Suitable Controller Research Articles

Lateral safety enhancement in a full dynamic vehicle model based on series active variable-geometry suspension

Today, the importance of providing safety and stability while paying attention to the ride comfort and providing road holding is of paramount importance. This issue has become more important due to the many accidents related to vehicle rollover. In this article, an attempt has been made to reduce the risk of rollover prevention of the vehicle while paying attention to the needs of the occupant and the road. In this research, an attempt has been made to reduce the overall acceleration of the GT vehicle by using a series of active variable geometry suspensions and by using a variety of control strategies such as Fuzzy PID, LQR, Sliding mode. In previous works, PID and Skyhook controllers have been used. However, in this study, the choice of the controllers is based on attention to accuracy and optimization while pay attention to control aims. This study was performed in conditions of severe asymmetric roughness and cornering maneuvers. The examination of the results shows an improvement of more than 20% for the goal of vehicle stability while providing other suspension goals. This performance improvement occurs with the effect of suspending variable geometry along with the use of a suitable controller. It should also be noted that the improvement achieved by consuming energy is far less than other suspensions, which is the strength of the research.

Analysis and control of the fractional chaotic Hopfield neural network

The fractional Hopfield neural network (HNN) model is studied here analyzing its symmetry, uniqueness of the solution, dissipativity, fixed points etc. A Lyapunov and bifurcation analysis of the system is done for specific as well as variable fractional order. Since a very long time ago, HNN has been carefully studied and applied in various fields. Because of the exceptional non-linearity of the neuron activation function, the HNN system is stoutly non-linear. Chaos control using adaptive SMC considering disturbances and uncertainties is done about randomly chosen points by designing suitable controllers. Numerical simulations performed in MATLAB verify the efficacy of the designed controllers.

A Linear Parameter Varying Control Approach for DC/DC Converters in All-Electric Boats

Utilization of renewable energies in association with energy storage is increased in different applications such as electrical vehicles (EVs), electric boats (EBs), and smart grids. A robust controller strategy plays a significant role to optimally utilize the energy resources available in a power system. In this paper, a suitable controller for the energy resources of an EB which consists of a 5 kW solar power plant, 5 kW fuel cell, and 2 kW battery package is designed based on the linear parameter varying (LPV) controller design approach. Initially, all component dynamics are augmented, and by exploiting the sector-nonlinearity approach, the LPV representation is derived. Then, the LPV control method determines the suitable gains of the states’ feedbacks to provide the required pulse commands of the boost converters of the energy resources to regulate the DC-link voltage and supply the power of EB loads. Comparing with the state-of-the-art nonlinear control methods, the developed control approach assures the stability of the overall system, as it considers all component dynamics in the design procedure. The real-time simulation results demonstrate the performance of the designed controller in the creation of a constant DC-link voltage.

Finite-time boundedness of uncertain Hamiltonian systems via sliding mode control approach

This paper seeks to address the problem of finite-time stabilization for a class of uncertain Hamiltonian systems via sliding mode control approach. A novel sliding function in connection with the state and energy function of the considered system is constructed, and then, a suitable controller is designed to drive the state trajectories onto the specified sliding surface before the given finite-time. Moreover, the finite-time boundedness of the closed-loop system over both reaching phase and sliding motion phase are analyzed and the corresponding conditions are obtained. Furthermore, two optimization problems are formed to enhance the performance of finite-time boundedness, which will be solved via genetic optimization algorithm. Finally, a simulation example is provided to illustrate the proposed control strategy.

DC-link voltage compensation with fuzzy-based MMC to mitigate the low-order circulating current

ABSTRACT In this paper, a novel fuzzy controller-based technique is used to control the harmonics of the circulating currents in Pulse width modulation (PWM) based modular multilevel converters (MMC). This technique is based on average model circuit of MMC, which recognises the cross-relation in between the sub-module and system-level elements using dependent sources. In addition to improving the damping of the system, the main superiority of this technique is that it maintains the natural balancing property of DC bus system in a PWM-based MMC by combining upper and lower arms together, instead of considering separately like in existing schemes. Fuzzy controller is most suitable controller for the decision-making. Fuzzy gives more accuracy, for the nonlinear loads or heavy industrial applications. Fuzzy controller allows the reduction of the harmonics of the circulating current in the dc-link system and works effectively during the unbalanced AC grid conditions also. Therefore, it is suitable for multi-frequency AC systems. The accuracy of the proposed method is verified using simulation results which include the arm currents, common mode (circulating) currents and DC-link voltages along with AC grid voltage and currents.

