Cancer chemotherapy has been the most common cancer treatment. However, it has side effects that kill both tumor cells and immune cells, which can ravage the patient’s immune system. Chemotherapy should be administered depending on the patient’s immunity as well as the level of cancer cells. Thus, we need to design an efficient treatment protocol. In this work, we study a feedback control problem of tumor-immune system to design an optimal chemotherapy strategy. For this, we first propose (...) a mathematical model of tumor-immune interactions and conduct stability analysis of two equilibria. Next, the feedback control is found by solving the Hamilton–Jacobi–Bellman equation. Here, we use an upwind finite-difference method for a numerical approximate solution of the HJB equation. Numerical simulations show that the feedback control can help determine the treatment protocol of chemotherapy for tumor and immune cells depending on the side effects. (shrink)

The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the solution (...) of stochastic nonlinear system objects satisfies the existence of uniqueness, ensuring that the system is globally asymptotically stable in the sense of probability. Furthermore, it is concluded that the system is inversely optimally stable in the sense of probability. Finally, we apply the theoretical results to the practical subsea intelligent electroexecution robot control system and obtain good results. (shrink)

The two-wheeled self-balancing robot is based on the axletree and inverted pendulum. Its balancing problem requires a control action. To speed up the response of the robot and minimize the steady state error, in this article, a grey wolf optimizer method is proposed for TWSBR control based on state space feedback control technique. The controller stabilizes the balancing robot and minimizes the overshoot value of the system. The dynamic model of the system is derived based on (...) Euler formula and linearized to state space representation to enhance the control technique. Then, the GWO optimizes the state feedback controller parameters. Simulation results show that the system reaches the zero steady-state error with less than 2 ms, which proves the effectiveness of the proposed controller over the classical state feedback controller in terms of fast response, very small overall error, and minimum overshoot. (shrink)

This paper is concerned with the optimal output feedback control problem for networked control systems with Markovian packet losses. In this paper, the packet losses occur both between the sensor and controller and between the controller and actuator. Moreover, the packet loss channels are described with two-state Markov chains. Since the precise state information cannot be obtained, thus an optimal recursive estimator is designed. Furthermore, by adopting the dynamic programming approach, we derive the optimal (...) output feedback control, which is based on the solution to a given modified Riccati equation. The obtained results can be seen as an important implementation of the control theory for NCSs with unreliable communication channels. (shrink)

Current models of speech motor control rely on either trajectory-based control (DIVA, GEPPETO, ACT) or a dynamical systems approach based on feedback control (Task Dynamics, FACTS). While both approaches have provided insights into the speech motor system, it is difficult to connect these findings across models given the distinct theoretical and computational bases of the two approaches. We propose a new extension of the most widely used dynamical systems approach, Task Dynamics, that incorporates many of the (...) strengths of trajectory-based approaches, providing a way to bridge the theoretical divide between what have been two separate approaches to understanding speech motor control. The Task Dynamics (TD) model posits that speech gestures are governed by point attractor dynamics consistent with a critically damped harmonic oscillator. Kinematic trajectories associated with such gestures should therefore be consistent with a second-order dynamical system, possibly modified by blending with temporally overlapping gestures or altering oscillator parameters. This account of observed kinematics is powerful and theoretically appealing, but may be insufficient to account for deviations from predicted kinematics – i.e., changes produced in response to some external perturbations to the jaw, changes in control during acquisition and development, or effects of word/syllable frequency. Optimization, such as would be needed to minimize articulatory effort, is also incompatible with the current TD model, though the idea that the speech production systems economizes effort has a long history and, importantly, also plays a critical role in current theories of domain-general human motor control. To address these issues, we use Dynamic Movement Primitives (DMPs) to expand a dynamical systems framework for speech motor control to allow modification of kinematic trajectories by incorporating a simple, learnable forcing term into existing point attractor dynamics. We show that integration of DMPs with task- based point-attractor dynamics enhances the potential explanatory power of TD in a number of critical ways, including the ability to account for external forces in planning and optimizing both kinematic and dynamic movement costs. At the same time, this approach preserves the successes of Task Dynamics in handling multi-gesture planning and coordination. (shrink)

This paper presents a novel fractional-order PID controller tuning strategy based on Bode’s optimal loop shaping which is commonly used for LTI feedback systems. Firstly, the controller parameters are achieved based on flat phase property and Bode’s optimal reference model, so that the controlled system is robust to gain variations and can achieve desirable transient performance according to various control requirements. Then, robustness analysis of the controlled system is carried out to support the results. Furthermore, the (...) parameter setting is analyzed to demonstrate the superiority of the proposed controller. At last, some simulation examples are shown to verify the accuracy and usefulness of the proposed control strategy. The proposed fractional-order PID controller does not have any restriction on the controlled plant, so it can be widely applied on both integer-order and fractional-order systems. (shrink)

