performance of the FOPID controller, a novel metaheuristic algorithm, which consists of a balanced structure in terms of explorative and exploitative phases, has also been developed by hybridizing the hunger games search algorithm with simulated annealing technique. The proposed hybrid algorithm helped tuning the FOPID controller optimally. The proposed algorithm and controlling scheme have been proved to be a better approach for controlling a buck converter system in terms of time and frequency domains along with disturbance rejection. To further verify the effectiveness of the proposed hybrid algorithm–based controlling scheme, it was compared with other reported and capable approaches which have also confirmed the greater performance of the proposed approach. [ABSTRACT FROM AUTHOR]

In this study, a magnetic actuator is controlled to obtain a constant flow rate micropumping by a magnetic nanofluid flow inside a semicircular-shaped microchannel with a constant square cross-section. A closed-loop control strategy is developed to achieve adequate control by utilizing a model based on experimental data. A novel digital image processing–based real-time velocity estimation algorithm is proposed as feedback information in the closed-loop control system. This paper aims to evaluate the success of the proposed real-time velocity estimation algorithm. The results indicate that the proposed algorithm can supply the fluid velocity inside the microchannel with a maximum deviation of less than 4% in the current micropumping system. Three different controllers—that is, proportional (P), proportional–integral (PI), and proportional–integral–derivative (PID)—are also implemented to test the influence of the control logic used in the closed-loop control strategy. Compared with the previous study, the implementation of a closed-loop control strategy in the present work provided a constant flow rate pumping. The findings reveal that the PID controller can maintain a constant flow rate with transient time values around 186, 94, and 60 seconds for reference values of 100, 200, and 300 µm/s, respectively. In addition, the PID controller could supply a constant flow rate within the microchannel 51% longer than the PI controller. [ABSTRACT FROM AUTHOR]

Wire winding is a key process in transformer manufacturing, and the accuracy of tension control directly affects the quality of the products. To achieve the requirement of constant tension winding of wire, the influence of roll diameter, speed, and other factors on the dynamic performance of tension is analyzed by establishing the dynamic model of unwinding and winding as well as the pendulum part. A control strategy combining proportional-integral-derivative (PID) control with fuzzy control is adopted, and the parameters of the fuzzy PID controller are optimized using an improved genetic algorithm. Simulation results demonstrate that the optimized fuzzy PID controller significantly reduces tension overshoot and effectively suppresses the tension fluctuation when the speed and roll diameter change, and the tension fluctuation is controlled within 2%. Finally, the feasibility of the optimized fuzzy PID controller in the tension control system is experimentally validated. [ABSTRACT FROM AUTHOR]

This paper presents the methodical development of a state-error-driven self-adaptive fractional-order proportional–integral–derivative (AFOPID) control algorithm to efficiently regulate the velocity of pneumatically conveyed particles at the desired set point and to prevent the blockage of particles in a pipe due to an imbalanced combination of their velocity and corresponding mass flow rate. The proposed fractional control law is constituted by adaptively modulating fractional orders of the integral and differential operators in the control based on the state-error variations in the velocity of solid particles. The particle’s velocity is measured and updated via electrostatic sensors in conjunction with cross-correlation signal processing algorithms. All the other fixed hyper-parameters associated with the proportional–integral–derivative (PID) control scheme are meta-heuristically optimized by using a genetic algorithm. The proposed AFOPID is benchmarked against conventional integer-order PID and the fractional-order proportional–integral–derivative (FOPID) controllers. Experiments are performed on a laboratory-scale test rig to comparatively analyze the aforesaid control schemes, where each controller is examined for three velocity set points and three disturbance levels. The experimental results validate the superior time optimality and robustness of the proposed AFOPID controller against bounded disturbances and abrupt velocity set-point variations by manifesting relatively faster settling time, low overshoots (and undershoots), and smaller steady-state fluctuations. [ABSTRACT FROM AUTHOR]

The unexpected heave motion of vessels generated by waves has always threatened the safe operation of mining vessels. The heave compensation system is a critical equipment for offshore cranes to ensure the safety and stability of the deep-sea mining vessel operation. Unfortunately, the nominal load of the mining vessel transporting minerals has become increasingly large, which has led to the dynamic performance of the heave compensation decline and a significant increase in energy consumption. To solve these problems, a semiactive heave compensation system and fuzzy logic-based controller are proposed in this paper. First, an active-passive hybrid heave compensation system is designed to reduce energy consumption greatly. The virtual prototype models of the proposed heave compensation system in a 500-ton deep-sea mining vessel are also built. Then, an adaptive tuning PID controller is developed based on the Transfer function of the heave compensation system and Mamdani-type fuzzy logic. Virtual prototype simulation results of AMESim-Simulink joint simulation illustrate that the accuracy of compensation for the four or six sea states reaches more than 90% with the proposed method and the power of the active compensation system is about 21% of the total power. Finally, the experimental results are included to demonstrate the effectiveness of the proposed semiactive heave compensation system. [ABSTRACT FROM AUTHOR]

Proportional--integral--derivative (PID) stabilization is an important control design strategy that provides the designer with all PID controller set which results control system stability absolutely. In this way, the designer has a wide range of freedom to obtain the controller that meets the desired criteria. This process is particularly advantageous in situations where it is difficult to clearly define the design criteria at the beginning of the design or to make a balanced decision among the design criteria. The main objective of this paper is to present for the first time a PID stabilization method for complex conjugate-order systems, which is a new type of system for the control community and has been little studied on. The method is based on obtaining of stability/instability regions using the D-decomposition method in the controller parameter space graphically. These regions are formed by stability boundaries that are defined as real root, infinite root and complex root boundaries. The stability of the regions is determined using generalized modified Mikhailov stability criterion that is a powerful stability tool of the system theory. The simulation results indicate that the presented stabilization method is effective and practically useful in the analysis and control of the complex conjugate-order systems. [ABSTRACT FROM AUTHOR]

