Biped robots have gained much attention for decades. A variety of researches has been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand the human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. Some challenges encountered in the design of biped robots are: (1) biped robots have unstable structures due to the passive joint located at the unilateral foot-ground contact. (2) They have different configuration when switching from walking phase to another. During the singlesupport phase, the robot is under-actuated, while turning into an over-actuated system during the double-support phase. (3) Biped robots have many degrees of freedom (DOFs). (4) Biped robots interact with different unknown environments. Therefore, this work attempts to investigate and resolve different issues encountered in dynamics, walking pattern generators and control of biped robots; the details as follows: • Dynamics Two walking patterns have been modeled using two well-known formulations: Lagrangian and the modified recursive Newton-Euler (N-E) formulations. The first walking pattern moves with 6 DOFs during the single support phase (SSP) changing its configuration with 7 DOFs during the double support phase (DSP) (the stance foot will move directly during the DSP). Whereas the other walking pattern has 6 DOFs during all walking phases (the SSP and the two sub-phases of the DSP); the stance foot will be fixed during the first sub-phase of the DSP. These two walking pattern are different in configuration and number of phases during the DSP. To resolve the problem of over-actuation, a linear transition function is proposed to ensure smooth transition for the biped from the SSP to the DSP and vice versa. If we assume ideal dynamic response, this strategy can resolve the discontinuity in input control torque and ground reaction forces. • Walking pattern generators Two methods have been used to generate walking patterns of biped mechanism which are (1) optimal control theory and (2) center of gravity (COG)-based model. Computational optimal control has been performed to investigate the effects of some imposed constraints on biped locomotion, such as enforcing swing foot to move level to the ground, hip motion with constant height etc. finite difference approach has been used to transcribe infinite dimensional optimal control problem into finite dimensional suboptimal control problem. Then parameter optimization has been used to get suboptimal trajectory of the biped with the imposing different constraints. In general, any artificially imposed constraint to biped locomotion can lead to increase in value of input control torques. On the other hand, suboptimal trajectory of biped robot during complete gait cycle had been accomplished with different cases such that continuous dynamic response occurs. Enforcing the biped locomotion to move with linear transition of zero-moment point (ZMP) during the DSP can lead to more energy consumption. Using the simple COG-based model, a comparative study has been conducted to generate continuous motion for COG of the biped; all these methods depend on linear pendulum model. It has been shown all these methods are equivalent. On the other hand, the effect of foot configuration has been investigated. Foot rotation can improve biped configuration at heel strike by controlling foot angle. In addition, foot motion with impact can give some freedom and uniform biped configuration compared with motion without impact. To compensate for the deviation of ZMP trajectory due to approximate model of the COG, a novel strategy has been proposed to satisfy kinematic and dynamic constraints, as well as singularity condition. A stable motion has been obtained for the target walking patterns. • Low-level control Two control schemes have been proposed based on dynamics formulations which are conventional adaptive control based on local approximation technique and Lagrangian formulation, and virtual decomposition control (VDC) based on local approximation technique and recursive N-E formulation. In the first approach (conventional control), a new representation of dynamic matrices has been coined which is computationally efficient than other representation (sparse-base representation, Kronecker product etc.). Controller structures for the SSP and the DSP have been designed in details. Since adaptive control assumes no prior knowledge of estimated weighting matrices; therefore, zero input control torques could be result in at the beginning of each phase. Consequently, discontinuous dynamic response could result. The VDC is an efficient tool for complex robotic system such as biped robot. Therefore each subsystem (link, joint) has been controlled using adaptive approximation–based VDC. A novel optimization technique has been used to deal with continuous dynamic response; however, using zero initial weighting matrices for estimation dynamic matrices and vectors could result in zero input control at beginning of each walking phases.
The heat exchanger is a device used to transfer heat energy between two fluids, hot and cold. In this work, an output feedback adaptive sliding mode controller is designed to control the temperature of the outlet cold water for plate heat exchanger. The measurement of the outlet cold temperature is the only information required. Hence, a sliding mode differentiator was designed to estimate the time derivative of outlet hot water temperature, which it is needed for constructing a sliding variable. The discontinuous gain value of the sliding mode controller is adapted according to a certain adaptation law. Two constraints which imposed on the volumetric flow rate of outlet cold (control input) were considered within the rules of the proposed
... Show MoreThe heat exchanger is a device used to transfer heat energy between two fluids, hot and cold. In this work, an output feedback adaptive sliding mode controller is designed to control the temperature of the outlet cold water for plate heat exchanger. The measurement of the outlet cold temperature is the only information required. Hence, a sliding mode differentiator was designed to estimate the time derivative of outlet hot water temperature, which it is needed for constructing a sliding variable. The discontinuous gain value of the sliding mode controller is adapted according to a certain adaptation law. Two constraints which imposed on the volumetric flow rate of outlet cold (control input) were considered within the rules of the proposed
... Show MoreThis paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin
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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
... Show MoreThe flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha
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This paper investigate a sensorless speed control of a separately excited dc motor fed from a buck type dc-dc converter. The control system is designed in digital technique by using a two dimension look-up table. The performance of the drive system was evaluated by digital simulation using Simulink toolbox of Matlab.
This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th
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