Motion planning and control of nonholonomic mobile robot using flatness and fuzzy logic concepts

This paper presents a fuzzy-flatness technique for the efficient manipulation of mobile robots with nonholonomic constraints. A decoupled “path trajectory” planning approach is firstly defined to ensure the generation of reference trajectories that respect the nonholonomic constraints. An auto-tuned endogenous feedback control law is then designed to ensure good tracking of the desired tasks despite uncertainties. The controller gains are adjusted online by using a suitable fuzzy controller. Based on the developed algorithm and the laboratory test prototype Pioneer-3dx, numerical tests were carried out to evaluate the performances of the proposed approach.

Design of an Efficient Controller for Steam Generator System

The paper describes the establishment of a boiler control implemented on laws of fundamental physical system, effects of modelling of boiler, data of plant, constant of known physical, and adjustment of heuristic. The objective of this work it to find the modelling of the steam generator and steady the properties of the outputs to find the suitable controller. The model involves the nonlinearity mathematical model, noise of measurement, and time delays. The model represents by state space equations for each variable to describe the whole model system. The model acquired can be utilized for the algorithm for modelled-based control as a simulator of real- time for controlling and operating system. The suggested control for this system will be state feedback control to decrease the peak overshoot for each response of outputs have been seen to maintain the stability and performance.

Fixed-Time Synchronization for Different Dimensional Complex Network Systems with Unknown Parameters via Adaptive Control

This article is related to the issue of fixed-time synchronization of different dimensional complex network systems with unknown parameters. Two suitable adaptive controllers and dynamic parameter estimations are proposed such that the complex network driving and response systems can be synchronized in the settling time. Based on fixed-time control theory and Lyapunov functional method, novel sufficient conditions are provided to guarantee the synchronization within the fixed times, and the settling times are explicitly evaluated, which are independent of the initial synchronization errors. Finally, a numerical example is given to illustrate the effectiveness of the proposed control algorithms.

The Impact of Fractional-Order Control on Blood Pressure Regulation

This paper presents a fractional-order framework for control of blood pressure regulation system. A new perspective is explored to control the blood pressure in lieu of the conventional control framework. A multi-variable scenario is adopted to control two outputs: mean arterial blood pressure (MABP) and cardiac output (CO) simultaneously. Three fractional-order controllers are designed and tuned optimally for the multi-input multi-output (MIMO) blood pressure regulation system. To test the effectiveness of the designed fractional controllers, control investigations are carried out based on controller performance indices and sensitivity performance indices. Stability analysis and sensitivity analysis are carried out in order to assure stable as well as robust feedback design. Sensitivity analysis of the paper reveals the controller's ability to handle model uncertainties of the blood pressure regulation system. Numerical simulation results of the paper unfold the best suitable fractional-order controller for the enhanced closed-loop performance of the blood pressure regulation system.

A fixed-time synchronization-based secure communication scheme for two-layer hybrid coupled networks

This literature mainly investigates the fixed-time synchronization-based secure communication issue with two-layer hybrid coupled networks, which consist of multitudinous subnets with different transmittal time-delays. By the application of appropriate cluster strategy, the subnets, in both transmitter and receiver, make up several matched subnet-pairs (encryption/encryption units). The nodes may behave different dynamics in different subnet-pairs but identical ones in the same subnet-pair. Similar to the block encryption method, every matched subnet-pair is merely in charge a portion of information encryption/decryption. Many encryption/encryption units working simultaneously can manifest the intricate characteristics of nodes and increase the encryption/decryption rate. Fixed-time synchronization is applied, which means that the time for information encryption/decryption is computable. Moreover, the chaos message, generated by a chaotic system, is taken as a key array, the key space will be enlarged with node-size at transmitter. With the design of some suitable chattering-free feedback controllers, a simple fixed-time synchronization-based secure communication scheme is given and the effectiveness is proved. This scheme shows not only good performance with regard to the complexity of key arrays and timeliness but also excellent robustness to the effect of time-delays. Both the theoretic analysis and numerical emulations indicate the feasibility and utility of the given scheme.

Optimized Fuzzy-Based Wavelet Neural Network Controller for a Non-Linear Process Control System

One of the common non-linear process control problems is the continuous stirred tank reactor problem and the reactor is applied widely in chemical process industries. It is of high importance to develop a suitable controller scheme for the concentration and temperature control of the considered non-linear continuous stirred tank reactor (CSTR) model. In this paper, a novel wavelet neural network (WNN) controller model is developed to carry out the control action and to meet the performance requirements of the system model. The developed wavelet neural network model is tuned for its weights employing the proposed deterministic grey wolf optimizer algorithm and its input is fed from the Mamdani fuzzy model. The optimal number of rules to be formulated for the fuzzy rule base model is computed using the deterministic grey wolf optimizer (DGWO) which is the variant of the classic grey wolf optimizer (GWO). WNN controller devise, based on the inputs from the fuzzy model and weights from DGWO, is designed to perform control action on the non-linear CSTR model. The concentration and temperature control is carried out by the proposed controller and the responses are obtained. Also, the respective time response specifications are evaluated for the developed WNN controller. Simulation experiments prove the effectiveness of the proposed controller for the considered non-linear CSTR model in comparison with that of the existing controllers from the literature.