In this research study, a new methodology of multi-objective optimal design is presented for control systems with time delay. Stackelberg method as an approach of game theory is implemented to develop the multi-objective optimization of proportional–integral (PI) and proportional–integral–derivative (PID) controllers. The surface area of control effort and tracking error are put in order of precedence together as the more important conflicting objective functions of the players in Stackelberg game design. Besides, the desirability of other effective criteria including frequency and time domains are measured as constraints in the procedure of the game-theoretic design. The main purpose of the proposed method is to optimally set and formulate controller parameters in the Stackelberg game-control system (SG-CS) design. Mapping the leader's variables into the optimized values of the follower's variables obtained via differential evolution (DE), the effectiveness of the proposed method is demonstrated in constructing a simple and explicit approximate model for rational reaction sets (RRSs). These obtained optimal models for the RRS allow the user to access the set of optimal controller parameters in the entire accessible strategic space of design variables in a formulated form. Utilizing the optimal synthesis for two case studies is validated the superiority of SG-CS design in establishing the explicit relationship between the controller's parameters. [ABSTRACT FROM AUTHOR]

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase the robustness of the AVR. Fuzzy PID controller parameters are determined by a genetic algorithm (GA)-based optimization method using a novel multi-objective function. The multi-objective function, which is important for tuning the controller parameters, obtains the optimal solution using the Integrated Time multiplied Absolute Error (ITAE) criterion and the peak value of the output response. The proposed method is tested on two AVR models with different parameters and compared with studies in the literature. It is observed that the proposed method improves the AVR transient response properties and is also robust to parameter changes. [ABSTRACT FROM AUTHOR]

Control strategies for uncertainties or nonlinear effects need to be developed for control systems. Optimization algorithms developed with the rapid development of computer technology are frequently used to improve the steady-state response with the help of the ambiguous mathematical characteristics or nonlinearity of control systems. In this study, an optimum proportional–integral–derivative (PID) controller was designed using the wound healing algorithm based on the clonal selection principle. The proposed algorithm is applied in self-tuning a PID controller in the ball and hoop system which represents a system of complex industrial processes. In order to adjust the PID parameters with the aid of the developed algorithm, an integral absolute error (IAE) has been chosen as the objective function. Thus, the system reached the optimum solution quickly and time was saved. The advantages of the proposed algorithm have been proved by comparing the obtained results with other algorithms. To succeed this, a programme was written in the MATLAB GUI environment. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synthesis of proportional–integral–derivative (PID) controller according to the H ∞ optimality criterion for seesaw-cart system. The equations of dynamics are obtained through modelling a seesaw-cart system actuated by direct-current motor via rack and pinion mechanism using the Euler–Lagrange approach. The obtained model is linearised and synthesis of the PID controller for linear model is performed. An algorithm based on the sub-gradient method, the Newton method, the self-adapting backpropagation algorithm and the Adams method is proposed to calculate the PID controller gains. The proposed control strategy is tested and compared with standard linear matrix inequality (LMI)-based method on computer simulations and experimentally on a laboratory model. [ABSTRACT FROM AUTHOR]

This paper introduces a novel design of a proportional filtered-integral (P-FI) controller whose parameters are auto-tuned using the backpropagation neural networks (BPNN) algorithm. The proposed controller is designed to address the main challenges posed by a class of complex systems characterized by uncertain high-gain and pure integrator dynamics, including high-frequency noise amplification and poor robustness against parameter variations. Designing such a controller involves three main steps: First, a proportional–integral–derivative (PID) controller is designed, with its parameters auto-tuned online using the BPNN algorithm, resulting in the primary (BPNN-PID) controller. Second, the obtained parameters of the previous controller are utilized to compute those of a low-pass filter offline. This filter is then cascaded with the integral parts of a PID controller, forming a P-FI controller structure. This configuration introduces a phase lead within a specific frequency range without amplifying high-frequency noise, overcoming the primary disadvantage of the derivative term. Finally, the parameters of the resulting P-FI controller are again auto-tuned online using the BPNN algorithm, resulting in the final robust (BPNN-P-FI) controller. This novel controller structure and its parameters tuning procedure, based on a two-stage BPNN learning approach, constitute the main contributions of this paper. Simulation results demonstrate the superiority of the proposed controller in terms of time-domain performance, sensor noise attenuation, and closed-loop robustness compared to those obtained with the BPNN-PID and optimally tuned PID controllers. [ABSTRACT FROM AUTHOR]

Coupled nonlinear systems are difficult to control due to the adverse effects of uncertainties and coupling effects with increased sensor noise. This paper proposes an improved Lyapunov-based composite controller consisting of fractional-order proportional–integral–derivative (FOPID) and velocity-based disturbance observer to deal with the motion control of uncertain, nonlinear, and coupled system. FOPID utilizes the stable filtered error to facilitate the control development and stability analysis for the multi-input multi-output (MIMO) coupled system. Moreover, a disturbance observer is developed by utilizing the velocity signals to provide robustness against the disturbances and parametric uncertainties. Enhanced infinite order disturbance observer (EIFDOB) structure is used to improve the robustness of the introduced technique despite the high-frequency sensor noise. Stability analysis is provided to verify the introduced controller through the Lyapunov stability theorem, LaSalle’s invariance principle, and Barbalat’s lemma. Signal chasing is also presented to show that all signals are ultimately bounded. Comprehensive numerical simulations are performed on high-fidelity and coupled nonlinear model of the twin rotor MIMO system where the efficiency of the presented technique is examined against the external disturbances, matched uncertainties, and sensor noise. The results presented with different scenarios show that the proposed technique performed better with more robustness than FOPID and integer order proportional–integral–derivative. [ABSTRACT FROM AUTHOR]

