Sliding-Mode Controller Based on Fractional Order Calculus for a Class of Nonlinear Systems

This  paper  presents  a  new  approach  of  fractional  order  sliding  mode controllers  (FOSMC)  for  a  class  of  nonlinear  systems  which  have  a  single input and two outputs (SITO). Firstly, two fractional order sliding surfaces S1 and S2 were proposed with an intermediate variable z transferred from S2 to S1 in order to hierarchy the two sliding surfaces. Secondly, a control law was determined  in  order  to  control  the  two  outputs.  A  sliding  control  stability condition  was  obtained  by  using  the  properties  of  the  fractional  order calculus.  Finally,  the  effectiveness  and  robustness  of  the  proposed  approach  were demonstrated by comparing its performance with the one of the conventional sliding mode controller (SMC), which is based on integer order derivatives. Simulation results were provided for the cases of controlling a ball-beam and inverted pendulum systems

Optimal fuzzy proportional-integral-derivative control for a class of fourth-order nonlinear systems using imperialist competitive algorithms

The proportional integral derivative (PID) controller has gained wide acceptance and use as the most useful control approach in the industry. However, the PID controller lacks robustness to uncertainties and stability under disturbances. To address this problem, this paper proposes an optimal fuzzy-PID technique for a two-degree-of-freedom cart-pole system. Fuzzy rules can be combined with controllers such as PID to tune their coefficients and allow the controller to deliver substantially improved performance. To achieve this, the fuzzy logic method is applied in conjunction with the PID approach to provide essential control inputs and improve the control algorithm efficiency. The achieved control gains are then optimized via the imperialist competitive algorithm. Consequently, the objective function for the cart-pole system is regarded as the summation of the displacement error of the cart, the angular error of the pole, and the control force. This control concept has been tested via simulation and experimental validations. Obtained results are presented to confirm the accuracy and efficiency of the suggested method. © 2022 S. Hadipour Lakmesari et al

Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton

A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user’s intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems

Two-Wheeled LEGO EV3 Robot Stabilisation Control Using Fuzzy Logic Based PSO Algorithm

This paper presents a control system design to stabilise a two-wheeled Lego EV3 robot. This robot is developed based on the inverted pendulum. The mathematical modelling is derived based on this robot and using Euler Lagrange equation and represented in Simulink block diagram. The fuzzy logic controller is used to stabilise this robot with Particle Swarm Optimization algorithm for optimum performance of the system. The result of the fuzzy logic controller without optimisation is compared with the fuzzy logic controller with optimisation. Using the Simulink block diagram, the result of optimum tilt angle and control input signal are presented. The results show that the fuzzy logic controller with optimisation is able to improve the performance of the solution when compared to the fuzzy logic controller without optimisation

Discrete-Inverse Optimal Control Applied to the Ball and Beam Dynamical System: A Passivity-Based Control Approach

This express brief deals with the problem of the state variables regulation in the ball and beam system by applying the discrete-inverse optimal control approach. The ball and beam system model is defined by a set of four-order nonlinear differential equations that are discretized using the forward difference method. The main advantages of using the discrete-inverse optimal control to regulate state variables in dynamic systems are (i) the control input is an optimal signal as it guarantees the minimum of the Hamiltonian function, (ii) the control signal makes the dynamical system passive, and (iii) the control input ensures asymptotic stability in the sense of Lyapunov. Numerical simulations in the MATLAB environment allow demonstrating the effectiveness and robustness of the studied control design for state variables regulation with a wide gamma of dynamic behaviors as a function of the assigned control gains

การควบคุมตำแหน่งของระบบบอลและบีมด้วยการควบคุมแบบฟัซซี

บทความนี้อธิบายวิธีการออกแบบการควบคุมแบบฟัซซีเพื่อที่จะควบคุมตำแหน่งการเคลื่อนที่ของลูกบอลของระบบบอลและบีม แบบจำลองของระบบบอลและบีมถูกใช้เพื่อหาค่าอัตราการขยายป้อนกลับให้กับตัวควบคุมอินพุตทั้งหมดสามารถถูกปรับได้ด้วยอัตราการขยายป้อนกลับนี้ ตัวควบคุมฟัซซีแบบสี่อินพุต สองอินพุต และแบบสองลูปถูกออกแบบและนำเสนอ ตัวควบคุมแบบพีไอดีถูกนำมาทดลอง ผลตอบสนองเชิงเวลาของการควบคุมทั้งหมดถูกนำมาเปรียบเทียบ ผลการทดลองพบว่าผลตอบสนองเชิงเวลาของตัวควบคุมแบบฟัซซีแบบสี่อินพุตสามารถให้ผลตอบสนองของระบบได้ดีกว่าการควบคุม แบบฟัซซีสองอินพุต แบบฟัซซีสองลูปและแบบพีไอดีคำสำคัญ: ระบบบอลและบีม การควบคุมแบบพีไอดี การควบคุมแบบฟัซซีสองอินพุต สี่อินพุต สองลูปThis paper describes a method to design a fuzzy control to control the movement of the ball and beam system. Ball and beam model is used to evaluate the feedback gains of the controller. All inputs can be adjusted by this feedback gains. The fuzzy controllers with four inputs, two inputs and two loops are designed and presented. The PID controller is implemented. The time responses of all controllers are compared. The experimental results indicate that the time responses of the fuzzy controller with four inputs give better performance than all other controllers.Keywords: Ball and Beam System, PID Control, Fuzzy Control with Two Inputs, Four Inputs, Two Loop

Multi-agent Optimal Control of Ball Balancing on a Mobile

Multi-agent systems have origin in computer engineering however, they have found applications in different field. One of the newly emerged problems in multi-agent systems is multi-agent control. In multi-agent control it is desired that the control is done in distributed manner. That is the controller of each agent should be implemented based on local feedback. In this a mechanism is introuded as a test bed for multi-agent control systems. The introduced mechanism is balancing of a ball on link located on a planar mobile robot. Dynamic equations of the mechanism is derived and the control task is distributed among two agents. For each agent a two loop controller designed wherein external loop is a LQR controller and inner loop is a simple proportional controller. Regulation and fault tolerance performance of controller scheme is evaluated by simulations

A Framework for Life Cycle Cost Estimation of a Product Family at the Early Stage of Product Development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system

An Approach to Fuzzy Modeling of Electromagnetic Actuated Clutch Systems

This paper proposes an approach to fuzzy modeling of a nonlinear servo system application represented by an electromagnetic actuated clutch system. The nonlinear model of the process is simplified and linearized around several operating points of the input-output static map of the process. Discrete-time Takagi-Sugeno (T-S) fuzzy models of the processes are derived on the basis of the modal equivalence principle; the rule consequents of these T-S fuzzy models contain the state-space models of the process. Three discrete-time T-S fuzzy models are suggested and compared. The simulation results validate the new fuzzy models of the electromagnetic actuated clutch system