Wearing a myoelectric prosthesis is a basic way for limb amputees to restore their lost limb functions in the activities of daily living. However, it is estimated that around 40% of amputees refuse the prosthesis. One of the primary reasons would be that the current prostheses lack appropriate sensory feedback. Currently, the amputees only depend on their visual feedback when using their arm prostheses. It would be difficult for them to accurately control the wrist position, which is (...) vital for flexible manipulation in ADLs. This manuscript designed a myoelectric arm prosthesis with wrist position feedback. To study the effect level of position feedback on prosthetic control, two tests were performed. The vibrotactile perception range test aims to analyze the perception sensitivity of the vibration in humans and obtain the optimal perception range utilized in the sensory feedback test. The sensory feedback test analyzes the effectiveness of the position feedback by comparing three feedback methods of Vis-FB, WP-FB, and a combination of Vis-FB and WP-FB. These tests were conducted by asking six able-bodied subjects to perform 20 movement combinations of five target positions. The WP-FB was transiently activated with five vibrating motors embedded in an armband to stimulate the arm stump when the prosthetic wrist rotates to the target positions. Our experimental results showed that when WP-FB was added to the prosthetic control, the absolute angular error of the prosthetic wrist declined from 4.50° to 1.08° while the success rate 3 increased from 0.34 to 0.84, respectively. This study demonstrates the importance of WP-FB to the effective control of the arm prosthesis. (shrink)

In order to avoid the motor damage caused by excessive temperature rise of armature winding of the walking motor during braking of high-voltage inspection robot in complexity microgrid networks, an unpowered downhill speed and energy recovery optimization control strategy is proposed based on temperature rise characteristics of the walking motor. Firstly, the thermal equivalent circuit model of the walking motor is established, and the mapping relationship between the armature winding temperature of the walking motor and ambient temperature is solved; (...) secondly, the influence of armature winding temperature on unpowered downhill speed and energy recovery control strategy of robot is analyzed; thirdly, according to the temperature of front and rear wheel walking motors and the temperature difference between them, the optimal control strategy of unpowered downhill speed and energy recovery of robot is put forward; fourthly, by adjusting the duty ratio u of the energy consumption speed control system and the front wheel feedback brake distribution factor λ, the temperature difference between the front and rear wheel walking motors is reduced. Through the experimental analysis on the simulated line, it is verified that the unpowered downhill speed and energy recovery optimization control method based on the temperature rise characteristics of the walking motor can effectively reduce the temperature difference between the front and rear wheels. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising (...) levels of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (shrink)

The question “How can humans learn efficiently to make decisions in a complex, dynamic, and uncertain environment” is still a very open question. We investigate what effects arise when feedback is given in a computer-simulated microworld that is controlled by participants. This has a direct impact on training simulators that are already in standard use in many professions, e.g., for flight simulators for pilots, and a potential impact on a better understanding of human decision making in general. Our study (...) is based on a benchmark microworld with an economic framing, the IWR Tailorshop. N=94 participants played four rounds of the microworld, each 10 months, via a web interface. We propose a new approach to quantify performance and learning, which is based on a mathematical model of the microworld and optimization. Six participant groups receive different kinds of feedback in a training phase, then results in a performance phase without feedback are analyzed. As a main result, feedback of optimal solutions in training rounds improved model knowledge, early learning, and performance, especially when this information is encoded in a graphical representation. (shrink)

When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...) unattended stimulus, they rely less on prior information about the probed stimulus’ identity. The model is in part inspired by recent findings that attention reduces trial-by-trial variability of the neuronal population response and that they use a common criterion for attended and unattended trials. In five different visual discrimination experiments, when attention was directed away from the target stimulus, subjects did not adjust their response bias in reaction to a change in stimulus presentation frequency despite being fully informed and despite the presence of performance feedback and monetary and social incentives. This indicates that subjects did not rely more on the priors under conditions of inattention as would be predicted by a Bayes-optimal observer model. These results inform and constrain future models of Bayesian inference in the human brain. (shrink)

Recent work has demonstrated that the sense of agency is not only determined by efference-copy-based internal predictions and internal comparator mechanisms, but by a large variety of different internal and external cues. The study by Moore and colleagues [Moore, J. W., Wegner, D. M., & Haggard, P. . Modulating the sense of agency with external cues. Conscious and Cognition] aimed to provide further evidence for this view by demonstrating that external agency cues might outweigh or even substitute efferent signals to (...) install a basic registration of self-agency. Although the study contains some critical points that, so we argue, are central to a proper interpretation of the data, it hints at a new perspective on agency: optimal cue integration seems to be the key to a robust sense of agency. We here argue that this framework could allow integrating the findings of Moore and colleagues and other recent agency studies into a comprehensive picture of the sense of agency and its pathological disruptions. (shrink)