Time-delay characteristics of various industrial processes may degrade the stability and dynamic performance of the control systems. Aiming at the problems of the existing methods in dealing with the time delay plant, a modified fractional-order proportional–integral–derivative (FOPID) controller for the first-order plus time-delay (FOPTD) system is developed. Assisted by a modified active disturbance rejection control (ADRC) scheme with increased observer bandwidth, the proposed FOPID controller inherently obtains good robustness to time-delay uncertainties and external disturbances. In addition, taking advantage of the fractional-order operator, the proposed controller can provide larger stability margin over the proportional–integral–derivative (PID) controller. By suitably establishing the relation between ADRC and FOPID controller parameters, the proposed controller can be analytically tuned based on the common design indices. A practical tuning guideline is developed according to frequency-domain characteristic analysis, making the proposed controller more acceptable to industrial application. The performance of the ADRC-based FOPID controller is tested by the control simulation of some typical FOPTD systems and a diesel engine speed regulation system. The efficiency of the ADRC-based FOPID controller is demonstrated by the comparisons with some existing controllers. [ABSTRACT FROM AUTHOR]

The external disturbances and backlash hysteresis kind of nonlinearity present in the manipulator system can greatly affect the tracking performance of the system. In order to undo the effects of these external disturbances and backlash hysteresis, a robust controller is established based on the integration of self-tuning fuzzy nonsingular proportional-integral-derivative (PID) type fast terminal sliding mode control and time delay estimation (TDE). In this paper, TDE plays the part of estimating the unknown dynamics of the robotic manipulator and nonsingular PID type fast terminal sliding mode control in which the gains of PID are tuned using fuzzy logic system to get multiple beneficial characteristics, such as lower steady-state error, finite-time convergence and little chattering. In addition, the derivative of unknown dynamics that is considered to be bounded is dealt by utilizing the adaptive technique. Moreover, Lyapunov theorem is used to study the overall stability of the system. Finally, a comparative study in terms of trajectory tracking has been carried out between the proposed controller and other existing advanced control approaches using PUMA560 robot in order to verify the effectiveness of the proposed controller in the presence of external disturbances and bacsklash hysteresis. [ABSTRACT FROM AUTHOR]

This paper deals with the design of an optimally performed proportional–integral–derivative (PID) controller utilized for speed control of a direct current (DC) motor. To do so, a novel hybrid algorithm was proposed which employs a recent metaheuristic approach, named Lévy flight distribution (LFD) algorithm, and a simplex search method known as Nelder–Mead (NM) algorithm. The proposed algorithm (LFDNM) combines both LFD and NM algorithms in such a way that the good explorative behaviour of LFD and excellent local search capability of NM help to form a novel hybridized version that is well balanced in terms of exploration and exploitation. The promise of the proposed structure was observed through employment of a DC motor with PID controller. Optimum values for PID gains were obtained with the aid of an integral of time multiplied absolute error objective function. To verify the effectiveness of the proposed algorithm, comparative simulations were carried out using cuckoo search algorithm, genetic algorithm and original LFD algorithm. The system behaviour was assessed through analysing the results for statistical and non-parametric tests, transient and frequency responses, robustness, load disturbance, energy and maximum control signals. The respective evaluations showed better performance of the proposed approach. In addition, the better performance of the proposed approach was also demonstrated through experimental verification. Further evaluation to demonstrate better capability was performed by comparing the LFDNM-based PID controller with other state-of-the-art algorithms-based PID controllers with the same system parameters, which have also confirmed the superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

As a key factor characterizing the control accuracy of multi-temperature zone systems (MTZSs), the stable control of temperature field distribution uniformity and consistency is of critical importance for MTZSs, and it largely determines the product quality and production efficiency. Due to the complicated multiple input and output properties, as well as the various external variations in practice, however, it is extremely difficult to monitor the temperature field distribution in production process. To address the uniform and consistent temperature field distribution problem in MTZSs, a multi-variable dynamic matrix control (DMC)-based predictive control mechanism is proposed in this paper. Specifically, we first establish a finite element-based heat transfer model to analyse heat transfer within the multi-temperature zone, and then propose a multi-variable DMC-based decoupling design method to decompose the entire system into multiple subsystems with single-input single-output for temperature uniformity distribution control in MTZS. By utilizing the ANSYS tools to analyse the transient field temperatures, we obtain both time and space distribution characteristics of the transient temperature field with the proposed control method, and also compare such results with those obtained using the PID control method. Finally, we apply the proposed multi-variable DMC control mechanism onto a multi-temperature sintering furnace of a practical industrial product line for verification. Results show that, with the proposed control mechanism adopted, the difference between the highest and lowest temperature of any workpiece could be maintained within 5°C in the heat rising up period, which convincingly verifies the effectiveness of the proposed predictive control algorithm in different cases. [ABSTRACT FROM AUTHOR]