Finite-Time Synchronization of Clifford-Valued Neural Networks With Infinite Distributed Delays and Impulses

We study the issue of finite-time synchronization pertaining to a class of Clifford-valued neural networks with discrete and infinite distributed delays and impulse phenomena. Since multiplication of Clifford numbers is of non-commutativity, we decompose the original $n$ -dimensional Clifford-valued drive and response systems into the equivalent $2^{m}$ -dimensional real-valued counterparts. We then derive the finite-time synchronization criteria concerning the decomposed real-valued drive and response models through new Lyapunov-Krasovskii functional and suitable controller as well as new computational techniques. We also demonstrate the usefulness of the results through a simulation example.

Variable Structure Based Control for the Chemotherapy of Brain Tumor

Brain Tumor is an unwanted mass when cells grow abnormally. It puts pressure on certain areas of the brain which dangerously affects its functioning. For severe tumors like malignant, surgery is not a good option because they do not have definite boundaries and are closely attached with the other healthy tissues of the brain. So chemotherapy is preferable in this case to avoid damaging the healthy cells. The primary intention of this research is to suggest a controller for drug injection so that the tumor cells may reach the desired reference value of zero. In this paper, variable structure based nonlinear control algorithms: sliding mode control, integral sliding mode control, double integral sliding mode control and super-twisting sliding mode controllers have been proposed to reduce the tumor cells, maintain a safe number of healthy cells, keep the immune cells above a certain value and ensure suitable amount of chemotherapy drug. Lyapunov based stability theory has been used to prove stability of SMC, ISMC, DISMC and ST-SMC. MATLAB/Simulink environment has been used to analyze the performance of the proposed controllers on the basis of chattering, rate of convergence, undershoot/overshoot etc. and on the basis of these results drug through most suitable controller is advised. Among the proposed controllers, due to its better convergence, reduced chattering and less amount of drug used, ST-SMC is suggested for the chemotherapy of brain tumor.

Robust hybrid supervisory control for spacecraft close proximity missions

We consider the problem of rendezvous, proximity operations, and docking of an autonomous spacecraft. The problem can be conveniently divided into three phases: (1) rendezvous phase; (2) docking phase; and (3) docked phase. On each phase the task to perform is different, and requires a different control algorithm. Angle and range measurements are available for the entire mission, but constraints and tasks to perform are different depending on the phase. Due to the different constraints, available measurements, and tasks to perform on each phase, we study this problem using a hybrid systems approach, in which the system has different modes of operation for which a suitable controller is to be designed. Following this approach, we characterize the family of individual controllers and the required properties they should induce to the closed-loop system to solve the problem within each phase of operation. Furthermore, we propose a supervisory algorithm that robustly coordinates the individual controllers so as to provide a solution to the problem. In addition, we present specific controller designs that appropriately solve the control problems for individual phases and validate them numerically.

Superheated steam temperature system of thermal power control engineering based on neural network local multi-model prediction

The superheated steam temperature object of thermal power plant has the characteristics of time lag, inertia and time-varying parameters. The control quality of the conventional proportional integral derivate controller with fixed parameters will decrease after the object characteristics change. The generalized predictive control strategy of superheated steam temperature based on neural network local multi-model switching can achieve the goal of designing sub-controllers for fixed models under several typical operating conditions. When the system operating conditions change, the effective switching strategy is timely and accurate. Switch to the most suitable controller. The paper proposes a new smooth switching method, which can effectively suppress the large disturbance phenomenon of the object when switching. The simulation results verify the effectiveness of the control strategy.

Online Parameter Estimation of DC-DC Converter through OPC Communication Channel

System identification is a very powerful tool for determining the system model and parameters from sets of observable input and output data. Once the system parameters are obtained, the system dynamic behavior, including all the system characteristics (time constant, overshoot, settling time, etc.) can be accessed and evaluated. Despite the difficulty and communication channel lag, online parameter estimation outperforms offline system identification due to the ability to remotely monitor and control the system as well as improve the system's controller, making it more accurate and reliable. With the extreme development in technology, the importance of combining wireless networks with closed automatic control systems has emerged. This connection facilitates communication processes between the different units in the control for remotely controlled of the output. However, there are some errors affecting such system resulted from communication channel, A/D and D/A conversion process, identification process, or the existence of adaptive weight Gaussian noise. In this paper, the errors were investigated using real system, and then a suitable controller was tuned and optimized in order to reduce and eliminate various errors. The results show excellent dynamic behavior of the system under transmitting and receiving process.