Automatic Generation Control in modern power systems is getting complex, due to intermittency in the output power of multiple sources along with considerable digressions in the loads and system parameters. To address this problem, this paper proposes an approach to calculate Power System Restoration Indices of a 2-area thermal-hydro restructured power system. This study also highlights the necessary ancillary service requirements for the system under a deregulated environment to cater to large-scale power failures and entire system outages. An abrupt (...) change in consumer load demands and disturbances in any control region of a multiarea system causes severe fluctuations in frequency and interarea power exchanges. However, simple Proportional and Integral controllers are most prevalent in the literature to effectively resolve AGC issues, while its integral gain is smaller due to the larger overshoot in transient performance. Therefore, an attempt has been made with a novel control strategy, known as the pseudoderivative feedforward with feedback controller, is developed to keep the interarea power exchanges and the frequency to the specified limits after load changes. A PDFF controller is designed and implemented using the flower pollination algorithm to obtain optimal dynamic performance for different types of potential power flows in a restructured power system under investigation. The proposed PDFF controller localizes the zero at an optimal place that reduces the rise time of the step-response to reduce the excessive overshoot and gives much better dynamic performances as compared to the PI control structure. The Integral Square Error is considered as a performance criterion to derive the optimized gain of the PDFF control structure using FPA. Different PSRI are computed based on the transient response of the 2-area deregulated multisource system and different restoration measures to be taken are also discussed. The simulation results clearly show that the proposed approach is very powerful in decreasing the frequency and tie-power digressions under different load perturbations. (shrink)

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. (...) For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path. (shrink)

We test people's ability to optimize performance across two concurrent tasks. Participants performed a number entry task while controlling a randomly moving cursor with a joystick. Participants received explicit feedback on their performance on these tasks in the form of a single combined score. This payoff function was varied between conditions to change the value of one task relative to the other. We found that participants adapted their strategy for interleaving the two tasks, by varying how long they spent (...) on one task before switching to the other, in order to achieve the near maximum payoff available in each condition. In a second experiment, we show that this behavior is learned quickly and remained stable for as long as the payoff function did not change. The results of this work show that people are adaptive and flexible in how they prioritize and allocate attention in a dual-task setting. However, it also demonstrates some of the limits regarding people's ability to optimize payoff functions. (shrink)

Utilization of renewable energies in association with energy storage is increased in different applications such as electrical vehicles, electric boats, 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 (...) 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. (shrink)

Dependency relationships within the cell cycle allow cells to arrest the cycle reversibly in response to agents or conditions that interfere with specific aspects of its normal progression. In addition, overlapping pathways exist which also arrest the cell cycle in response to DNA damage. Collectively, these control mechanisms have become known as checkpoints. Analysis of checkpoints is facilitated by the fact that dependency relationships within the cell cycle, such as the dependency of mitosis on the completion of DNA synthesis, (...) and the DNA damage checkpoint can be separated genetically. In fission yeast, Schizosaccharomyces pombe, the dependency of mitosis on prior completion of DNA synthesis is mediated through tyrosine‐15 phosphorylation of the ubiquitous mitotic regulator p34cdc2. In contrast, the arrest of mitosis caused by DNA damage acts through a separate mechanism that appears to be independent of tyrosine‐15 phosphorylation. Despite these distinct interactions with the mitotic machinery, the majority of fission yeast mutants that are deficient in mitotic arrest after DNA damage are also unable to respond to inhibition of DNA synthesis. In this essay we survey the current knowledge concerning feedback controls and checkpoints within fission yeast and relate this to information derived from other systems. (shrink)

This 1992 book examines alternative methods for achieving optimality without all the apparatus of economic planning, or a vain reliance on sufficiently 'perfect' competition. All rely entirely on the self-interest of economic agents and voluntary contract. The author considers methods involving feedback iterative controls which require the prior selection of a 'criterion function', but no prior calculation of optimal quantities. The target is adjusted as the results for each step become data for the criterion function. Implementation is built (...) in by the incentive structure, and all controls rely on consistency with the self-interest of individuals. The applicability of all the methods is shown to be independent of the form of ownership of enterprises: examples are given for industries which are wholly privately owned, wholly nationalized, mixed and labour-managed. (shrink)