In this paper, the control of a fast steering mirror, which is the core element of an adaptive optics system, is investigated to suppress the beam jitter. The main source of the jitter is taken as the atmospheric turbulence. The effect of the atmospheric turbulence on the beam jitter is experimentally determined with respect to the two different refractive index structure parameters. The mathematical model of the fast steering mirror based on the atmoshperic turbulence data is obtained using the system identification. In order to overcome implementation problems, the low order proportional-integral-derivative (PID) type controllers, which minimize the H ∞ norm of the closed loop system, are designed in the centralized and the decentralized settings. In addition to this, the fixed order weighted H ∞ controller is based on the frequency characteristics of the atmospheric turbulence that is determined experimentally. Then, in order to show the effectiveness of the proposed low order PID type controller, the designed controllers are compared on the experimental setup. Finally, the simulation and the experimental results are presented. Comparison of advantageous and disadvantageous of centralized and decentralized controller architectures are discussed. [ABSTRACT FROM AUTHOR]

This paper concerns the improvement on proportional-integration-derivative (PID) control for the electro-optical tracking system for high-mobility targets. To achieve higher tracking precision and stronger disturbance rejection while fully utilizing the existing PID loop, the add-on integration module is proposed and seamlessly integrated into the conventional PID loop. It is proven that for any given conventional PID controller parameters, the add-on integration module based PID control can improve the ability of error attenuation at low frequency and keep the stability of resulting closed-loop system. More importantly, the feasible set of all parameters in the added module is explicitly given. Based on the feasible set, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to obtain the globally optimal controller's parameter under certain performance indices. The experiments are carried out for a typical electro-optical tracking test bed with several reference signals. It is shown that the proposed method has much smaller tracking errors than the existing PID method. [ABSTRACT FROM AUTHOR]

In this paper, the authors propose an optimal IMC-PID controller design for the Load Frequency Control (LFC) of large-scale power system via model approximation method. The model approximation method uses the Enhanced Differential Evolution (EDE) algorithm to determine an optimal Reduced Order Model (ROM) for the considered large-scale power system by minimizing the performance measure called Integral Square Error (ISE) between their step responses. Later, the LFC design is carried out using an optimal ROM instead of processing with the large-scale power system model. Thus, this simplifies the design, reduces the computational efforts and also helps in determining the lower order controller. An optimal IMC design methodology is proposed by minimizing ISE between the actual output and the reference input responses of the large-scale power system using EDE algorithm. Further, PID controller gains are acquired by least square model matching with the optimal IMC transfer function. The proposed IMC-PID controller design allows a satisfied reference input tracking performance, robustness in disturbance rejection and improves the dynamic stability of the power system. The proposed method is validated by applying it to a single area power system of third-order SISO model and also extended to a centralized two-area thermal–thermal non-reheated power system of a seventh-order MIMO model. The simulation results and the comparison of error performance indices show the efficacy of the proposed method over the significant methods available in the literature. [ABSTRACT FROM AUTHOR]

A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy control algorithm is introduced in the objective function of the MPCC to dynamically assign the weighting factors before the current component on the d - q axis and the influence of the objective function on the performance of the BL-IM is analyzed under different weighting factors. By discretizing the rotational speed deviation Δ ω and rotational speed deviation rate, fuzzy reasoning is performed to obtain the optimal fuzzy dynamic function. Finally, the optimal fuzzy dynamic function is selected as the objective function of the MPCC to perform the simulations and experiments. The results show that the performance of the BL-IM under the MPCC strategy based on the fuzzy dynamic objective function is improved compared with the traditional MPCC and the vector control based on the fuzzy PID, due to its better dynamic and suspension performance. Meanwhile, the stability of rotor current component is enhanced. [ABSTRACT FROM AUTHOR]

This paper provides optimum analytical tuning rules to determine tuning parameters of Integral-Proportional Derivative (I-PD) controllers for controlling integrating processes with inverse response and time delay. Integral performance criteria, such as ISTE (integral of squared time error), IST2E (integral of squared time2 error) and IST3E (integral of squared time3 error), are used to derive mentioned optimum tuning rules. The effectiveness of the proposed I-PD controller design method are shown by simulation examples. Comparisons with design methods existing in the literature, in terms of set point tracking and disturbance rejection capability, are performed to see the use of the proposed I-PD controller. Some performance measures are also given to evaluate the closed loop performances. It has been observed that the proposed I-PD controller has some important advantages over design methods used for comparison. [ABSTRACT FROM AUTHOR]

This article is devoted to stability analysis of generator excitation control system that has some time delay with fractional order proportional integral derivative controller by using direct method. When the time delay exceeds certain critical values, the excitation control system becomes unstable. In order to obtain more delay margin, in control part of the system, fractional order proportional integral derivative controller is used. A formulation is obtained to find out the maximum time delay which is known as delay margin with which the system can tolerate without any loss in its stability. All the possible stability regions analytically in the parametric space of the time delay is obtained by using an exact method and it is presented in this study. The method is formulated in frequency domain. The time-domain simulations are implemented to validate theoretical delay margin results in Matlab/Simulink. When it is compared with previous researches in literature, better stability margin is obtained. The results have shown that fractional order PID controller gives wide stability area than integer order PID controller. [ABSTRACT FROM AUTHOR]