On the Design of Outdoor Leader-Follower UAV-Formation Controllers From a Practical Point of View

This work presents a control structure designed to autonomously guide two of-the-shelf quadrotors navigating in outdoor environments, as a leader-follower formation. The objective is to show how simple is to design controllers to guide the two vehicles when taking into account practical assumptions and simplifications in their model. This way, the main contribution of the paper is to show how practical knowledge obtained from real experiments using of-the-shelf quadrotors, translated to the assumptions and simplifications applied to its model, can help in the design of a suitable controller. The basic premise is that the quadrotor is driven by high-level commands that excite its degrees of freedom. The control system here designed following such reasoning is implemented in a ground station that allows manual or automatic control of the leader vehicle, with the follower one always automatically controlled. Experimental results in real outdoor scenarios, subject to unpredicted disturbances, validate the assumptions and simplifications applied to the model of the quadrotor, and the proposed control structure as well.

A Hysteresis Space Vector PWM for PV Tied Z-Source NPC-MLI With DC-Link Neutral Point Balancing

The Photo-voltaic (PV) tied Z-source Neutral-point clamped multilevel inverter (Z-NPC-MLI) is used in solar grid connected applications due to its single stage conversion and better performance. Though the Z source inverters adaptation is accepted in grid connected technology, the need for suitable controller and PWM scheme are necessary to meet out the performance such as shoot through switching, neutral point balancing, and harmonic reduction. The space vector pulse width modulation (SVPWM) strategy is a prominent modulation technique for Z-source NPC-MLIs due to the flexibility to select the appropriate voltage vector. Previous publications have shown the control of a Z-source MLI using the SVPWM with and without modification of shoot through switching. However, the current controller (CC) based SVPWM is not matured, which is the most essential consideration for the grid connected inverter to provide neutral point balancing, shoot through control for low harmonic distortion and a high quality current. With all these aims, this paper presents a PV tied Z-NPC-MLI grid connected system with a unique hysteresis current control SVPWM (HSVM) strategy with neutral point (NP) balancing control and direct current control in the inverter input side. Also, the proposed HSVM is assuring the grid connection with high quality voltage and current waveforms. This CC based SVPWM for Z-NPC MLI has been validated through simulation and FPGA based experimental investigations. The results are confirmed the feasibility and reliability of the proposed HSVM for the PV tie grid connected Z- Source NPC-MLI.

Design Stable Controller for PUMA 560 Robot with PID and Sliding Mode Controller Based on PSO Algorithm

The most significant challenge facing the researcher in the field of robotics is to control the robot manipulator with appropriate overall performance. This paper focuses mainly on the novel Intelligent Particle Swarm Optimization (PSO) algorithm that was used for optimizing and tuning the gain of conventional Proportional Integral Derivative (PID), and improve the parameters of dynamic design in Sliding Mode Control (SMC), which is considered a strong nonlinear controller for controlling highly nonlinear systems, particularly for multi-degree serial link robot manipulator. Additional modified Integral Sliding Mode Controller (ISMC) was implemented to the design of dynamic system with high control theory of sliding mode controller. Intelligent Particle Swarm Optimization (PSO) algorithm was introduced for developing the nonlinear controller. The algorithm demonstrates superior performance in determining the appropriate gains and parameters value in harmony with robot scheme dynamic layout in order to achieve suitable and stable nonlinear controller, besides reduce the chattering phenomenon. PUMA robot manipulator that was used as study case in this work, shows perfect result in step response, with acceptable steady state, and overshoot, besides, eliminating the disadvantage of chattering in conventional SMC. Matlab / Simulink presents to increase the speed of matrix calculation in forward, inverse kinematics and dynamic model of manipulator. Comparison was made between the proposed method with existing methods. Result shows that integral sliding mode with PSO (ISMC/PSO) gave best result for stable step response, minimum mean square error with best objective function, and stable torque.

Finite-Time L2-Gain Asynchronous Control for Continuous-Time Positive Hidden Markov Jump Systems via T-S Fuzzy Model Approach.

This article investigates the finite-time asynchronous control problem for continuous-time positive hidden Markov jump systems (HMJSs) by using the Takagi-Sugeno fuzzy model method. Different from the existing methods, the Markov jump systems under consideration are considered with the hidden Markov model in the continuous-time case, that is, the Markov model consists of the hidden state and the observed state. We aim to derive a suitable controller that depends on the observation mode which makes the closed-loop fuzzy HMJSs be stochastically finite-time bounded and positive, and fulfill the given L2 performance index. Applying the stochastic Lyapunov-Krasovskii functional (SLKF) methods, we establish sufficient conditions to obtain the finite-time state-feedback controller. Finally, a Lotka-Volterra population model is used to show the feasibility and validity of the main results.