Spontaneous polarization without spatial cues, or symmetry breaking, is a fundamental problem of spatial organization in biological systems. This question has been extensively studied using yeast models, which revealed the central role of the small GTPase switch Cdc42. Active Cdc42‐GTP forms a coherent patch at the cell cortex, thought to result from amplification of a small initial stochastic inhomogeneity through positive feedback mechanisms, which induces cell polarization. Here, I review and discuss the mechanisms of Cdc42 activity self‐amplification and dynamic (...) turnover. A robust Cdc42 patch is formed through the combined effects of Cdc42 activity promoting its own activation and active Cdc42‐GTP displaying reduced membrane detachment and lateral diffusion compared to inactive Cdc42‐GDP. I argue the role of the actin cytoskeleton in symmetry breaking is not primarily to transport Cdc42 to the active site. Finally, negative feedback and competition mechanisms serve to control the number of polarization sites. (shrink)

Negative feedback is an important mechanism whereby the organism maintains its balance in a complicated system. It may beregarded as a modern version of the ancient Eastern wisdom of Yin and Yang balance. Control of pain and analgesia, is no exception: CCK seems to serve as a built-in mechanism for the modulation of opioid analgesia system [dickenson].

A novel conservative chaotic system with no equilibrium is investigated in this study. Various dynamics such as the conservativeness, coexistence, symmetry, and invariance are presented. Furthermore, a partial-state feedback control scheme is proposed, and the stable domain of control parameters is analyzed based on the degenerate Hopf bifurcation. In order to verify the numerical simulation analysis, an analog circuit is designed. The simulation results show that the output of the analog circuit system can reproduce the numerical simulation (...) results and verify the correctness of the theoretical analysis. (shrink)

This study focuses on the static output feedback control of nonlinear Markov jump singularly perturbed systems within the framework of Takagi–Sugeno fuzzy approximation. From a practical point of view, the phenomenon of asynchronous switching between the plant and the controller is considered and characterized by a finite piecewise-homogenous Markov process. Particularly, for facilitating the controller synthesis, the closed-loop system is transformed into a fuzzy Markov jump singularly perturbed descriptor system by adopting descriptor representation. In order to fully accommodate (...) the system features, an appropriate stochastic Lyapunov function is constructed. Afterwards, by combining Finsler’s lemma, the mean square exponential admissibility of the system is analyzed. The conditions ensuring the existence of the predesigned controller are given and further solved by designing a brief search algorithm. Finally, a typical circuit system is used to demonstrate the application potential of the developed control technology and the effectiveness of the control strategy. (shrink)

Security issue against different attacks is the core topic of cyberphysical systems. In this paper, optimal control theory, reinforcement learning, and neural networks are integrated to provide a brief overview of optimal robust control strategies for a benchmark power system. First, the benchmark power system models with actuator and sensor attacks are considered. Second, we investigate the optimal control issue for the nominal system and review the state-of-the-art RL methods along with the NN implementation. (...) Third, we propose several robust control strategies for different types of cyberphysical attacks via the optimal control design, and stability proofs are derived through Lyapunov theory. Furthermore, the stability analysis with the NN approximation error, which is rarely discussed in the previous works, is studied in this paper. Finally, two different simulation examples demonstrate the effectiveness of our proposed methods. (shrink)

A long-standing problem in biology, economics, and social sciences is to understand the conditions required for the emergence and maintenance of cooperation in evolving populations. This paper investigates how to promote the evolution of cooperation in the Prisoner’s Dilemma game. Differing from previous approaches, we not only propose a tag-based control mechanism but also look at how the evolution of cooperation by TBC can be successfully promoted. The effect of TBC on the evolutionary process of cooperation shows that it (...) can both reduce the payoff of defectors and inhibit defection; although when the cooperation rate is high, TBC will also reduce the payoff of cooperators unless the identified rate of the TBC is large enough. An optimal timing control of switched replicator dynamics is designed to consider the control costs, the cooperation rate at terminal time, and the cooperator’s payoff. The results show that the switching control between an optimal identified rate control of the TBC and no TBC can properly not only maintain a high cooperation rate but also greatly enhance the payoff of the cooperators. Our results provide valuable insights for some clusters, for example, logistics parks and government, to regard the decision to promote cooperation. (shrink)

Actuator saturation phenomenon often exists in the actual control system, which could destroy the closed-loop performance of the system and even lead to unstable behavior. Our main contribution is to provide an antiwindup recursive dynamic surface control for a discrete-time system with an unknown state and actuator saturation. The fuzzy compensator is added to perform as an active disturbance rejection term in the feedforward path to avoid windup caused by input saturation. To construct output feedback control, (...) the system is transformed into the form of pure-feedback and an improved HOSM observer is designed to carry out future output prediction. Based on which RDSC is synthesized, only one fuzzy logic system is used and the controller singularity is completely avoided. In addition, the simulation and numeral examples using a continuous stirred tank reactors system with actuator saturation are provided and the results show that the strategy owns good robustness and effectively compensates for the disturbance caused by actuator saturation in the presence of a discrete-time system with an unmeasurable state. (shrink)