Controlling of a rotational inverted pendulum is considered as a challenging problem, mainly due to the system's inherent nonlinear and unstable dynamics. In fact, the goal of this control is to maintain the pendulum vertically upward regardless of external disturbances. This paper aims to optimally design a model reference adaptive proportional integral derivative (PID) control for rotary inverted pendulum system based on a novel hybrid particle swarm optimization algorithm, combining sine cosine algorithm and levy flight distribution. Evaluation of the performance quality of the proposed adaptive controller is accomplished based on the stabilization and tracking control of rotary inverted pendulum system. In addition, two other PID controllers are designed to get a better understanding of the performance and robustness of the proposed controller. To make a complete comparison, the performance of the hybrid particle swarm optimization algorithm is examined against two other optimization techniques known as simple particle swarm optimization and whale optimization algorithm. Finally, the obtained simulation results demonstrate that the proposed optimal adaptive controller is superior to the other controllers, especially in terms of the transient response characteristics and the magnitude of control output signal. [ABSTRACT FROM AUTHOR]

Parameter adjustment is usually applied for designing the proportional-integral-differential (PID) controllers. However, the ability to improve control performance by adjusting parameters is limited. Hence, with the goal to achieve ideal closed-loop response, this paper takes advantage of a structural optimization method for modifying the controller model. A symbolic adaptation algorithm for fractional order PID (FOPID) controller is employed to obtain precise nonlinear controller model. Firstly, a modeling comparison for nonlinear duffing system is carried out to highlight the efficiency of the symbolic adaptation algorithm. The case study indicates the proposed algorithm can establish compact dynamic models by amending the shortcomings of symbolic regression. Secondly, the proposed controller is restructured with the linear FOPID controller and its nonlinearity is increased by adjusting controllers' components in symbolic form. The proposed controllers are simulated in an unstable second-order system, a time-delay system and a nonlinear VanderPol system. Compared with the IOPID and the FOPID controller, the symbolic adaptation algorithm improves the structural flexibility of these linear controllers. Meanwhile, the system response can better approximate the desired response and the structural integrity of the nonlinear controller model is guaranteed simultaneously. Finally, the nonlinear FOPD controllers for trajectory tracking experiments are carried out on a rotary inverted pendulum control system. [ABSTRACT FROM AUTHOR]

Wurster fluidised bed is commonly used for coating pellets in the pharmaceutical industry. Normally, the control in a Wurster fluidised bed for coating is based on point-based measurement, that is, pressure and optical probes. However, the point-based measurement methods only provide local flow information and cannot reveal the cross-sectional flow dynamics characteristics and it is difficult to control the whole process with limited data. In this paper, electrical capacitance tomography (ECT) is applied to reconstruct the solids distribution in a lab-scale Wurster fluidised bed for coating pellets and the measurements are used in a control loop of the process. The flow regime is identified from the ECT images using a simple but efficient approach. The objective of control is to keep stable minimum fluidisation and avoid undesired flow regime in the region between the outside wall and the Wurster tube, such as intermittent, plug and defluidisation. To achieve this target, a PID controller is applied to keep a low volume fraction in the annular region by adjusting the fluidisation air rate, and bang-bang control is applied to a peristaltic pump used for spraying coating solutions based on the detected flow regime. It has been found that the proposed control scheme based on the ECT measurement is effective for keeping a stable flow regime, reducing the degree of pellets agglomeration and avoiding defluidisation. [ABSTRACT FROM AUTHOR]

Due to the sensitivity of gas turbines' power generation in Iran, robustness is considered as a crucial matter and the controllers play an essential role in this objective. The common controllers used in gas turbines are usually based on standard performance. Whereas, robust controllers demonstrate acceptable performance in the presence of adverse factors such as uncertainties, disturbances, and input step changes. In this study, dynamic structures and various robust control design scenarios for an MGT-30 three-shaft gas turbine have proposed. Input-output matrices have been presented based on the dynamic model structures, and a standard robust controller structure has been used to design and present transfer matrices. Four scenarios have been considered in the robust control design according to the number of control variables, uncertainties, and disturbance effects, evolutionally, respectively. H ∞ and H 2 / H ∞ methods were used in the controller design when presenting the results of using the existing PID controller. The results show that with the increase and develop in parameters influencing the production of the actual system behavior and the controller responses improve noticeably. Finally, the fourth scenario was proposed as a scenario with more desirable robustness features than other scenarios, which provide a complete array of robust controllers. [ABSTRACT FROM AUTHOR]

Solid oxide fuel cell (SOFC) plant is considered a most important type in the field of fuel cells, which gives control difficulties such as fuel flow constraints, load disturbance, system nonlinearities, and parameter uncertainties. However, due to these difficulties, the voltage control of SOFC plant is extremely difficult. In this paper, a new intelligent proportional integral-adaptive sliding mode control (iPI-ASMC) with anti-windup compensator is proposed to control the output voltage of SOFC plant to keep up with the rated voltage. The referred iPI-ASMC is made of three sub-components: (i) an extended state observer (ESO)-based-intelligent proportional-integral to estimate the unknown dynamic, (ii) an adaptive sliding mode control is added to compensate the estimation error of unknown dynamic, and (iii) an anti-windup compensator based on back-calculation is used to deal with saturation problem which is caused by input constraints. Moreover, the effectiveness and efficiency of the proposed iPI-ASMC strategy is demonstrated by comparing with some other approaches such as conventional proportional integral-derivative (PID) controller, intelligent proportional-integral (iPI) and fuzzy PID controller. Corresponding simulation results show that the proposed iPI-ASMC approach provides better dynamic responses and outperforms to compared methods in term of settling time, peak overshoots, integral absolute error (IAE), integral square error (ISE), and integral time absolute error (ITAE). [ABSTRACT FROM AUTHOR]

In this paper, a new strategy for robust control of temperature in a steel slab reheating furnace with large time delay uncertainty based on fractional-order controllers combined with a Smith predictor is proposed. A time delay model of the preheating zone of this process is used, obtained from an identification procedure applied in a real industrial furnace. It is shown that this process experiences very large time delay changes. A fractional-order integral controller embedded in a Smith predictor structure (FI-SP) is designed, which is robust to changes in such time delay. Simulated results of a standard Proportinal Integral Derivative (PID) controller, a PID controller embedded in a Smith predictor and the proposed FI-SP controller are compared. Six performance indexes have been used in this comparison. The analysis of these indexes shows that the designed FI-SP controller exhibits the most robust behavior (lowest indexes averaged in all the range of time delay variation) for ranges that include large time delays. Then the robustness features of the FI-SP controller outperform the other integer order controllers in the time responses both to set-point changes and to step disturbances. Therefore, this controller guarantees the best accuracy of temperature control. The designed FI-SP guarantees system stability and robust performance for a high range of plant time delay uncertainties. [ABSTRACT FROM AUTHOR]

In this paper, a simple yet effective method has been raised for non-overshooting control of linear higher order plant. It is based on Posicast control, asymptotic gain scheduling and dominant pole placement by modified proportional-integral-derivative (PID) controllers, including PI-D, I-PD, PI-PD and PD-PID. The control system is composed by two closed-loops, that is, the inner loop where modified PID controllers are used to stabilize the plant by dominant pole placement, and the outer loop where asymptotic gain scheduling is used to shape the non-overshooting step response. Use of the modified PID controllers is the key to secure success of asymptotic gain scheduling, for dominance of the specified poles and phase lag dominant pole control system can be designed by these controllers in the inner loop. Three numerical examples are used to validate the method; results show that a non-overshooting control with relatively short settling time and small undershoot can be realized. [ABSTRACT FROM AUTHOR]

In practical systems having separable hard nonlinearities, sustained oscillation is detected at the steady state response due to the presence of stable limit cycles. An optimization problem is proposed to tune the fractional order controller parameters for system with multiple-nonlinearity to suppress the limit cycle magnitude in addition to meet the desired closed loop specifications. To extend the applicability of the existing Nyquist plot for predicting this limit cycle, an input dependent Nyquist plot is proposed in this paper. A servo system with backlash and relay nonlinearities is considered as a case study for limit cycle prediction with obtained fractional order controllers using an input dependent Nyquist plot. The predicted limit cycle information is compared with optimization results, input dependent root locus and are validated through closed loop simulations. Further, the robustness of the designed controllers are tested under system parameter uncertainty, disturbance and measurement noise conditions. [ABSTRACT FROM AUTHOR]

Several methods have been proposed and implemented to improve the power system stability. Based on the theory of proportional-integral-derivative (PID) excitation control and the composition principle of fuzzy PID controller, a novel PID controller based on Mamdani fuzzy inference (MFPID) is proposed in this paper. The proposed controller realizes the self-adjustment of the excitation controller parameter. Furthermore, the MFPID and power system stabilizer (PSS) subsection switch control strategy (MFPID-PSS) is presented based on the advantages of PSS and MFPID. In MFPID-PSS strategy, by switching the control strategy between MFPID and PSS at appropriate moment, the MFPID-PSS method acquires the overshoot as small as PSS, and at the same time acquires the adjusting time as short as MFPID. The simulation results demonstrate that the MFPID-PSS method improves the power system stability and has better mitigation effect for low frequency oscillations in power systems after disturbances. [ABSTRACT FROM AUTHOR]

This article presents a novel hybrid fractional-order intelligent proportional-integral-derivative (PID) controller integrated with a fractional-order fuzzy PID controller for load frequency control of a realistic interconnected two-area power system, where each area is powered from a different source. The strategy presented here involves incorporating a damping controller based on a thyristor-controlled series capacitor in the system. In doing so, the parameters of the current controller are optimized via craziness-based particle swarm optimization. The effectiveness of the strategy presented here in load frequency control is validated by extensive simulation examples. The results are compared with a recently published technique based on a fractional-order PID controller. Finally, the sensitivity analysis of the plant is studied by varying the plant parameters and operating load conditions from their prescribed values. It is observed that the current controller is a robust controller and performs satisfactorily with variations in system parameters and load patterns. [ABSTRACT FROM AUTHOR]

The analysis, identification and control of periodic systems has gained increasing interest during the last few decades due to the increased use of dynamical systems that exhibit periodic motion. The vast majority of these studies focus on the analysis and control problem for a known state-space formulation of the linear time-periodic (LTP) system. On the other hand, there are also some studies that focus on data-driven identification of LTP systems with unknown state-space formulations. However, most of these methods provide numerical estimates for the harmonic transfer functions (HTFs) of an LTP system that are extremely difficult to work with during controller design. The goal of this paper is to provide a simple controller design methodology for unknown LTP systems by utilizing so-called HTFs estimates. To this end, we first build a mathematical basis of LTP controller design for known LTP systems using the Nyquist diagrams and analytically derived HTFs. We propose a new methodology to design P-, PD- and PID-type controllers for LTP systems using Nyquist diagrams and the eigenlocus of the HTFs. Having established the HTF-based controller design procedure, we extend our methodology to unknown LTP systems by presenting a new sum-of-cosine signal-based data-driven system identification method. We show that the proposed data-driven controller design method allows estimation of the HTFs and it provides simple tools for optimizing certain time-domain performance metrics. We provide numerical examples for both known and unknown LTP system cases to illustrate the performance of the proposed controller design methodology. [ABSTRACT FROM AUTHOR]

Obtaining all feasible parameters of the proportional-integral-differential (PID) controller is the key goal in uncertain systems. This paper proposes a graphical tuning method based on an internal model control (IMC) strategy for uncertain systems with time delay. Specifically, the Kharitonov theorem is introduced first to simplify the uncertain system into 32 polynomials. Then, for each polynomial, the IMC structure is applied to reduce the tuning parameters of the PID controller in order to rapidly determine the controller parameters. Finally, the maximum sensitivity (Ms) is used to further guarantee the controlled system with a certain robustness and dynamic performance, which can portray constant gain margin and phase margin boundaries, and can even determine the range of parameters of the proposed IMC filter. Three example results from simulations are presented to demonstrate the effectiveness and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a new Proportional Integral Derivative (PID) control algorithm based on the Meixner-like model. The Meixner-like functions are an extension of Laguerre functions and are convenient when the system has a slow start. The parameters of the PID controller are auto adjusted by the model predictive control (MPC) technique. To improve system performance, the resolution of the problem of saturation of the control signal is proposed. A numerical example of a variable parameter system is given to illustrate the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

Pitch angle control is considered as a practical technique for power regulation above the rated wind speed. As a conventional pitch control, commonly the proportional and integral (PI) controller is used. However, the PI-type may not have a suitable performance if the controlled system contains non-linearity, as the wind turbine system or the desired wind trajectory varies with higher frequency. In the presence of modeling uncertainties, the necessity of methods presenting controllers with appropriate performance as the advanced control strategies is inevitable. The control approach based on Particle Swarm Optimization (PSO) algorithm may have the potential when the system contains strong non-linearity, such as strong wind turbulence. In this work, a new pitch control method based on PSO is developed. The design of the proposed strategy and its comparisons with a fuzzy logic controller and a conventional PI controller are carried out. The simulation results demonstrate that our developed approach has regulated both the output aerodynamic power and the speed in the nominal range. Results indicate that the new proposed PSO technique outperforms one of the best and earliest methods in smoothing the output power during wind fluctuations. [ABSTRACT FROM AUTHOR]

This paper deals with the systematic design and hardware co-simulation of a fuzzy gain-scheduled proportional–integral–derivative (GS-PID) controller for a quad tilt wing (QTW) type of unmanned aerial vehicles (UAVs) based on different variants of the particle swarm optimization (PSO) algorithm. The fuzzy PID gains scheduling problem for the stabilization of the roll, pitch and yaw dynamics of the QTW vehicle is formulated as a constrained optimization problem and solved thanks to improved PSO algorithms. PSO algorithms with variable inertia weight (PSO-In), PSO with constriction factor (PSO-Co) and PSO with possibility updating strategies (PSO-gbest) are proposed. Such variants of the PSO algorithm aim further to improve the exploration and exploitation capabilities of such a stochastic algorithm as well as its convergence fastness. The robustness of the designed PSO-based fuzzy GS-PID controllers under actuators faults is shown on the non-linear model of the QTW. All optimized fuzzy GS-PID controllers are then co-simulated within a processor-in-the-loop (PIL) framework based on an embedded NI myRIO-1900 board and a host PC. Such a proposed software (SW) and hardware (HW) computer aided design (CAD) platform is based on the Control Design and Simulation (CDSim) module of the LabVIEW environment as well as a set-up Network Streams-based data communication protocol. Demonstrative simulation results are presented, compared and discussed in order to improve the effectiveness of the proposed PSO-based fuzzy gains scheduled PID controllers for the QTW’s attitude flight stabilization. [ABSTRACT FROM AUTHOR]

Cooperative teleoperation combines two traditional areas of robotics, that is, teleoperation and collaborative manipulation. Cooperative telerobotic systems consist of multiple pairs of master and slave robotic manipulators operating in a shared environment. The most common control frameworks for nonlinear systems, that is, Proportional Derivative (PD) controllers, possess considerable deficiency in contact motion. In this paper, a novel control scheme is proposed for a nonlinear bilateral cooperative teleoperation system with time delay. In addition to position and velocity signals, force signals are employed in the control strategy. This modification significantly enhances the poor transparency when the slave robots are in collision with the environment. To cope with external forces measurement, a modified force estimation algorithm is proposed to estimate human and environment forces. The closed loop stability of the nonlinear cooperative teleoperation system with the proposed control scheme is investigated using the Lyapunov theory. The main achievement of this research is the stability of the closed loop cooperative teleoperation system in the presence of estimated operator and environmental forces. In addition, it is theoretically and experimentally proved that force reflection occurs and transparency is improved at the same time. Experimental results demonstrate the efficiency of the presented control strategy in free motion as well as when the slave robots are in contact with the environment. [ABSTRACT FROM AUTHOR]

One of the main renewable energy sources for the future is photovoltaic (PV) energy. Hence, working of the PV systems at maximum efficiency is taken into consideration in recent years. In this paper, for improving the performance of the global maximum power point tracking under partial shading conditions and uncertainty in parameters of DC-DC converter, a two-level adaptive control scheme is proposed. The proposed controller is capable of efficiently handling the uncertainties in the PV systems and the perturbations in the environment. The first level is global perturbation-based extremum seeking control (GPESC), and the second level is model reference adaptive control (MRAC). GPESC is used to find global maximum power point and MRAC is utilized to handle the dynamics of the DC-DC converter. Adequate difference in the time constants of control levels, causes decoupled control levels, which in turn makes it easy to design the controller. The performance of the proposed control scheme is evaluated through simulation based on four indicators: tracking accuracy, tracking efficiency, tracking speed and searching resolution for different irradiance patterns. The results are compared with GPESC and GPESC with PID controller. [ABSTRACT FROM AUTHOR]

This paper is concerned with the development of a Modified Finite Dimensional Repetitive Control (MFDRC) system. Conventional FDRC is modified through parameterization of the controller using co-prime factorization. The proposed method of controller design specifies the input output characteristics beforehand, ensuring highly accurate tracking and disturbance rejection property of the system subjected to periodic reference input. Another problem is the stabilization issues in the input–output and the disturbance rejection characteristics of a conventional repetitive control system with respect to the periodic reference input owing to have infinite number of poles in the transfer function of it. It is desirable that the transfer functions from both the reference input and the disturbance to the output have a finite number of poles and that will be taken care of in the proposed scheme of MFDRC design depicted in this paper. The performance of designed controller has been validated in steps applied to a laboratory based servo system. Comparisons are done using conventional PID controller, FDRC-based PID controller and MFDRC to show advantage, disadvantage or limitation of applied control scheme. [ABSTRACT FROM AUTHOR]

This article presents a novel control strategy on an electro-hydraulic shaking table under the acceleration control combining an amplitude phase controller and a zero phase error tracking controller with a discrete feed-forward compensator. Because of the electro-hydraulic system's nonlinearity, phase delay and amplitude attenuation exist in the acceleration response signal inevitably when the electro-hydraulic shaking table system is excited by a sine vibration signal. Moreover, the phase delay of the electro-hydraulic shaking table is composed of phase deviation and actuator delay. For improving the acceleration tracking accuracy, an amplitude phase controller is employed to compensate the phase deviation and amplitude attenuation by introducing weights to adjust the reference signal. Meanwhile, the discrete feed-forward compensator is applied to compensate the actuator delay. As an offline compensator, the zero phase error tracking controller is employed to compensate the phase delay of the response signal and improve the convergence speed of the proposed controller. Overall, the proposed control strategy combines the merits of these three controllers with better tracking performance demonstrated by simulation and experimental results. [ABSTRACT FROM AUTHOR]

In the paper, we consider the problem of global finite-time regulation of robot manipulators with position measurements only. A simple nonlinear filter is proposed to replace the joint velocity measurements. A nonlinear proportional-derivative plus gravity compensation is constructed. Global finite-time stability is proved using Lyapunov stability theory and a geometric homogeneity technique. The benefits of the proposed control are the ease of implementation and global finite-time stability without joint velocity measurements. Simulations and experimental results are presented to verify the expected performance of the proposed approach. [ABSTRACT FROM AUTHOR]

The Magnitude Optimum (MO) tuning method for PID controllers, applied on stable and non-oscillating plants, usually gives fast tracking responses and offers very good process output disturbance-rejection performance, even if the process contains significant dead time. On the other hand, when an exogenous disturbance affects the process indirectly, for example, via the plant input, slow disturbance rejection responses may be obtained. The paper proposes a way of removing this problem by means of adding two first-order filters into the control loop, without modifying the controller parameters. The filter parameters are determined so that the disturbance lag is partially compensated and the stability margin properties of the MO tuning are preserved. [ABSTRACT FROM AUTHOR]

In this paper, the problems of finite-frequency fault estimation (FE) and fault tolerant controller design are investigated for a class of systems subjected to both sensor and actuator faults. To begin with, by introducing an expanded state vector, the original system is transformed into a descriptor system, and then an unknown input proportional-integral observer (PI) is developed to provide state and FE, which avoids the overdesign problems occurring in the entire frequency domain. After this, based on reconstructed information, an observer-based fault-tolerant controller is designed to stabilize the closed-loop system even if it suffers from faults and disturbances. In addition, the sufficient conditions of the existence of the PI and fault tolerant controller are derived by linear matrix inequality (LMI) tools. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

This paper proposes a new algorithm for the design of robust PI controller for plants with parametric uncertainty using new necessary and sufficient stability conditions. Most of the control systems operate under large uncertainty causing degradation of system performance and destabilization. In order to compensate these shortcomings, a robust PI controller is designed based on new necessary and sufficient conditions for stability of a plant with parametric uncertainty, a class of interval polynomial. New necessary and sufficient conditions for the determination of robust stability of interval polynomials have been developed using the results of Routhe’s theorem and Karitonov theorem. A set of inequalities are derived based on these developed new necessary and sufficient conditions to obtain robust controller parameters. The proposed method is simple and involves less computational complexity compared with the available methods in the literature. The efficacy of the proposed methodology is demonstrated with a numerical example for successful implementation. [ABSTRACT FROM AUTHOR]

In this paper, a proportional–integral–derivative (PID) controller design method for stable and integrating time-delay systems with and without non-minimum phase zero (inverse response) using the direct method is proposed. The PID controller gains are obtained by matching the frequency response of the closed-loop control system to that of the reference model with a minimum weighted integral squared absolute error in the bandwidth region. The reference model is chosen to satisfy the desired maximum sensitivity Ms. As a result, three linear algebraic equations in three unknowns are obtained and the solution of them gives the PID controller gains. The proposed method can be applied to low- and high-order systems, and the Pade approximation of the time-delay term e−Ls is not required. [ABSTRACT FROM AUTHOR]